Codebook SIBS 8282

IDSEX

Sex of participant

Distribution

Distribution of values for IDSEX

0 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
IDSEX	Sex of participant	haven_labelled	0	1	1	2	2	1.566108	0.4958414	2	<U+2586><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2587>

Value labels

Response choices
name	value
male	1
female	2

IDAB

Whether child is adopted or biologically related to rearing parents

Distribution

Distribution of values for IDAB

0 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
IDAB	Whether child is adopted or biologically related to rearing parents	haven_labelled	0	1	1	1	2	1.437616	0.4963241	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2586>

Value labels

Response choices
name	value
adoptive	1
biological	2

IDFAMAB

Whether family is adoptive, non-adoptive, or mixed

Distribution

Distribution of values for IDFAMAB

0 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
IDFAMAB	Whether family is adoptive, non-adoptive, or mixed	haven_labelled	0	1	1	2	3	1.733706	0.7685815	3	<U+2587><U+2581><U+2581><U+2586><U+2581><U+2581><U+2581><U+2583>

Value labels

Response choices
name	value
adoptive	1
biological	2
mixed	3

IN_MPQ_AGE

Age at intake

Distribution

Distribution of values for IN_MPQ_AGE

770 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
IN_MPQ_AGE	Age at intake	numeric	770	0.283054	16	17	21	17.32176	1.111559	<U+2587><U+2586><U+2583><U+2582><U+2581>

FU1_MPQ_AGE

Age at follow-up 1

Distribution

Distribution of values for FU1_MPQ_AGE

241 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
FU1_MPQ_AGE	Age at follow-up 1	numeric	241	0.7756052	15	18	25	18.67604	1.630421	<U+2583><U+2587><U+2583><U+2581><U+2581>

FU3_MPQ_AGE

Age at follow-up 3

Distribution

Distribution of values for FU3_MPQ_AGE

360 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
FU3_MPQ_AGE	Age at follow-up 3	numeric	360	0.6648045	26	32	41	31.8788	2.729035	<U+2583><U+2587><U+2587><U+2583><U+2581>

IN_NCDATE

Date of intake

Distribution

## 236  unique, categorical values, so not shown.

770 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	min	median	max
IN_NCDATE	Date of intake	Date	770	0.283054	236	1998-12-11	2000-07-02	2004-06-14

FU1_NCDATE

Date of follow-up 1

Distribution

## 468  unique, categorical values, so not shown.

241 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	min	median	max
FU1_NCDATE	Date of follow-up 1	Date	241	0.7756052	468	2003-02-27	2004-10-26	2008-01-03

FU3_NCDATE

Date of follow-up 3

Distribution

## 343  unique, categorical values, so not shown.

360 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	min	median	max
FU3_NCDATE	Date of follow-up 3	Date	360	0.6648045	343	2018-03-29	2018-08-17	2020-04-13

Scale: AC_1

Overview

Reliability: .

Missing: 780.

Likert plot of scale AC_1 items

Distribution of scale AC_1

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	IN_Q8, IN_Q32, IN_Q46, IN_Q56, IN_Q65, IN_Q74, IN_Q82, IN_Q115, IN_Q125, IN_Q137, IN_Q145 & IN_Q197
Observations:	294
Positive correlations:	66
Number of correlations:	66
Percentage positive correlations:	100

Estimates assuming interval level

Omega (total):	0.89
Omega (hierarchical):	0.69
Revelle’s Omega (total):	0.89
Greatest Lower Bound (GLB):	0.91
Coefficient H:	0.87
Coefficient Alpha:	0.86

(Estimates assuming ordinal level not computed, as the polychoric correlation matrix has missing values.)

Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help (‘?ufs::scaleStructure’) for more information.

Eigen values

4.777, 1.112, 1.087, 0.919, 0.726, 0.624, 0.579, 0.557, 0.457, 0.406, 0.392 & 0.364

Factor analysis (reproducing only shared variance)

	ML1	ML2	ML3
IN_Q8	0.133	0.609	-0.008
IN_Q32	0.099	0.095	0.388
IN_Q46	0.743	0.053	-0.053
IN_Q56	-0.041	0.872	0.016
IN_Q65	0.406	-0.103	0.237
IN_Q74	0.137	0.139	0.382
IN_Q82	-0.013	0.001	0.905
IN_Q115	0.359	-0.034	0.065
IN_Q125	0.402	0.031	0.129
IN_Q137	0.763	-0.064	0.034
IN_Q145	0.289	0.334	0.189
IN_Q197	0.709	0.070	-0.012

Component analysis (reproducing full covariance matrix)

	TC1	TC2	TC3
IN_Q8	-0.062	0.804	0.100
IN_Q32	-0.022	0.286	0.650
IN_Q46	0.550	0.133	0.277
IN_Q56	0.014	0.862	-0.076
IN_Q65	0.775	-0.201	0.057
IN_Q74	0.366	0.408	-0.073
IN_Q82	0.455	0.280	0.196
IN_Q115	0.051	-0.101	0.867
IN_Q125	0.762	0.042	-0.256
IN_Q137	0.644	0.091	0.178
IN_Q145	0.320	0.553	0.035
IN_Q197	0.629	0.164	0.109

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
IN_Q8	2.68707482993197	3	0.78228970769195	0.884471428420359	1	0.0515834212309632	1	2	4	4	-0.207664831827518	-0.661961075176956	0.149659863945578	294	294
IN_Q32	2.25510204081633	2	0.75722644006408	0.870187589008301	1	0.0507503707993585	1	1	3	4	0.387596781758347	-0.44719288735872	0.120748299319728	294	294
IN_Q46	2.60204081632653	3	0.977606742355645	0.988739977120196	1	0.0576644864817999	1	2	4	4	-0.0302101196884747	-1.04838720007547	0.147959183673469	294	294
IN_Q56	2.67687074829932	3	0.799667990062919	0.894241572542297	1	0.0521532276074442	1	2	4	4	-0.0958713273199057	-0.779880400990226	0.168367346938776	294	294
IN_Q65	2.57142857142857	3	0.798634812286689	0.893663702008026	1	0.0521195255134834	1	2	4	4	0.0577771012659709	-0.776498987035308	0.168367346938776	294	294
IN_Q74	3.12585034013605	3	0.581377260801932	0.762480990452832	1	0.0444687944090802	1	2	4	4	-0.681389875676662	0.297893703273696	0.163265306122449	294	294
IN_Q82	2.69387755102041	3	0.834296858675211	0.913398521279299	1	0.0532704835463563	1	2	4	4	-0.221284083169471	-0.749362422732018	0.144557823129252	294	294
IN_Q115	1.84353741496599	2	0.767244781871793	0.875925100606092	1	0.0510849892709749	1	1	3	4	0.893005150389228	0.141589177050258	0.202380952380952	294	294
IN_Q125	2.85714285714286	3	0.703071672354949	0.838493692495626	1	0.0489019452180102	1	2	4	4	-0.214841969276668	-0.680020137554574	0.144557823129252	294	294
IN_Q137	2.85714285714286	3	0.805460750853242	0.897474651927976	2	0.052341784626321	1	2	4	4	-0.285221024208644	-0.782769418759679	0.139455782312925	294	294
IN_Q145	2.62585034013605	3	0.705950639641522	0.840208688149273	1	0.0490019657956894	1	2	4	4	-0.106772849103044	-0.564033745916619	0.171768707482993	294	294
IN_Q197	2.80272108843537	3	0.786886768359221	0.887066383287756	1	0.0517347620721698	1	2	4	4	-0.222962525979173	-0.758179162632961	0.147959183673469	294	294

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
IN_Q8	I often keep working on a problem even if I am very tired	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	772	0.2811918	1	3	4	2.695364	0.8816579	4	<U+2582><U+2581><U+2586><U+2581><U+2581><U+2587><U+2581><U+2583>
IN_Q32	I enjoy putting in long hours	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	773	0.2802607	1	2	4	2.262459	0.8761008	4	<U+2583><U+2581><U+2587><U+2581><U+2581><U+2585><U+2581><U+2582>
IN_Q46	People say that I drive myself hard	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	773	0.2802607	1	3	4	2.598007	0.9905534	4	<U+2583><U+2581><U+2587><U+2581><U+2581><U+2587><U+2581><U+2586>
IN_Q56	I often go on working on a problem long after others would have given up	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	773	0.2802607	1	3	4	2.687708	0.8918978	4	<U+2582><U+2581><U+2587><U+2581><U+2581><U+2587><U+2581><U+2585>
IN_Q65	I work just hard enough to get by without overdoing it	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	773	0.2802607	1	3	4	2.571429	0.8976159	4	<U+2582><U+2581><U+2587><U+2581><U+2581><U+2587><U+2581><U+2583>
IN_Q74	I like to try difficult things	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	772	0.2811918	1	3	4	3.129139	0.7645892	4	<U+2581><U+2581><U+2582><U+2581><U+2581><U+2587><U+2581><U+2585>
IN_Q82	I like hard work	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	772	0.2811918	1	3	4	2.698675	0.9178544	4	<U+2582><U+2581><U+2586><U+2581><U+2581><U+2587><U+2581><U+2585>
IN_Q115	Some people say that I put my work ahead of too many other things	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	773	0.2802607	1	2	4	1.837209	0.8737339	4	<U+2587><U+2581><U+2587><U+2581><U+2581><U+2582><U+2581><U+2581>
IN_Q125	I am not a terribly ambitious person	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	773	0.2802607	1	3	4	2.850498	0.8451280	4	<U+2581><U+2581><U+2586><U+2581><U+2581><U+2587><U+2581><U+2585>
IN_Q137	I push myself to my limits	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	773	0.2802607	1	3	4	2.867110	0.8994153	4	<U+2582><U+2581><U+2586><U+2581><U+2581><U+2587><U+2581><U+2586>
IN_Q145	I find it really hard to give up on a project when It proves too difficult	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	773	0.2802607	1	3	4	2.627907	0.8452329	4	<U+2582><U+2581><U+2586><U+2581><U+2581><U+2587><U+2581><U+2583>
IN_Q197	I set extremely high standards for myself in my work	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	774	0.2793296	1	3	4	2.796667	0.8970346	4	<U+2582><U+2581><U+2586><U+2581><U+2581><U+2587><U+2581><U+2585>

Scale: AG_1

Overview

Reliability: .

Missing: 782.

Likert plot of scale AG_1 items

Distribution of scale AG_1

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	IN_Q13, IN_Q38, IN_Q47, IN_Q55, IN_Q67, IN_Q75, IN_Q98, IN_Q109, IN_Q128, IN_Q152, IN_Q173 & IN_Q196
Observations:	292
Positive correlations:	66
Number of correlations:	66
Percentage positive correlations:	100

Estimates assuming interval level

Omega (total):	0.92
Omega (hierarchical):	0.76
Revelle’s Omega (total):	0.92
Greatest Lower Bound (GLB):	0.94
Coefficient H:	0.91
Coefficient Alpha:	0.90

(Estimates assuming ordinal level not computed, as the polychoric correlation matrix has missing values.)

Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help (‘?ufs::scaleStructure’) for more information.

Eigen values

5.886, 1.133, 0.892, 0.726, 0.638, 0.584, 0.49, 0.406, 0.382, 0.339, 0.268 & 0.256

Factor analysis (reproducing only shared variance)

	ML1	ML2
IN_Q13	0.078	0.768
IN_Q38	0.456	0.098
IN_Q47	0.674	0.076
IN_Q55	0.793	-0.077
IN_Q67	0.059	0.471
IN_Q75	-0.039	0.738
IN_Q98	0.310	0.422
IN_Q109	0.666	0.036
IN_Q128	0.625	0.143
IN_Q152	0.731	-0.067
IN_Q173	-0.030	0.876
IN_Q196	0.761	0.011

Component analysis (reproducing full covariance matrix)

	TC1	TC2
IN_Q13	0.152	0.740
IN_Q38	0.503	0.129
IN_Q47	0.732	0.056
IN_Q55	0.813	-0.043
IN_Q67	-0.135	0.780
IN_Q75	-0.064	0.842
IN_Q98	0.309	0.495
IN_Q109	0.691	0.082
IN_Q128	0.691	0.116
IN_Q152	0.804	-0.084
IN_Q173	0.100	0.784
IN_Q196	0.812	-0.009

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
IN_Q13	2.36301369863014	2	0.823094666478369	0.907245648365628	1	0.0530925357367052	1	1	3	4	0.246431276877808	-0.699415602197886	0.138698630136986	292	292
IN_Q38	2.10958904109589	2	0.723344160429318	0.850496419997943	1.5	0.0497715383413807	1	1	3	4	0.396026195110444	-0.457125741871271	0.125	292	292
IN_Q47	2.16095890410959	2	1.01524031445653	1.00759134298411	2	0.0589648233438752	1	1	3	4	0.423231626440615	-0.919925495937545	0.155821917808219	292	292
IN_Q55	1.58219178082192	1	0.718307207079979	0.847530062640836	1	0.0495979454073459	1	NA	2	4	1.29187346140256	0.66769335391819	0.111301369863014	292	292
IN_Q67	2.8527397260274	3	0.861401402815045	0.928117127745763	2	0.0543139466818709	1	2	4	4	-0.455852572641751	-0.619076796367699	0.133561643835616	292	292
IN_Q75	2.52739726027397	3	0.793061243703808	0.890539860816914	1	0.052114903466947	1	2	4	4	-0.0390682436698156	-0.727153901617517	0.176369863013699	292	292
IN_Q98	1.92123287671233	2	0.732606034929153	0.855924082456589	1	0.0500891682617573	1	1	3	4	0.582261981409109	-0.440919009544584	0.181506849315068	292	292
IN_Q109	1.99657534246575	2	1.05497104928682	1.02711783612535	2	0.0601075249228592	1	1	3	4	0.658298702536028	-0.768693854876082	0.148972602739726	292	292
IN_Q128	1.91438356164384	2	1.01326319258109	1.00660975188058	2	0.0589073800694578	1	1	3	4	0.681595546222302	-0.800622839646067	0.11986301369863	292	292
IN_Q152	2.02054794520548	2	1.00988560937721	1.00493064903863	2	0.0588091180080168	1	1	3	4	0.592840225494381	-0.792074401194828	0.155821917808219	292	292
IN_Q173	2.32876712328767	2	0.798757237678294	0.893732195726602	1	0.0523017207369791	1	1	3	4	0.147198856922961	-0.733373272672983	0.159246575342466	292	292
IN_Q196	1.76712328767123	1	0.852798568940357	0.923470935622966	1	0.054042048853798	1	NA	2	4	0.927329330502969	-0.219046801787544	0.13527397260274	292	292

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
IN_Q13	When someone hurts me, I try to retaliate (get even)	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	771	0.2821229	1	2	4	2.369637	0.9072932	4	<U+2583><U+2581><U+2587><U+2581><U+2581><U+2586><U+2581><U+2582>
IN_Q38	I see no objection to stepping on people’s toes a little if it is to my advantage	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	770	0.2830540	1	2	4	2.101974	0.8400825	4	<U+2585><U+2581><U+2587><U+2581><U+2581><U+2583><U+2581><U+2581>
IN_Q47	When I get angry I am often ready to hit someone	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	771	0.2821229	1	2	4	2.148515	1.0071217	4	<U+2587><U+2581><U+2587><U+2581><U+2581><U+2586><U+2581><U+2583>
IN_Q55	I admit that I sometimes take pleasure in hurting someone physically	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	770	0.2830540	1	1	4	1.572368	0.8411996	4	<U+2587><U+2581><U+2583><U+2581><U+2581><U+2582><U+2581><U+2581>
IN_Q67	I can’t help but enjoy it when someone I dislike makes a fool of herself/himself	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	770	0.2830540	1	3	4	2.848684	0.9210402	4	<U+2582><U+2581><U+2585><U+2581><U+2581><U+2587><U+2581><U+2585>
IN_Q75	I would rather tum the other cheek than get even when someone treats me badly	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	770	0.2830540	1	3	4	2.516447	0.8898358	4	<U+2583><U+2581><U+2587><U+2581><U+2581><U+2587><U+2581><U+2583>
IN_Q98	Sometimes I seem to enjoy hurting someone by saying something mean	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	770	0.2830540	1	2	4	1.914474	0.8516656	4	<U+2587><U+2581><U+2587><U+2581><U+2581><U+2583><U+2581><U+2581>
IN_Q109	I enjoy a good brawl	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	774	0.2793296	1	2	4	2.000000	1.0247767	4	<U+2587><U+2581><U+2586><U+2581><U+2581><U+2583><U+2581><U+2582>
IN_Q128	Sometimes I hit people who have done something to deserve it	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	772	0.2811918	1	2	4	1.900662	1.0000330	4	<U+2587><U+2581><U+2585><U+2581><U+2581><U+2583><U+2581><U+2582>
IN_Q152	I like to watch a good, vicious fight	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	771	0.2821229	1	2	4	2.019802	1.0096901	4	<U+2587><U+2581><U+2586><U+2581><U+2581><U+2583><U+2581><U+2582>
IN_Q173	When people insult me, I try to get even	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	771	0.2821229	1	2	4	2.316832	0.9054364	4	<U+2585><U+2581><U+2587><U+2581><U+2581><U+2586><U+2581><U+2582>
IN_Q196	Sometimes I just like to hit someone	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	772	0.2811918	1	1	4	1.754967	0.9147509	4	<U+2587><U+2581><U+2585><U+2581><U+2581><U+2582><U+2581><U+2581>

Scale: CON_1

Overview

Reliability: .

Missing: 781.

Likert plot of scale CON_1 items

Distribution of scale CON_1

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	IN_Q15, IN_Q31, IN_Q37, IN_Q129, IN_Q53, IN_Q60, IN_Q69, IN_Q92, IN_Q102, IN_Q149, IN_Q159 & IN_Q180
Observations:	293
Positive correlations:	55
Number of correlations:	66
Percentage positive correlations:	83

Estimates assuming interval level

Omega (total):	0.87
Omega (hierarchical):	0.63
Revelle’s Omega (total):	0.87
Greatest Lower Bound (GLB):	0.87
Coefficient H:	0.87
Coefficient Alpha:	0.80

(Estimates assuming ordinal level not computed, as the polychoric correlation matrix has missing values.)

Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help (‘?ufs::scaleStructure’) for more information.

Eigen values

4.47, 1.312, 1.014, 0.866, 0.771, 0.737, 0.633, 0.557, 0.499, 0.427, 0.379 & 0.334

Factor analysis (reproducing only shared variance)

	ML1	ML3	ML2
IN_Q15	0.835	-0.130	0.067
IN_Q31	0.616	0.204	-0.011
IN_Q37	-0.048	0.411	0.464
IN_Q129	0.084	-0.138	-0.307
IN_Q53	0.176	0.328	0.108
IN_Q60	0.255	0.561	-0.063
IN_Q69	0.003	0.630	-0.027
IN_Q92	0.005	0.598	0.209
IN_Q102	0.686	0.198	-0.002
IN_Q149	0.260	0.442	-0.001
IN_Q159	0.075	-0.044	0.750
IN_Q180	0.154	0.098	0.275

Component analysis (reproducing full covariance matrix)

	TC1	TC3	TC2
IN_Q15	0.882	-0.138	0.048
IN_Q31	0.759	0.143	-0.031
IN_Q37	-0.019	0.482	0.470
IN_Q129	0.210	-0.083	-0.684
IN_Q53	0.261	0.307	0.202
IN_Q60	0.382	0.521	-0.017
IN_Q69	-0.019	0.821	-0.076
IN_Q92	0.044	0.677	0.213
IN_Q102	0.749	0.169	0.024
IN_Q149	0.385	0.478	-0.046
IN_Q159	0.093	0.014	0.732
IN_Q180	0.307	-0.174	0.589

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
IN_Q15	2.96245733788396	3	0.625298050399738	0.790757896198159	2	0.0461965695577816	1	2	4	4	-0.351612862515762	-0.403571481541379	0.129692832764505	293	293
IN_Q31	2.78498293515358	3	0.532376455187246	0.729641319544916	1	0.0426261010261749	1	2	4	4	-0.122605012701933	-0.300661081660706	0.151877133105802	293	293
IN_Q37	2.48464163822526	2	0.956098929356211	0.977803113799609	1	0.057123867845816	1	1	3	4	0.0543645386157495	-0.989648872406555	0.151877133105802	293	293
IN_Q129	2.5358361774744	3	0.818060685399037	0.904467072589731	1	0.0528395305725079	1	2	4	4	-0.093529565012427	-0.76220769514496	0.16382252559727	293	293
IN_Q53	2.87030716723549	3	0.599560521763523	0.774312935293944	1	0.0452358446836588	1	2	4	4	-0.30634105484734	-0.260974098810843	0.12457337883959	293	293
IN_Q60	2.52559726962457	3	0.770746645471972	0.877921776396947	1	0.0512887378104024	1	2	4	4	-0.0785413126896104	-0.683076497421547	0.172354948805461	293	293
IN_Q69	2.33105802047782	2	0.824956753471411	0.908271299486784	1	0.0530617758808484	1	1	3	4	0.235279910278067	-0.712539648216102	0.141638225255973	293	293
IN_Q92	2.21160409556314	2	0.701645705736594	0.837642946449496	1	0.0489356234395948	1	1	3	4	0.288439647054892	-0.469415951318464	0.136518771331058	293	293
IN_Q102	2.74061433447099	3	0.617420169245874	0.785760885540808	1	0.0459046410781254	1	2	4	4	-0.146382346929249	-0.421905282550363	0.158703071672355	293	293
IN_Q149	2.77474402730375	3	0.620318855486465	0.787603234812088	1	0.046012272271781	1	2	4	4	-0.382865862434558	-0.131019418640639	0.126279863481229	293	293
IN_Q159	2.69965870307167	3	0.724554677638038	0.851207775832692	1	0.0497280892336805	1	2	4	4	-0.287555458620618	-0.478609362815518	0.139931740614334	293	293
IN_Q180	3.07167235494881	3	0.450324933376969	0.671062540585428	0	0.0392038922188743	1	2	4	4	-0.495002670148333	0.647131633887645	0.121160409556314	293	293

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
IN_Q15	When faced with a decision I usually take time to consider and weigh all aspects	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	770	0.2830540	1	3	4	2.973684	0.7872530	4	<U+2581><U+2581><U+2583><U+2581><U+2581><U+2587><U+2581><U+2585>
IN_Q31	I like to stop and think things over before I do them	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	770	0.2830540	1	3	4	2.779605	0.7362234	4	<U+2581><U+2581><U+2585><U+2581><U+2581><U+2587><U+2581><U+2582>
IN_Q37	I often prefer to “play things by ear” rather than to plan ahead	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	771	0.2821229	1	2	4	2.488449	0.9895306	4	<U+2585><U+2581><U+2587><U+2581><U+2581><U+2587><U+2581><U+2585>
IN_Q129	I often start projects with only a vague idea of what the end result will be	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	772	0.2811918	1	3	4	2.536424	0.9097101	4	<U+2583><U+2581><U+2587><U+2581><U+2581><U+2587><U+2581><U+2583>
IN_Q53	I am very level-headed and always like to keep my feet on the ground	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	772	0.2811918	1	3	4	2.860927	0.7821916	4	<U+2581><U+2581><U+2585><U+2581><U+2581><U+2587><U+2581><U+2583>
IN_Q60	I am more likely to be fast and careless than to be slow and plodding	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	773	0.2802607	1	3	4	2.518272	0.8815696	4	<U+2583><U+2581><U+2587><U+2581><U+2581><U+2587><U+2581><U+2582>
IN_Q69	I almost never do anything reckless	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	770	0.2830540	1	2	4	2.312500	0.9143385	4	<U+2583><U+2581><U+2587><U+2581><U+2581><U+2585><U+2581><U+2582>
IN_Q92	I often act on the spur of the moment	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	771	0.2821229	1	2	4	2.211221	0.8466565	4	<U+2583><U+2581><U+2587><U+2581><U+2581><U+2585><U+2581><U+2581>
IN_Q102	I usually make up my mind through careful reasoning	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	771	0.2821229	1	3	4	2.745875	0.7878051	4	<U+2581><U+2581><U+2586><U+2581><U+2581><U+2587><U+2581><U+2583>
IN_Q149	I am a cautious person	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	771	0.2821229	1	3	4	2.775578	0.7905470	4	<U+2581><U+2581><U+2583><U+2581><U+2581><U+2587><U+2581><U+2582>
IN_Q159	I generally do not like to have detailed plans	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	771	0.2821229	1	3	4	2.693069	0.8621079	4	<U+2582><U+2581><U+2585><U+2581><U+2581><U+2587><U+2581><U+2583>
IN_Q180	Before I get into a new situation I like to find out what to expect from it	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	771	0.2821229	1	3	4	3.092409	0.6745431	4	<U+2581><U+2581><U+2582><U+2581><U+2581><U+2587><U+2581><U+2583>

Scale: HA_1

Overview

Reliability: .

Missing: 779.

Likert plot of scale HA_1 items

Distribution of scale HA_1

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	IN_Q71, IN_Q21, IN_Q45, IN_Q62, IN_Q84, IN_Q90, IN_Q100, IN_Q108, IN_Q117, IN_Q147, IN_Q171 & IN_Q194
Observations:	295
Positive correlations:	66
Number of correlations:	66
Percentage positive correlations:	100

Estimates assuming interval level

Omega (total):	0.83
Omega (hierarchical):	0.56
Revelle’s Omega (total):	0.83
Greatest Lower Bound (GLB):	0.85
Coefficient H:	0.82
Coefficient Alpha:	0.80

(Estimates assuming ordinal level not computed, as the polychoric correlation matrix has missing values.)

Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help (‘?ufs::scaleStructure’) for more information.

Eigen values

3.848, 1.291, 0.968, 0.923, 0.848, 0.683, 0.659, 0.649, 0.611, 0.584, 0.489 & 0.447

Factor analysis (reproducing only shared variance)

	ML1	ML2
IN_Q71	0.524	-0.062
IN_Q21	0.499	0.271
IN_Q45	0.400	0.384
IN_Q62	0.418	0.060
IN_Q84	0.626	0.018
IN_Q90	0.124	0.492
IN_Q100	0.379	0.140
IN_Q108	-0.050	0.741
IN_Q117	0.657	-0.131
IN_Q147	0.482	0.064
IN_Q171	0.532	-0.092
IN_Q194	0.452	0.041

Component analysis (reproducing full covariance matrix)

	TC1	TC2
IN_Q71	0.666	-0.138
IN_Q21	0.474	0.403
IN_Q45	0.369	0.509
IN_Q62	0.437	0.166
IN_Q84	0.639	0.120
IN_Q90	-0.001	0.754
IN_Q100	0.347	0.306
IN_Q108	-0.093	0.817
IN_Q117	0.728	-0.110
IN_Q147	0.530	0.134
IN_Q171	0.648	-0.131
IN_Q194	0.505	0.093

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
IN_Q71	2.87118644067797	3	1.33028940389715	1.15338172514443	2	0.0671524802701361	1	1	4	4	-0.482619571108023	-1.25444157876926	0.108474576271186	295	295
IN_Q21	2.65084745762712	3	1.18039893923671	1.08646166027003	2	0.063256243457825	1	2	4	4	-0.0719296272130059	-1.31881512209223	0.152542372881356	295	295
IN_Q45	2.66779661016949	3	1.24980975441024	1.11794890509819	2	0.0650895017286885	1	2	4	4	-0.139672777417344	-1.36541631915209	0.13728813559322	295	295
IN_Q62	2.68474576271186	3	1.48190937391906	1.21733700096525	3	0.0708761003900842	1	1	4	4	-0.253819783671523	-1.5169731803357	0.130508474576271	295	295
IN_Q84	2.87457627118644	3	1.36856912256428	1.16985859084091	2	0.0681118004799805	1	1	4	4	-0.524096862863036	-1.24037425966233	0.115254237288136	295	295
IN_Q90	2.69830508474576	3	1.08894269572236	1.04352417112511	2	0.0607563261886381	1	2	4	4	-0.274659631892522	-1.09944551011712	0.133898305084746	295	295
IN_Q100	2.17627118644068	2	1.39059149083362	1.17923343356336	2	0.0686576249258082	1	1	4	4	0.418065558924044	-1.3570914156437	0.103389830508475	295	295
IN_Q108	2.55593220338983	2	1.13886775049003	1.06717746906971	2	0.06213347443793	1	1	4	4	0.0814052786325392	-1.26252211746301	0.133898305084746	295	295
IN_Q117	2.57966101694915	3	1.53699988469964	1.23975799440844	3	0.0721815010974194	1	1	4	4	-0.108308778471033	-1.60482414010282	0.149152542372881	295	295
IN_Q147	2.83728813559322	3	1.47683615819209	1.21525147940337	2	0.0707546766302973	1	1	4	4	-0.474716112810603	-1.37727724812689	0.116949152542373	295	295
IN_Q171	2.68135593220339	3	1.44914101233714	1.20380272982625	3	0.0700881046590801	1	1	4	4	-0.249672801731544	-1.49133421462079	0.127118644067797	295	295
IN_Q194	2.74576271186441	3	1.40793266459126	1.186563384144	2	0.0690843911481411	1	1	4	4	-0.308390633044495	-1.43677501884614	0.111864406779661	295	295

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
IN_Q71	Of the following two situations I would dislike more: (A) Having a pilot announce that the plane has engine trouble and he may have to make an emergency landing, (B) Working in the fields digging potatoes.	haven_labelled	4. Definitely A, 3. Probably A, 2. Probably B, 1. Definitely B	772	0.2811918	1	3	4	2.867550	1.156668	4	<U+2583><U+2581><U+2583><U+2581><U+2581><U+2585><U+2581><U+2587>
IN_Q21	It might be fun and exciting to experience an earthquake	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	770	0.2830540	1	3	4	2.644737	1.092476	4	<U+2585><U+2581><U+2587><U+2581><U+2581><U+2585><U+2581><U+2587>
IN_Q45	I might enjoy riding in an open elevator to the top of a tall building under construction	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	770	0.2830540	1	3	4	2.671053	1.121505	4	<U+2585><U+2581><U+2587><U+2581><U+2581><U+2585><U+2581><U+2587>
IN_Q62	Of the following two situations I would dislike more: (A) Having to walk around all day on a blistered foot, (B) Sleeping out on a camping trip in an area where there are rattlesnakes.	haven_labelled	1. Definitely A, 2. Probably A, 3. Probably B, 4. Definitely B	772	0.2811918	1	3	4	2.701987	1.216141	4	<U+2586><U+2581><U+2583><U+2581><U+2581><U+2585><U+2581><U+2587>
IN_Q84	Of the following two situations I would dislike more: (A) Being out on a sailboat during a great storm at sea. (B) Having to stay home every night for two weeks with a sick relative.	haven_labelled	4. Definitely A, 3. Probably A, 2. Probably B, 1. Definitely B	771	0.2821229	1	3	4	2.871287	1.167978	4	<U+2583><U+2581><U+2583><U+2581><U+2581><U+2585><U+2581><U+2587>
IN_Q90	I would enjoy trying to cross the ocean in a small but seaworthy sailboat	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	770	0.2830540	1	3	4	2.707237	1.045095	4	<U+2585><U+2581><U+2586><U+2581><U+2581><U+2587><U+2581><U+2586>
IN_Q100	Of the following two situations I would dislike more: (A) Riding a long stretch of rapids in a canoe. (B) Waiting for someone who’s late.	haven_labelled	4. Definitely A, 3. Probably A, 2. Probably B, 1. Definitely B	771	0.2821229	1	2	4	2.174917	1.181717	4	<U+2587><U+2581><U+2583><U+2581><U+2581><U+2583><U+2581><U+2583>
IN_Q108	It might be fun learning to walk a tightrope	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	770	0.2830540	1	2	4	2.559210	1.066957	4	<U+2583><U+2581><U+2587><U+2581><U+2581><U+2585><U+2581><U+2586>
IN_Q117	Of the following two situations I would dislike more: (A) Being at the circus when two lions suddenly get loose down in the ring, (B) Bringing my whole family to the circus and then not being able to get in because a clerk sold me tickets for the wrong night.	haven_labelled	4. Definitely A, 3. Probably A, 2. Probably B, 1. Definitely B	771	0.2821229	1	3	4	2.577558	1.239429	4	<U+2587><U+2581><U+2585><U+2581><U+2581><U+2585><U+2581><U+2587>
IN_Q147	Of the following two situations I would dislike more: (A) Being chosen as the “target” for a knife-throwing act, (B) Being sick to my stomach for 24 hours.	haven_labelled	4. Definitely A, 3. Probably A, 2. Probably B, 1. Definitely B	772	0.2811918	1	3	4	2.824503	1.214118	4	<U+2585><U+2581><U+2582><U+2581><U+2581><U+2583><U+2581><U+2587>
IN_Q171	Of the following two situations I would dislike more: (A) Being in a flood, (B) carrying a ton of coal from the backyard into the basement.	haven_labelled	4. Definitely A, 3. Probably A, 2. Probably B, 1. Definitely B	773	0.2802607	1	3	4	2.677741	1.205184	4	<U+2586><U+2581><U+2583><U+2581><U+2581><U+2585><U+2581><U+2587>
IN_Q194	Of the following two situations I would dislike more: (A) Being seasick every day for a week while on an ocean voyage. (B) Having to stand on the ledge of the 25th floor of a hotel because there’s a fire in my room.	haven_labelled	1. Definitely A, 2. Probably A, 3. Probably B, 4. Definitely B	772	0.2811918	1	3	4	2.748344	1.179665	4	<U+2585><U+2581><U+2585><U+2581><U+2581><U+2585><U+2581><U+2587>

Scale: SP_1

Overview

Reliability: .

Missing: 784.

Likert plot of scale SP_1 items

Distribution of scale SP_1

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	IN_Q1, IN_Q14, IN_Q30, IN_Q54, IN_Q61, IN_Q77, IN_Q91, IN_Q119, IN_Q142, IN_Q153, IN_Q170 & IN_Q184
Observations:	290
Positive correlations:	66
Number of correlations:	66
Percentage positive correlations:	100

Estimates assuming interval level

Omega (total):	0.88
Omega (hierarchical):	0.65
Revelle’s Omega (total):	0.88
Greatest Lower Bound (GLB):	0.91
Coefficient H:	0.88
Coefficient Alpha:	0.84

(Estimates assuming ordinal level not computed, as the polychoric correlation matrix has missing values.)

Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help (‘?ufs::scaleStructure’) for more information.

Eigen values

4.543, 1.507, 1.052, 0.911, 0.791, 0.743, 0.565, 0.535, 0.464, 0.335, 0.32 & 0.236

Factor analysis (reproducing only shared variance)

	ML1	ML2	ML3
IN_Q1	0.061	0.440	0.162
IN_Q14	0.014	0.892	-0.057
IN_Q30	0.009	-0.017	0.808
IN_Q54	0.903	-0.049	-0.003
IN_Q61	0.766	-0.005	0.029
IN_Q77	0.169	0.291	-0.112
IN_Q91	-0.018	0.686	0.140
IN_Q119	0.008	0.230	0.320
IN_Q142	0.055	0.114	0.511
IN_Q153	0.837	0.045	-0.024
IN_Q170	0.521	0.091	0.059
IN_Q184	0.191	0.079	0.206

Component analysis (reproducing full covariance matrix)

	TC1	TC2	TC3
IN_Q1	0.578	0.000	0.380
IN_Q14	0.658	0.054	0.306
IN_Q30	0.755	0.040	-0.213
IN_Q54	-0.051	0.902	0.045
IN_Q61	-0.023	0.839	0.092
IN_Q77	0.014	0.074	0.860
IN_Q91	0.725	0.010	0.177
IN_Q119	0.641	-0.013	-0.080
IN_Q142	0.682	0.069	-0.215
IN_Q153	0.016	0.875	-0.011
IN_Q170	0.148	0.682	-0.201
IN_Q184	0.305	0.240	0.007

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
IN_Q1	2.93103448275862	3	0.67342799188641	0.820626584925452	2	0.0481888523339525	1	2	4	4	-0.40122781220612	-0.375915059317915	0.127586206896552	290	290
IN_Q14	2.63793103448276	3	0.882293282424532	0.939304680295234	1	0.0551578700554156	1	2	4	4	-0.2029436450781	-0.827843129219497	0.141379310344828	290	290
IN_Q30	2.3551724137931	2	0.748848586087579	0.865360379314641	1	0.050815711190047	1	1	3	4	0.179638643977468	-0.605217210943345	0.156896551724138	290	290
IN_Q54	2.91379310344828	3	0.681123970886529	0.825302351194112	1	0.0484634227834207	1	2	4	4	-0.396105152500097	-0.380100768454035	0.124137931034483	290	290
IN_Q61	2.89310344827586	3	0.607910750507099	0.779686315454555	1	0.0457847569313834	1	2	4	4	-0.340389368929565	-0.248432385793324	0.118965517241379	290	290
IN_Q77	2.02758620689655	2	0.642834983892137	0.801769907075675	2	0.0470815500833261	1	1	3	4	0.396275620591753	-0.375336919280074	0.13448275862069	290	290
IN_Q91	2.68275862068965	3	0.937071948454838	0.968024766447036	1	0.0568443715848698	1	2	4	4	-0.22662453444971	-0.912526785666577	0.136206896551724	290	290
IN_Q119	2.39310344827586	2	0.765350196873881	0.874842955549098	1	0.0513725472398433	1	1	3	4	-0.0128201869061963	-0.728295836648972	0.181034482758621	290	290
IN_Q142	2.42068965517241	2	0.722061806467009	0.84974220000363	1	0.0498985801217039	1	1	3	4	-0.0735663044819365	-0.65216960618793	0.181034482758621	290	290
IN_Q153	2.85172413793103	3	0.652678677962057	0.807885312381688	1	0.0474406590479479	1	2	4	4	-0.397456663792226	-0.225797038832067	0.117241379310345	290	290
IN_Q170	2.78965517241379	3	0.692626178260351	0.832241658570605	1	0.0488709129435111	1	2	4	4	-0.277970994088685	-0.46425840896052	0.137931034482759	290	290
IN_Q184	2.73448275862069	3	0.576315475480253	0.759154447711566	1	0.0445790841430749	1	2	4	4	-0.277948461501915	-0.159135816577109	0.144827586206897	290	290

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
IN_Q1	When I work with others I like to take charge	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	774	0.2793296	1	3	4	2.933333	0.8232952	4	<U+2581><U+2581><U+2583><U+2581><U+2581><U+2587><U+2581><U+2585>
IN_Q14	I enjoy being in the spotlight	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	774	0.2793296	1	3	4	2.653333	0.9395556	4	<U+2582><U+2581><U+2586><U+2581><U+2581><U+2587><U+2581><U+2585>
IN_Q30	On most social occasions I like to have someone else take the lead	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	772	0.2811918	1	2	4	2.354305	0.8724072	4	<U+2583><U+2581><U+2587><U+2581><U+2581><U+2586><U+2581><U+2582>
IN_Q54	I am quite effective at talking people into things	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	772	0.2811918	1	3	4	2.920530	0.8354534	4	<U+2581><U+2581><U+2583><U+2581><U+2581><U+2587><U+2581><U+2585>
IN_Q61	I am very good at influencing people	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	773	0.2802607	1	3	4	2.900332	0.7853024	4	<U+2581><U+2581><U+2583><U+2581><U+2581><U+2587><U+2581><U+2583>
IN_Q77	People consider me forceful	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	773	0.2802607	1	2	4	2.023256	0.8017423	4	<U+2585><U+2581><U+2587><U+2581><U+2581><U+2583><U+2581><U+2581>
IN_Q91	I do not like to be the center of attention on social occasions	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	772	0.2811918	1	3	4	2.692053	0.9651071	4	<U+2583><U+2581><U+2586><U+2581><U+2581><U+2587><U+2581><U+2585>
IN_Q119	I do not like to organize other people’s activities	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	773	0.2802607	1	2	4	2.388704	0.8897970	4	<U+2583><U+2581><U+2587><U+2581><U+2581><U+2587><U+2581><U+2582>
IN_Q142	On social occasions I usually allow others to dominate the conversation	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	773	0.2802607	1	2	4	2.428571	0.8440266	4	<U+2583><U+2581><U+2587><U+2581><U+2581><U+2587><U+2581><U+2582>
IN_Q153	I am quite good at convincing others to see things my way	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	773	0.2802607	1	3	4	2.853821	0.8156145	4	<U+2581><U+2581><U+2583><U+2581><U+2581><U+2587><U+2581><U+2583>
IN_Q170	I don’t enjoy trying to convince people of something	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	773	0.2802607	1	3	4	2.790698	0.8362893	4	<U+2581><U+2581><U+2585><U+2581><U+2581><U+2587><U+2581><U+2583>
IN_Q184	When it is time to make decisions, others usually tum to me	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	774	0.2793296	1	3	4	2.730000	0.7565323	4	<U+2581><U+2581><U+2585><U+2581><U+2581><U+2587><U+2581><U+2582>

Scale: TR_1

Overview

Reliability: .

Missing: 803.

Likert plot of scale TR_1 items

Distribution of scale TR_1

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	IN_Q7, IN_Q36, IN_Q52, IN_Q58, IN_Q105, IN_Q113, IN_Q126, IN_Q150, IN_Q168, IN_Q174, IN_Q181 & IN_Q190
Observations:	271
Positive correlations:	66
Number of correlations:	66
Percentage positive correlations:	100

Estimates assuming interval level

Omega (total):	0.83
Omega (hierarchical):	0.55
Revelle’s Omega (total):	0.83
Greatest Lower Bound (GLB):	0.86
Coefficient H:	0.82
Coefficient Alpha:	0.79

(Estimates assuming ordinal level not computed, as the polychoric correlation matrix has missing values.)

Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help (‘?ufs::scaleStructure’) for more information.

Eigen values

3.802, 1.319, 1.057, 0.869, 0.828, 0.796, 0.679, 0.641, 0.56, 0.547, 0.485 & 0.418

Factor analysis (reproducing only shared variance)

	ML2	ML1	ML3
IN_Q7	0.141	0.172	0.528
IN_Q36	-0.012	0.522	0.178
IN_Q52	0.618	-0.006	0.201
IN_Q58	0.536	0.027	-0.124
IN_Q105	0.003	0.796	-0.002
IN_Q113	0.237	0.450	-0.192
IN_Q126	0.142	0.067	0.247
IN_Q150	0.232	0.025	0.165
IN_Q168	0.638	-0.044	0.056
IN_Q174	0.232	0.269	0.125
IN_Q181	0.509	0.176	-0.209
IN_Q190	0.012	0.432	0.372

Component analysis (reproducing full covariance matrix)

	TC1	TC2	TC3
IN_Q7	0.698	-0.123	0.173
IN_Q36	0.725	-0.003	-0.060
IN_Q52	0.297	0.499	0.096
IN_Q58	-0.079	0.725	0.014
IN_Q105	0.658	0.242	-0.039
IN_Q113	0.289	0.535	-0.222
IN_Q126	0.180	-0.056	0.670
IN_Q150	-0.006	0.144	0.688
IN_Q168	-0.028	0.616	0.376
IN_Q174	0.522	0.251	-0.174
IN_Q181	0.000	0.739	-0.021
IN_Q190	0.754	-0.086	0.125

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
IN_Q7	2.93726937269373	3	0.659013256799235	0.81179631484704	0	0.0493131142336552	1	2	4	4	-0.679645567014306	0.265393917548686	0.114391143911439	271	271
IN_Q36	2.74907749077491	3	0.618286182861829	0.786311759330756	1	0.0477650377341884	1	2	4	4	-0.353453852839082	-0.16440589931234	0.132841328413284	271	271
IN_Q52	2.66420664206642	3	0.846084460844608	0.919828495342805	1	0.0558756018432501	1	2	4	4	-0.146757806541542	-0.81239431925078	0.156826568265683	271	271
IN_Q58	2.39852398523985	2	0.973923739237392	0.98687574660511	1	0.0599484323058688	1	1	3	4	0.063900774020736	-1.02805239961625	0.156826568265683	271	271
IN_Q105	2.8929889298893	3	0.607024736914036	0.779117922341693	1	0.047328043258195	1	2	4	4	-0.331761916409432	-0.261828841706859	0.119926199261993	271	271
IN_Q113	1.91143911439114	2	0.858794587945879	0.926711707029689	1	0.0562937271759251	1	1	3	4	0.796048973562089	-0.223854506423437	0.190036900369004	271	271
IN_Q126	3.26937269372694	3	0.72346590132568	0.850567987479943	1	0.0516683256168659	1	2	4	4	-0.946829961932551	0.0687010034868233	0.164206642066421	271	271
IN_Q150	2.93357933579336	3	1.05483121497882	1.02704976265944	2	0.0623888299852858	1	2	4	4	-0.610195086425669	-0.775815714212627	0.171586715867159	271	271
IN_Q168	2.54981549815498	3	0.789175891758918	0.888355723659682	1	0.0539637671171317	1	2	4	4	-0.167661449197129	-0.692383145937543	0.154981549815498	271	271
IN_Q174	2.56826568265683	3	0.883285499521662	0.939832697623179	1	0.057090770592065	1	2	4	4	0.0166184467467386	-0.901558391201856	0.160516605166052	271	271
IN_Q181	2.62730627306273	3	0.74577012436791	0.863579830917739	1	0.0524587388154764	1	2	4	4	-0.103337022599607	-0.641186194488148	0.169741697416974	271	271
IN_Q190	3.09963099630996	3	0.578925789257893	0.760871729832232	1	0.0462196659976776	1	2	4	4	-0.525080957039139	-0.114319124305052	0.158671586715867	271	271

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
IN_Q7	The best way to achieve a peaceful world is to improve people’s morals	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	775	0.2783985	1	3.0	4	2.949833	0.8031972	4	<U+2581><U+2581><U+2582><U+2581><U+2581><U+2587><U+2581><U+2583>
IN_Q36	Higher standards of conduct are what this country needs most	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	775	0.2783985	1	3.0	4	2.745819	0.7786632	4	<U+2581><U+2581><U+2583><U+2581><U+2581><U+2587><U+2581><U+2582>
IN_Q52	I would prefer to see: (A) Stricter observance of the Sabbath, (B) Greater freedom in regard to divorce.	haven_labelled	4. Definitely A, 3. Probably A, 2. Probably B, 1. Definitely B	784	0.2700186	1	3.0	4	2.658621	0.9059653	4	<U+2582><U+2581><U+2587><U+2581><U+2581><U+2587><U+2581><U+2585>
IN_Q58	More censorship of books and movies is a violation of free speech and should be abolished	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	775	0.2783985	1	2.0	4	2.418060	1.0079258	4	<U+2586><U+2581><U+2587><U+2581><U+2581><U+2587><U+2581><U+2585>
IN_Q105	People should observe moral laws more strictly than they do	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	774	0.2793296	1	3.0	4	2.880000	0.7621480	4	<U+2581><U+2581><U+2583><U+2581><U+2581><U+2587><U+2581><U+2583>
IN_Q113	I am disgusted by foul language	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	772	0.2811918	1	2.0	4	1.894040	0.9160969	4	<U+2587><U+2581><U+2587><U+2581><U+2581><U+2582><U+2581><U+2582>
IN_Q126	No decent person could ever think of hurting a close friend or relative	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	774	0.2793296	1	3.5	4	3.283333	0.8438577	4	<U+2581><U+2581><U+2582><U+2581><U+2581><U+2585><U+2581><U+2587>
IN_Q150	It is a pretty callous (unfeeling) person who does not feel love and gratitude toward her/his parents	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	775	0.2783985	1	3.0	4	2.916388	1.0181403	4	<U+2583><U+2581><U+2583><U+2581><U+2581><U+2587><U+2581><U+2587>
IN_Q168	I don’t like to see religious authority overturned by so-called progress and logical reasoning	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	779	0.2746741	1	3.0	4	2.562712	0.8817689	4	<U+2582><U+2581><U+2586><U+2581><U+2581><U+2587><U+2581><U+2582>
IN_Q174	Strict discipline in the home would prevent much of the crime in our society	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	772	0.2811918	1	2.5	4	2.549669	0.9378617	4	<U+2583><U+2581><U+2587><U+2581><U+2581><U+2587><U+2581><U+2583>
IN_Q181	I am not at all sorry to see many of the traditional values change	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	773	0.2802607	1	3.0	4	2.621262	0.8733535	4	<U+2582><U+2581><U+2586><U+2581><U+2581><U+2587><U+2581><U+2583>
IN_Q190	High moral standards are the most important thing parents can teach their children	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	774	0.2793296	1	3.0	4	3.106667	0.7553304	4	<U+2581><U+2581><U+2582><U+2581><U+2581><U+2587><U+2581><U+2585>

Scale: AC_2

Overview

Reliability: .

Missing: 307.

Likert plot of scale AC_2 items

Distribution of scale AC_2

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	FU1_Q8, FU1_Q32, FU1_Q46, FU1_Q56, FU1_Q65, FU1_Q74, FU1_Q82, FU1_Q115, FU1_Q125, FU1_Q137, FU1_Q145 & FU1_Q197
Observations:	767
Positive correlations:	66
Number of correlations:	66
Percentage positive correlations:	100

Estimates assuming interval level

Omega (total):	0.87
Omega (hierarchical):	0.74
Revelle’s Omega (total):	0.87
Greatest Lower Bound (GLB):	0.90
Coefficient H:	0.86
Coefficient Alpha:	0.85

(Estimates assuming ordinal level not computed, as the polychoric correlation matrix has missing values.)

Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help (‘?ufs::scaleStructure’) for more information.

Eigen values

4.615, 1.001, 0.986, 0.877, 0.778, 0.668, 0.626, 0.579, 0.536, 0.478, 0.442 & 0.414

Factor analysis (reproducing only shared variance)

	ML1	ML2
FU1_Q8	-0.031	0.740
FU1_Q32	0.563	-0.076
FU1_Q46	0.559	0.140
FU1_Q56	0.083	0.667
FU1_Q65	0.497	0.051
FU1_Q74	0.424	0.079
FU1_Q82	0.782	-0.114
FU1_Q115	0.365	0.123
FU1_Q125	0.471	0.024
FU1_Q137	0.561	0.157
FU1_Q145	0.204	0.411
FU1_Q197	0.501	0.201

Component analysis (reproducing full covariance matrix)

	TC1	TC2
FU1_Q8	0.676	-0.032
FU1_Q32	-0.010	0.791
FU1_Q46	0.528	0.284
FU1_Q56	0.672	0.048
FU1_Q65	0.459	0.201
FU1_Q74	0.567	-0.021
FU1_Q82	0.390	0.465
FU1_Q115	0.008	0.742
FU1_Q125	0.709	-0.224
FU1_Q137	0.676	0.095
FU1_Q145	0.681	-0.082
FU1_Q197	0.634	0.131

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
FU1_Q8	2.77053455019557	3	0.686180262185927	0.828359983452802	1	0.029910345438628	1	2	4	4	-0.1724810205722	-0.583215550689365	0.153846153846154	767	767
FU1_Q32	2.37027379400261	2	0.755668723894595	0.869292082038364	1	0.0313883178572364	1	1	3	4	0.17548835535331	-0.627053566456529	0.157105606258149	767	767
FU1_Q46	2.60625814863103	3	0.831710131705706	0.911981431667173	1	0.0329297409335006	1	2	4	4	-0.0839228083916085	-0.804703676684748	0.166883963494133	767	767
FU1_Q56	2.64406779661017	3	0.642076381820596	0.8012966877634	1	0.0289331464684367	1	2	4	4	-0.110002805513958	-0.454486554978655	0.173402868318123	767	767
FU1_Q65	2.65449804432855	3	0.753840707241601	0.868240005552382	1	0.0313503295770778	1	2	4	4	-0.1576729941329	-0.64198010726969	0.159713168187744	767	767
FU1_Q74	3.05736636245111	3	0.466678694585054	0.683138854542072	0	0.0246667143875453	1	2	4	4	-0.46666910580425	0.437944442995687	0.121251629726206	767	767
FU1_Q82	2.8135593220339	3	0.689737575784396	0.830504410454512	1	0.0299877762098752	1	2	4	4	-0.380486846885696	-0.335416764395435	0.121903520208605	767	767
FU1_Q115	1.86571056062581	2	0.682987190266918	0.826430390454585	1	0.0298406718736495	1	1	3	4	0.74118657417448	0.0114686622380444	0.185788787483703	767	767
FU1_Q125	2.97131681877445	3	0.602309360330337	0.776085923290931	2	0.028022838523574	1	2	4	4	-0.219196607941265	-0.680639034255313	0.132985658409387	767	767
FU1_Q137	2.85788787483703	3	0.62338091169352	0.789544749645971	1	0.0285088085770763	1	2	4	4	-0.237263862596653	-0.451725185692899	0.135593220338983	767	767
FU1_Q145	2.64146023468057	3	0.598435462842242	0.773586105641927	1	0.0279325753398025	1	2	4	4	-0.080813991992111	-0.389416049959493	0.179269882659713	767	767
FU1_Q197	2.8148631029987	3	0.756802298467121	0.869943847881644	1	0.0314118517578436	1	2	4	4	-0.169294850650754	-0.79995344333948	0.155801825293351	767	767

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
FU1_Q8	I often keep working on a problem even if I am very tired	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	245	0.7718808	1	3	4	2.755127	0.8335440	4	<U+2581><U+2581><U+2586><U+2581><U+2581><U+2587><U+2581><U+2583>
FU1_Q32	I enjoy putting in long hours	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	249	0.7681564	1	2	4	2.370909	0.8663769	4	<U+2583><U+2581><U+2587><U+2581><U+2581><U+2586><U+2581><U+2582>
FU1_Q46	People say that I drive myself hard	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	247	0.7700186	1	3	4	2.605804	0.9069894	4	<U+2582><U+2581><U+2587><U+2581><U+2581><U+2587><U+2581><U+2583>
FU1_Q56	I often go on working on a problem long after others would have given up	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	250	0.7672253	1	3	4	2.638349	0.8086923	4	<U+2582><U+2581><U+2586><U+2581><U+2581><U+2587><U+2581><U+2582>
FU1_Q65	I work just hard enough to get by without overdoing it	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	250	0.7672253	1	3	4	2.650485	0.8660884	4	<U+2582><U+2581><U+2586><U+2581><U+2581><U+2587><U+2581><U+2583>
FU1_Q74	I like to try difficult things	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	248	0.7690875	1	3	4	3.058111	0.6903760	4	<U+2581><U+2581><U+2582><U+2581><U+2581><U+2587><U+2581><U+2583>
FU1_Q82	I like hard work	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	247	0.7700186	1	3	4	2.808948	0.8291115	4	<U+2581><U+2581><U+2585><U+2581><U+2581><U+2587><U+2581><U+2583>
FU1_Q115	Some people say that I put my work ahead of too many other things	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	246	0.7709497	1	2	4	1.861111	0.8309519	4	<U+2587><U+2581><U+2587><U+2581><U+2581><U+2582><U+2581><U+2581>
FU1_Q125	I am not a terribly ambitious person	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	248	0.7690875	1	3	4	2.967312	0.7847929	4	<U+2581><U+2581><U+2585><U+2581><U+2581><U+2587><U+2581><U+2585>
FU1_Q137	I push myself to my limits	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	285	0.7346369	1	3	4	2.854246	0.7951617	4	<U+2581><U+2581><U+2585><U+2581><U+2581><U+2587><U+2581><U+2583>
FU1_Q145	I find it really hard to give up on a project when It proves too difficult	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	287	0.7327747	1	3	4	2.635324	0.7752025	4	<U+2581><U+2581><U+2586><U+2581><U+2581><U+2587><U+2581><U+2582>
FU1_Q197	I set extremely high standards for myself in my work	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	247	0.7700186	1	3	4	2.816203	0.8775260	4	<U+2581><U+2581><U+2586><U+2581><U+2581><U+2587><U+2581><U+2585>

Scale: AG_2

Overview

Reliability: .

Missing: 302.

Likert plot of scale AG_2 items

Distribution of scale AG_2

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	FU1_Q13, FU1_Q38, FU1_Q47, FU1_Q55, FU1_Q67, FU1_Q75, FU1_Q98, FU1_Q109, FU1_Q128, FU1_Q152, FU1_Q173 & FU1_Q196
Observations:	772
Positive correlations:	66
Number of correlations:	66
Percentage positive correlations:	100

Estimates assuming interval level

Omega (total):	0.92
Omega (hierarchical):	0.77
Revelle’s Omega (total):	0.92
Greatest Lower Bound (GLB):	0.92
Coefficient H:	0.91
Coefficient Alpha:	0.90

(Estimates assuming ordinal level not computed, as the polychoric correlation matrix has missing values.)

Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help (‘?ufs::scaleStructure’) for more information.

Eigen values

5.756, 1.196, 0.761, 0.707, 0.683, 0.521, 0.506, 0.488, 0.404, 0.345, 0.33 & 0.302

Factor analysis (reproducing only shared variance)

	ML1	ML2
FU1_Q13	-0.031	0.817
FU1_Q38	0.054	0.480
FU1_Q47	0.590	0.124
FU1_Q55	0.785	-0.032
FU1_Q67	0.077	0.467
FU1_Q75	0.013	0.657
FU1_Q98	0.379	0.300
FU1_Q109	0.662	0.091
FU1_Q128	0.810	-0.031
FU1_Q152	0.620	0.085
FU1_Q173	0.017	0.810
FU1_Q196	0.840	-0.058

Component analysis (reproducing full covariance matrix)

	TC1	TC2
FU1_Q13	0.057	0.768
FU1_Q38	-0.086	0.709
FU1_Q47	0.694	0.070
FU1_Q55	0.811	-0.016
FU1_Q67	-0.082	0.722
FU1_Q75	-0.017	0.757
FU1_Q98	0.357	0.395
FU1_Q109	0.762	0.039
FU1_Q128	0.840	-0.029
FU1_Q152	0.731	0.026
FU1_Q173	0.110	0.749
FU1_Q196	0.844	-0.030

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
FU1_Q13	2.22538860103627	2	0.722156139325148	0.849797704942269	1	0.0305848886483769	1	1	3	4	0.251487385459707	-0.562130192696993	0.142487046632124	772	772
FU1_Q38	2.05569948186529	2	0.672639328508162	0.820145919034023	2	0.0295176975216477	1	1	3	4	0.377645590586151	-0.45878052246223	0.132772020725389	772	772
FU1_Q47	2	2	0.90272373540856	0.950117748181014	2	0.0341954860103288	1	1	3	4	0.664070235883656	-0.49015517760475	0.178108808290155	772	772
FU1_Q55	1.59455958549223	1	0.71348527919464	0.844680578203761	1	0.0304007192271291	1	NA	2	4	1.25481308423135	0.595264449194107	0.117875647668394	772	772
FU1_Q67	2.74611398963731	3	0.737014710724918	0.858495609030657	1	0.030897933066443	1	2	4	4	-0.362875336361519	-0.442317162216665	0.125647668393782	772	772
FU1_Q75	2.39896373056995	2	0.758909430589437	0.871154079706591	1	0.0313535213950894	1	1	3	4	0.146832787355493	-0.645669704133507	0.161917098445596	772	772
FU1_Q98	1.69559585492228	2	0.621874222965935	0.788590022106503	1	0.0283819759397761	1	1	3	4	0.882019994869263	0.0263182715388405	0.178108808290155	772	772
FU1_Q109	1.95725388601036	2	0.982606197455696	0.991264948162547	2	0.0356764061426245	1	1	3	4	0.678497300699645	-0.675543719446924	0.15220207253886	772	772
FU1_Q128	1.7940414507772	1	0.89267521488142	0.944814910382674	1	0.0340046327017833	1	NA	3	4	0.837203646058025	-0.49903825539268	0.120466321243523	772	772
FU1_Q152	1.95984455958549	2	1.01654368527516	1.00823791104836	2	0.0362872764437286	1	1	3	4	0.674308580835227	-0.736341880037081	0.143134715025907	772	772
FU1_Q173	2.19948186528497	2	0.727989355053326	0.853222922250291	1	0.0307081649167794	1	1	3	4	0.259551695508963	-0.590024710519616	0.140544041450777	772	772
FU1_Q196	1.59455958549223	1	0.721267380361955	0.849274620109394	1	0.0305660624132928	1	NA	2	4	1.31373923388317	0.820801862503297	0.123704663212435	772	772

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
FU1_Q13	When someone hurts me, I try to retaliate (get even)	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	247	0.7700186	1	2	4	2.227328	0.8431912	4	<U+2583><U+2581><U+2587><U+2581><U+2581><U+2585><U+2581><U+2581>
FU1_Q38	I see no objection to stepping on people’s toes a little if it is to my advantage	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	250	0.7672253	1	2	4	2.053398	0.8187138	4	<U+2585><U+2581><U+2587><U+2581><U+2581><U+2585><U+2581><U+2581>
FU1_Q47	When I get angry I am often ready to hit someone	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	246	0.7709497	1	2	4	1.998792	0.9491285	4	<U+2587><U+2581><U+2587><U+2581><U+2581><U+2583><U+2581><U+2582>
FU1_Q55	I admit that I sometimes take pleasure in hurting someone physically	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	249	0.7681564	1	1	4	1.589091	0.8416508	4	<U+2587><U+2581><U+2583><U+2581><U+2581><U+2582><U+2581><U+2581>
FU1_Q67	I can’t help but enjoy it when someone I dislike makes a fool of herself/himself	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	249	0.7681564	1	3	4	2.746667	0.8576139	4	<U+2582><U+2581><U+2585><U+2581><U+2581><U+2587><U+2581><U+2583>
FU1_Q75	I would rather tum the other cheek than get even when someone treats me badly	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	246	0.7709497	1	2	4	2.411836	0.8731962	4	<U+2583><U+2581><U+2587><U+2581><U+2581><U+2586><U+2581><U+2582>
FU1_Q98	Sometimes I seem to enjoy hurting someone by saying something mean	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	248	0.7690875	1	2	4	1.700969	0.7963091	4	<U+2587><U+2581><U+2586><U+2581><U+2581><U+2582><U+2581><U+2581>
FU1_Q109	I enjoy a good brawl	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	248	0.7690875	1	2	4	1.960048	0.9979868	4	<U+2587><U+2581><U+2586><U+2581><U+2581><U+2583><U+2581><U+2582>
FU1_Q128	Sometimes I hit people who have done something to deserve it	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	246	0.7709497	1	1	4	1.785024	0.9419257	4	<U+2587><U+2581><U+2583><U+2581><U+2581><U+2583><U+2581><U+2581>
FU1_Q152	I like to watch a good, vicious fight	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	285	0.7346369	1	2	4	1.968314	1.0114872	4	<U+2587><U+2581><U+2586><U+2581><U+2581><U+2583><U+2581><U+2582>
FU1_Q173	When people insult me, I try to get even	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	247	0.7700186	1	2	4	2.195889	0.8510541	4	<U+2583><U+2581><U+2587><U+2581><U+2581><U+2585><U+2581><U+2581>
FU1_Q196	Sometimes I just like to hit someone	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	246	0.7709497	1	1	4	1.601449	0.8591764	4	<U+2587><U+2581><U+2583><U+2581><U+2581><U+2582><U+2581><U+2581>

Scale: CON_2

Overview

Reliability: .

Missing: 300.

Likert plot of scale CON_2 items

Distribution of scale CON_2

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	FU1_Q15, FU1_Q31, FU1_Q37, FU1_Q129, FU1_Q53, FU1_Q60, FU1_Q69, FU1_Q92, FU1_Q102, FU1_Q149, FU1_Q159 & FU1_Q180
Observations:	774
Positive correlations:	55
Number of correlations:	66
Percentage positive correlations:	83

Estimates assuming interval level

Omega (total):	0.87
Omega (hierarchical):	0.69
Revelle’s Omega (total):	0.87
Greatest Lower Bound (GLB):	0.86
Coefficient H:	0.87
Coefficient Alpha:	0.79

(Estimates assuming ordinal level not computed, as the polychoric correlation matrix has missing values.)

Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help (‘?ufs::scaleStructure’) for more information.

Eigen values

4.537, 1.197, 1, 0.842, 0.805, 0.718, 0.633, 0.556, 0.506, 0.449, 0.389 & 0.369

Factor analysis (reproducing only shared variance)

	ML1	ML2
FU1_Q15	0.717	-0.060
FU1_Q31	0.813	-0.033
FU1_Q37	-0.046	0.815
FU1_Q129	-0.186	-0.219
FU1_Q53	0.493	-0.040
FU1_Q60	0.483	0.148
FU1_Q69	0.460	0.095
FU1_Q92	0.314	0.421
FU1_Q102	0.755	0.001
FU1_Q149	0.521	0.128
FU1_Q159	0.070	0.618
FU1_Q180	0.366	0.134

Component analysis (reproducing full covariance matrix)

	TC1	TC2
FU1_Q15	0.745	-0.057
FU1_Q31	0.806	-0.006
FU1_Q37	-0.032	0.849
FU1_Q129	-0.062	-0.474
FU1_Q53	0.645	-0.157
FU1_Q60	0.543	0.165
FU1_Q69	0.606	0.022
FU1_Q92	0.347	0.490
FU1_Q102	0.774	0.016
FU1_Q149	0.616	0.103
FU1_Q159	-0.005	0.804
FU1_Q180	0.452	0.125

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
FU1_Q15	3.01033591731266	3	0.607913729186932	0.779688225630561	1	0.0280253145346039	1	2	4	4	-0.494118925987517	-0.100639279058284	0.135658914728682	774	774
FU1_Q31	2.82170542635659	3	0.61241312915551	0.782568290410179	1	0.0281288363253344	1	2	4	4	-0.309606270638204	-0.253895776982862	0.12984496124031	774	774
FU1_Q37	2.43798449612403	2	0.844143927314299	0.918773055391972	1	0.0330246155025042	1	1	3	4	0.00766638334295338	-0.835460806589809	0.172480620155039	774	774
FU1_Q129	2.50645994832041	3	0.76515873254644	0.874733520877324	1	0.0314416471234032	1	2	4	4	-0.0604851893433053	-0.686785995575423	0.175710594315245	774	774
FU1_Q53	2.92118863049096	3	0.572047226985703	0.75633803751081	0	0.0271860093546789	1	2	4	4	-0.443882958210559	0.0473432739530056	0.104005167958656	774	774
FU1_Q60	2.52583979328165	3	0.715372838466193	0.845797161538269	1	0.0304015511654227	1	2	4	4	-0.13264707842149	-0.584974496476939	0.171188630490956	774	774
FU1_Q69	2.30490956072351	2	0.784012087541075	0.885444570563892	1	0.031826647853944	1	1	3	4	0.171320401896834	-0.709489075382467	0.155684754521964	774	774
FU1_Q92	2.21188630490956	2	0.658797730911814	0.811663557708373	1	0.0291746441119543	1	1	3	4	0.162337859349695	-0.558873520198192	0.153100775193798	774	774
FU1_Q102	2.8062015503876	3	0.575588916634074	0.758675765155362	1	0.0272700372396478	1	2	4	4	-0.355482910133356	-0.0686822041465977	0.125968992248062	774	774
FU1_Q149	2.70542635658915	3	0.60134179728632	0.775462311970298	1	0.0278734172048357	1	2	4	4	-0.304365530310157	-0.202314571555203	0.144702842377261	774	774
FU1_Q159	2.72222222222222	3	0.669182118729337	0.818035524124312	1	0.0294036797150843	1	2	4	4	-0.202213065481832	-0.466867859624525	0.153100775193798	774	774
FU1_Q180	3.05684754521964	3	0.449545547232	0.670481578592581	0	0.0240999626671524	1	2	4	4	-0.479391573199977	0.60480722286246	0.116925064599483	774	774

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
FU1_Q15	When faced with a decision I usually take time to consider and weigh all aspects	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	248	0.7690875	1	3	4	3.009685	0.7768799	4	<U+2581><U+2581><U+2583><U+2581><U+2581><U+2587><U+2581><U+2585>
FU1_Q31	I like to stop and think things over before I do them	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	249	0.7681564	1	3	4	2.824242	0.7817046	4	<U+2581><U+2581><U+2585><U+2581><U+2581><U+2587><U+2581><U+2583>
FU1_Q37	I often prefer to “play things by ear” rather than to plan ahead	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	245	0.7718808	1	2	4	2.428227	0.9214169	4	<U+2583><U+2581><U+2587><U+2581><U+2581><U+2587><U+2581><U+2583>
FU1_Q129	I often start projects with only a vague idea of what the end result will be	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	247	0.7700186	1	3	4	2.516324	0.8847166	4	<U+2583><U+2581><U+2587><U+2581><U+2581><U+2587><U+2581><U+2583>
FU1_Q53	I am very level-headed and always like to keep my feet on the ground	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	246	0.7709497	1	3	4	2.905797	0.7639490	4	<U+2581><U+2581><U+2583><U+2581><U+2581><U+2587><U+2581><U+2583>
FU1_Q60	I am more likely to be fast and careless than to be slow and plodding	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	249	0.7681564	1	3	4	2.513939	0.8533840	4	<U+2582><U+2581><U+2586><U+2581><U+2581><U+2587><U+2581><U+2582>
FU1_Q69	I almost never do anything reckless	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	248	0.7690875	1	2	4	2.297821	0.8908532	4	<U+2583><U+2581><U+2587><U+2581><U+2581><U+2586><U+2581><U+2582>
FU1_Q92	I often act on the spur of the moment	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	246	0.7709497	1	2	4	2.204106	0.8099338	4	<U+2583><U+2581><U+2587><U+2581><U+2581><U+2586><U+2581><U+2581>
FU1_Q102	I usually make up my mind through careful reasoning	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	247	0.7700186	1	3	4	2.804111	0.7561419	4	<U+2581><U+2581><U+2583><U+2581><U+2581><U+2587><U+2581><U+2582>
FU1_Q149	I am a cautious person	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	286	0.7337058	1	3	4	2.701777	0.7751849	4	<U+2581><U+2581><U+2585><U+2581><U+2581><U+2587><U+2581><U+2582>
FU1_Q159	I generally do not like to have detailed plans	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	284	0.7355680	1	3	4	2.718987	0.8146435	4	<U+2581><U+2581><U+2585><U+2581><U+2581><U+2587><U+2581><U+2583>
FU1_Q180	Before I get into a new situation I like to find out what to expect from it	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	246	0.7709497	1	3	4	3.039855	0.6775773	4	<U+2581><U+2581><U+2582><U+2581><U+2581><U+2587><U+2581><U+2583>

Scale: HA_2

Overview

Reliability: .

Missing: 303.

Likert plot of scale HA_2 items

Distribution of scale HA_2

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	FU1_Q71, FU1_Q21, FU1_Q45, FU1_Q62, FU1_Q84, FU1_Q90, FU1_Q100, FU1_Q108, FU1_Q117, FU1_Q147, FU1_Q171 & FU1_Q194
Observations:	771
Positive correlations:	66
Number of correlations:	66
Percentage positive correlations:	100

Estimates assuming interval level

Omega (total):	0.81
Omega (hierarchical):	0.55
Revelle’s Omega (total):	0.81
Greatest Lower Bound (GLB):	0.84
Coefficient H:	0.81
Coefficient Alpha:	0.78

(Estimates assuming ordinal level not computed, as the polychoric correlation matrix has missing values.)

Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help (‘?ufs::scaleStructure’) for more information.

Eigen values

3.638, 1.241, 1.029, 0.908, 0.835, 0.75, 0.714, 0.654, 0.635, 0.582, 0.547 & 0.469

Factor analysis (reproducing only shared variance)

	ML1	ML3	ML2
FU1_Q71	-0.182	0.474	0.180
FU1_Q21	0.463	0.323	-0.005
FU1_Q45	0.506	0.062	0.279
FU1_Q62	0.111	0.202	0.193
FU1_Q84	0.103	0.516	0.075
FU1_Q90	0.590	0.079	-0.117
FU1_Q100	0.292	0.301	-0.008
FU1_Q108	0.646	-0.116	0.077
FU1_Q117	0.200	0.263	0.144
FU1_Q147	0.133	0.108	0.352
FU1_Q171	0.021	0.507	-0.048
FU1_Q194	0.006	0.017	0.735

Component analysis (reproducing full covariance matrix)

	TC1	TC3	TC2
FU1_Q71	-0.266	0.277	0.647
FU1_Q21	0.566	0.041	0.356
FU1_Q45	0.529	0.364	0.052
FU1_Q62	0.061	0.544	0.040
FU1_Q84	0.183	0.193	0.530
FU1_Q90	0.765	-0.109	0.028
FU1_Q100	0.441	0.072	0.275
FU1_Q108	0.728	0.127	-0.171
FU1_Q117	0.262	0.327	0.200
FU1_Q147	0.070	0.696	-0.064
FU1_Q171	0.102	-0.163	0.780
FU1_Q194	-0.018	0.762	0.023

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
FU1_Q71	2.91439688715953	3	1.45240285006822	1.20515677406229	2	0.0434026610453933	1	1	4	4	-0.553684824286371	-1.30424285182406	0.104409857328145	771	771
FU1_Q21	2.69909208819715	3	1.13790826553472	1.0667278310491	2	0.0384172644382604	1	2	4	4	-0.156652678619224	-1.25298325528238	0.146562905317769	771	771
FU1_Q45	2.69001297016861	3	1.27910792190948	1.1309765346414	2	0.0407311249787634	1	2	4	4	-0.196308223505884	-1.37209255754228	0.123216601815824	771	771
FU1_Q62	2.44357976653697	2	1.54064379200566	1.24122672868645	3	0.0447016887305616	1	1	4	4	0.0844703384352444	-1.60915572842722	0.154345006485084	771	771
FU1_Q84	2.8715953307393	3	1.38738693213401	1.17787390332498	2	0.0424200924564408	1	1	4	4	-0.509821198172081	-1.2747268557291	0.108300907911803	771	771
FU1_Q90	2.71076523994812	3	1.09155928377718	1.04477714550864	2	0.0376267298084667	1	2	4	4	-0.243234116125401	-1.13631509179888	0.141374837872892	771	771
FU1_Q100	2.25810635538262	2	1.35796991594657	1.16531966255898	2	0.0419679625191778	1	1	4	4	0.325905668435213	-1.37451898469548	0.119325551232166	771	771
FU1_Q108	2.48378728923476	2	1.09681472872134	1.04728922878131	1	0.0377172002776603	1	1	3	4	0.117837857101927	-1.17997882703636	0.114785992217899	771	771
FU1_Q117	2.61997405966278	3	1.56058753179376	1.24923477849192	3	0.0449900915996506	1	1	4	4	-0.142065451835169	-1.61639487125394	0.143968871595331	771	771
FU1_Q147	2.8378728923476	3	1.37497936564084	1.17259514140254	2	0.0422299824895139	1	1	4	4	-0.438334403582143	-1.32836704799461	0.103761348897536	771	771
FU1_Q171	2.83527885862516	3	1.38452001953947	1.17665628776609	2	0.04237624110322	1	1	4	4	-0.459364014557024	-1.31141558778091	0.11219195849546	771	771
FU1_Q194	2.82101167315175	3	1.37831118298044	1.17401498413796	2	0.0422811168765988	1	1	4	4	-0.421402850856458	-1.34010831944036	0.107003891050584	771	771

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
FU1_Q71	Of the following two situations I would dislike more: (A) Having a pilot announce that the plane has engine trouble and he may have to make an emergency landing, (B) Working in the fields digging potatoes.	haven_labelled	4. Definitely A, 3. Probably A, 2. Probably B, 1. Definitely B	248	0.7690875	1	3	4	2.900726	1.212990	4	<U+2583><U+2581><U+2582><U+2581><U+2581><U+2583><U+2581><U+2587>
FU1_Q21	It might be fun and exciting to experience an earthquake	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	247	0.7700186	1	3	4	2.695284	1.065194	4	<U+2583><U+2581><U+2587><U+2581><U+2581><U+2586><U+2581><U+2587>
FU1_Q45	I might enjoy riding in an open elevator to the top of a tall building under construction	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	246	0.7709497	1	3	4	2.693237	1.131115	4	<U+2585><U+2581><U+2586><U+2581><U+2581><U+2585><U+2581><U+2587>
FU1_Q62	Of the following two situations I would dislike more: (A) Having to walk around all day on a blistered foot, (B) Sleeping out on a camping trip in an area where there are rattlesnakes.	haven_labelled	1. Definitely A, 2. Probably A, 3. Probably B, 4. Definitely B	252	0.7653631	1	2	4	2.451338	1.242543	4	<U+2587><U+2581><U+2585><U+2581><U+2581><U+2583><U+2581><U+2587>
FU1_Q84	Of the following two situations I would dislike more: (A) Being out on a sailboat during a great storm at sea. (B) Having to stay home every night for two weeks with a sick relative.	haven_labelled	4. Definitely A, 3. Probably A, 2. Probably B, 1. Definitely B	249	0.7681564	1	3	4	2.884848	1.180372	4	<U+2583><U+2581><U+2582><U+2581><U+2581><U+2583><U+2581><U+2587>
FU1_Q90	I would enjoy trying to cross the ocean in a small but seaworthy sailboat	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	246	0.7709497	1	3	4	2.721014	1.049301	4	<U+2585><U+2581><U+2587><U+2581><U+2581><U+2587><U+2581><U+2587>
FU1_Q100	Of the following two situations I would dislike more: (A) Riding a long stretch of rapids in a canoe. (B) Waiting for someone who’s late.	haven_labelled	4. Definitely A, 3. Probably A, 2. Probably B, 1. Definitely B	249	0.7681564	1	2	4	2.256970	1.170803	4	<U+2587><U+2581><U+2585><U+2581><U+2581><U+2583><U+2581><U+2585>
FU1_Q108	It might be fun learning to walk a tightrope	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	249	0.7681564	1	2	4	2.483636	1.052061	4	<U+2585><U+2581><U+2587><U+2581><U+2581><U+2585><U+2581><U+2585>
FU1_Q117	Of the following two situations I would dislike more: (A) Being at the circus when two lions suddenly get loose down in the ring, (B) Bringing my whole family to the circus and then not being able to get in because a clerk sold me tickets for the wrong night.	haven_labelled	4. Definitely A, 3. Probably A, 2. Probably B, 1. Definitely B	248	0.7690875	1	3	4	2.624697	1.249318	4	<U+2586><U+2581><U+2583><U+2581><U+2581><U+2583><U+2581><U+2587>
FU1_Q147	Of the following two situations I would dislike more: (A) Being chosen as the “target” for a knife-throwing act, (B) Being sick to my stomach for 24 hours.	haven_labelled	4. Definitely A, 3. Probably A, 2. Probably B, 1. Definitely B	285	0.7346369	1	3	4	2.835234	1.175350	4	<U+2583><U+2581><U+2583><U+2581><U+2581><U+2583><U+2581><U+2587>
FU1_Q171	Of the following two situations I would dislike more: (A) Being in a flood, (B) carrying a ton of coal from the backyard into the basement.	haven_labelled	4. Definitely A, 3. Probably A, 2. Probably B, 1. Definitely B	284	0.7355680	1	3	4	2.836709	1.176413	4	<U+2585><U+2581><U+2583><U+2581><U+2581><U+2585><U+2581><U+2587>
FU1_Q194	Of the following two situations I would dislike more: (A) Being seasick every day for a week while on an ocean voyage. (B) Having to stand on the ledge of the 25th floor of a hotel because there’s a fire in my room.	haven_labelled	1. Definitely A, 2. Probably A, 3. Probably B, 4. Definitely B	246	0.7709497	1	3	4	2.829710	1.172534	4	<U+2585><U+2581><U+2583><U+2581><U+2581><U+2585><U+2581><U+2587>

Scale: SP_2

Overview

Reliability: .

Missing: 306.

Likert plot of scale SP_2 items

Distribution of scale SP_2

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	FU1_Q1, FU1_Q14, FU1_Q30, FU1_Q54, FU1_Q61, FU1_Q77, FU1_Q91, FU1_Q119, FU1_Q142, FU1_Q153, FU1_Q170 & FU1_Q184
Observations:	768
Positive correlations:	66
Number of correlations:	66
Percentage positive correlations:	100

Estimates assuming interval level

Omega (total):	0.87
Omega (hierarchical):	0.62
Revelle’s Omega (total):	0.87
Greatest Lower Bound (GLB):	0.86
Coefficient H:	0.88
Coefficient Alpha:	0.83

(Estimates assuming ordinal level not computed, as the polychoric correlation matrix has missing values.)

Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help (‘?ufs::scaleStructure’) for more information.

Eigen values

4.448, 1.357, 1.072, 0.971, 0.784, 0.726, 0.593, 0.546, 0.497, 0.369, 0.353 & 0.284

Factor analysis (reproducing only shared variance)

	ML1	ML2	ML3
FU1_Q1	0.277	0.006	0.388
FU1_Q14	0.125	0.619	0.040
FU1_Q30	0.019	0.179	0.594
FU1_Q54	0.886	0.000	-0.049
FU1_Q61	0.782	0.074	-0.023
FU1_Q77	0.114	-0.067	0.272
FU1_Q91	-0.021	0.892	0.018
FU1_Q119	-0.062	-0.121	0.527
FU1_Q142	0.025	0.204	0.462
FU1_Q153	0.764	-0.070	0.088
FU1_Q170	0.498	0.107	0.083
FU1_Q184	0.278	-0.093	0.307

Component analysis (reproducing full covariance matrix)

	TC1	TC2	TC3
FU1_Q1	0.384	0.183	0.341
FU1_Q14	0.097	0.790	-0.120
FU1_Q30	0.052	0.586	0.354
FU1_Q54	0.885	-0.004	-0.042
FU1_Q61	0.819	0.066	-0.038
FU1_Q77	0.168	0.069	0.261
FU1_Q91	-0.016	0.885	-0.061
FU1_Q119	-0.078	0.017	0.825
FU1_Q142	-0.004	0.603	0.283
FU1_Q153	0.864	-0.054	0.033
FU1_Q170	0.611	0.171	-0.044
FU1_Q184	0.404	-0.127	0.501

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
FU1_Q1	2.98307291666667	3	0.530351952955237	0.728252671093788	0	0.0262785547308789	1	2	4	4	-0.44113022447879	0.13449648135935	0.11328125	768	768
FU1_Q14	2.72265625	3	0.771741566166884	0.87848822767689	1	0.0316997134205731	1	2	4	4	-0.193032341464716	-0.685908027837992	0.15234375	768	768
FU1_Q30	2.46484375	2	0.679336090286832	0.82421847242514	1	0.0297414223078573	1	1	3	4	0.00755926547123569	-0.535789224869684	0.193359375	768	768
FU1_Q54	2.98307291666667	3	0.585110753476749	0.764925325425135	0	0.0276018651590103	1	2	4	4	-0.479590703967013	0.00162807163521751	0.123046875	768	768
FU1_Q61	2.90625	3	0.523142112125163	0.723285636609191	0.5	0.0260993223123317	1	2	4	4	-0.354158466124968	0.0435047462032084	0.109375	768	768
FU1_Q77	2.00260416666667	2	0.651883691873099	0.807393145792741	1	0.0291342906290811	1	1	3	4	0.501920406030309	-0.210662183532781	0.139973958333333	768	768
FU1_Q91	2.76302083333333	3	0.759934539330726	0.871742243630952	1	0.0314562886890186	1	2	4	4	-0.326358786515712	-0.539829784989743	0.130208333333333	768	768
FU1_Q119	2.48697916666667	3	0.769061006084311	0.876961234082962	1	0.0316446127854165	1	2	4	4	-0.0706595812728004	-0.700115064224234	0.173177083333333	768	768
FU1_Q142	2.51822916666667	3	0.617659441547153	0.785913125954233	1	0.0283591971768335	1	2	4	4	-0.116903889743951	-0.4105455589498	0.188151041666667	768	768
FU1_Q153	2.86197916666667	3	0.549373913515863	0.741197621094309	1	0.0267456653788443	1	2	4	4	-0.390065370871314	0.0553650283506772	0.113932291666667	768	768
FU1_Q170	2.80859375	3	0.585219401890482	0.76499634109614	1	0.0276044277163085	1	2	4	4	-0.361676878785878	-0.0863793890806705	0.125	768	768
FU1_Q184	2.6875	3	0.603650586701434	0.776949539353383	1	0.028035751605777	1	2	4	4	-0.363721654147229	-0.154841080325289	0.139973958333333	768	768

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
FU1_Q1	When I work with others I like to take charge	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	246	0.7709497	1	3	4	2.987923	0.7209754	4	<U+2581><U+2581><U+2582><U+2581><U+2581><U+2587><U+2581><U+2583>
FU1_Q14	I enjoy being in the spotlight	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	249	0.7681564	1	3	4	2.729697	0.8748942	4	<U+2582><U+2581><U+2586><U+2581><U+2581><U+2587><U+2581><U+2583>
FU1_Q30	On most social occasions I like to have someone else take the lead	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	247	0.7700186	1	2	4	2.469166	0.8204143	4	<U+2582><U+2581><U+2587><U+2581><U+2581><U+2587><U+2581><U+2582>
FU1_Q54	I am quite effective at talking people into things	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	245	0.7718808	1	3	4	2.984319	0.7683316	4	<U+2581><U+2581><U+2583><U+2581><U+2581><U+2587><U+2581><U+2583>
FU1_Q61	I am very good at influencing people	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	248	0.7690875	1	3	4	2.918886	0.7199035	4	<U+2581><U+2581><U+2583><U+2581><U+2581><U+2587><U+2581><U+2583>
FU1_Q77	People consider me forceful	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	249	0.7681564	1	2	4	2.001212	0.7997260	4	<U+2585><U+2581><U+2587><U+2581><U+2581><U+2583><U+2581><U+2581>
FU1_Q91	I do not like to be the center of attention on social occasions	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	248	0.7690875	1	3	4	2.766344	0.8682301	4	<U+2582><U+2581><U+2585><U+2581><U+2581><U+2587><U+2581><U+2583>
FU1_Q119	I do not like to organize other people’s activities	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	248	0.7690875	1	3	4	2.490315	0.8783059	4	<U+2583><U+2581><U+2587><U+2581><U+2581><U+2587><U+2581><U+2582>
FU1_Q142	On social occasions I usually allow others to dominate the conversation	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	286	0.7337058	1	3	4	2.520305	0.7847621	4	<U+2582><U+2581><U+2587><U+2581><U+2581><U+2587><U+2581><U+2582>
FU1_Q153	I am quite good at convincing others to see things my way	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	285	0.7346369	1	3	4	2.869455	0.7366010	4	<U+2581><U+2581><U+2583><U+2581><U+2581><U+2587><U+2581><U+2582>
FU1_Q170	I don’t enjoy trying to convince people of something	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	288	0.7318436	1	3	4	2.816794	0.7618435	4	<U+2581><U+2581><U+2583><U+2581><U+2581><U+2587><U+2581><U+2582>
FU1_Q184	When it is time to make decisions, others usually tum to me	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	248	0.7690875	1	3	4	2.686441	0.7736479	4	<U+2581><U+2581><U+2585><U+2581><U+2581><U+2587><U+2581><U+2582>

Scale: TR_2

Overview

Reliability: .

Missing: 340.

Likert plot of scale TR_2 items

Distribution of scale TR_2

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	FU1_Q7, FU1_Q36, FU1_Q52, FU1_Q58, FU1_Q105, FU1_Q113, FU1_Q126, FU1_Q150, FU1_Q168, FU1_Q174, FU1_Q181 & FU1_Q190
Observations:	734
Positive correlations:	66
Number of correlations:	66
Percentage positive correlations:	100

Estimates assuming interval level

Omega (total):	0.80
Omega (hierarchical):	0.59
Revelle’s Omega (total):	0.80
Greatest Lower Bound (GLB):	0.80
Coefficient H:	0.80
Coefficient Alpha:	0.76

(Estimates assuming ordinal level not computed, as the polychoric correlation matrix has missing values.)

Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help (‘?ufs::scaleStructure’) for more information.

Eigen values

3.521, 1.384, 1.021, 0.947, 0.788, 0.74, 0.705, 0.649, 0.625, 0.577, 0.536 & 0.507

Factor analysis (reproducing only shared variance)

	ML2	ML3	ML1
FU1_Q7	0.007	0.011	0.991
FU1_Q36	-0.104	0.576	0.067
FU1_Q52	0.663	0.043	0.021
FU1_Q58	0.548	-0.138	0.077
FU1_Q105	0.124	0.570	0.083
FU1_Q113	0.451	0.127	-0.007
FU1_Q126	-0.024	0.182	0.177
FU1_Q150	0.132	0.168	-0.031
FU1_Q168	0.603	-0.044	0.001
FU1_Q174	0.149	0.491	-0.125
FU1_Q181	0.531	0.159	-0.036
FU1_Q190	-0.006	0.585	0.053

Component analysis (reproducing full covariance matrix)

	TC1	TC2	TC3
FU1_Q7	-0.013	0.564	0.292
FU1_Q36	-0.080	0.786	-0.103
FU1_Q52	0.708	0.125	-0.052
FU1_Q58	0.665	-0.138	0.050
FU1_Q105	0.227	0.639	0.055
FU1_Q113	0.587	0.161	-0.123
FU1_Q126	-0.095	0.124	0.784
FU1_Q150	0.228	-0.137	0.623
FU1_Q168	0.711	-0.097	0.095
FU1_Q174	0.263	0.483	-0.104
FU1_Q181	0.634	0.149	-0.002
FU1_Q190	0.049	0.632	0.185

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
FU1_Q7	2.93188010899183	3	0.579255123396441	0.761088118023426	0	0.0280922750490921	1	2	4	4	-0.51818840098518	0.179650806525565	0.10558583106267	734	734
FU1_Q36	2.74659400544959	3	0.620554549813948	0.787752848178887	1	0.0290764881985266	1	2	4	4	-0.291757564491095	-0.261863503282699	0.140326975476839	734	734
FU1_Q52	2.52861035422343	3	0.887993427778046	0.942334031953662	1	0.034782183806143	1	2	4	4	0.00550184651247971	-0.897665473061769	0.166212534059946	734	734
FU1_Q58	2.21117166212534	2	0.952617179223154	0.976021095685516	2	0.0360255960176083	1	1	3	4	0.246774312421545	-1.00395560615041	0.14441416893733	734	734
FU1_Q105	2.8841961852861	3	0.533638029671649	0.73050532487563	1	0.0269634435556921	1	2	4	4	-0.428012089524719	0.179890431258241	0.106267029972752	734	734
FU1_Q113	1.86512261580381	2	0.760773723007609	0.872223436401252	1	0.032194354502975	1	1	3	4	0.759570365906574	-0.187435078036857	0.192779291553134	734	734
FU1_Q126	3.27384196185286	3	0.673885082766132	0.820905038823695	1	0.0303001578840981	1	2	4	4	-0.944321798805414	0.213155626449269	0.181198910081744	734	734
FU1_Q150	2.84877384196185	3	0.949814319860526	0.974584177924373	2	0.0359725584152427	1	2	4	4	-0.518131628008235	-0.693303408909801	0.141689373297003	734	734
FU1_Q168	2.35149863760218	2	0.850359278988592	0.922149271532864	1	0.0340371507040447	1	1	3	4	0.0119367151922051	-0.906425422591901	0.162806539509537	734	734
FU1_Q174	2.5299727520436	3	0.795144064740847	0.891708508841789	1	0.0329135616504636	1	2	4	4	-0.021083562254737	-0.741000892691542	0.179155313351499	734	734
FU1_Q181	2.56675749318801	3	0.706997111642275	0.840831202823893	1	0.0310356460181405	1	2	4	4	-0.149015084370844	-0.551403414318315	0.168256130790191	734	734
FU1_Q190	3.04904632152589	3	0.589678488983722	0.767905260421962	1	0.0283439003665466	1	2	4	4	-0.60930103526156	0.212841112343292	0.140326975476839	734	734

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
FU1_Q7	The best way to achieve a peaceful world is to improve people’s morals	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	245	0.7718808	1	3	4	2.931243	0.7542799	4	<U+2581><U+2581><U+2582><U+2581><U+2581><U+2587><U+2581><U+2583>
FU1_Q36	Higher standards of conduct are what this country needs most	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	253	0.7644320	1	3	4	2.749087	0.7795494	4	<U+2581><U+2581><U+2585><U+2581><U+2581><U+2587><U+2581><U+2582>
FU1_Q52	I would prefer to see: (A) Stricter observance of the Sabbath, (B) Greater freedom in regard to divorce.	haven_labelled	4. Definitely A, 3. Probably A, 2. Probably B, 1. Definitely B	270	0.7486034	1	3	4	2.511194	0.9409060	4	<U+2583><U+2581><U+2587><U+2581><U+2581><U+2587><U+2581><U+2583>
FU1_Q58	More censorship of books and movies is a violation of free speech and should be abolished	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	253	0.7644320	1	2	4	2.204629	0.9813023	4	<U+2587><U+2581><U+2587><U+2581><U+2581><U+2587><U+2581><U+2583>
FU1_Q105	People should observe moral laws more strictly than they do	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	252	0.7653631	1	3	4	2.880779	0.7290027	4	<U+2581><U+2581><U+2583><U+2581><U+2581><U+2587><U+2581><U+2582>
FU1_Q113	I am disgusted by foul language	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	247	0.7700186	1	2	4	1.848851	0.8636501	4	<U+2587><U+2581><U+2587><U+2581><U+2581><U+2583><U+2581><U+2581>
FU1_Q126	No decent person could ever think of hurting a close friend or relative	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	246	0.7709497	1	3	4	3.285024	0.8248955	4	<U+2581><U+2581><U+2582><U+2581><U+2581><U+2586><U+2581><U+2587>
FU1_Q150	It is a pretty callous (unfeeling) person who does not feel love and gratitude toward her/his parents	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	287	0.7327747	1	3	4	2.838628	0.9784612	4	<U+2582><U+2581><U+2583><U+2581><U+2581><U+2587><U+2581><U+2586>
FU1_Q168	I don’t like to see religious authority overturned by so-called progress and logical reasoning	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	297	0.7234637	1	2	4	2.339768	0.9224443	4	<U+2585><U+2581><U+2587><U+2581><U+2581><U+2587><U+2581><U+2582>
FU1_Q174	Strict discipline in the home would prevent much of the crime in our society	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	249	0.7681564	1	2	4	2.496970	0.8896945	4	<U+2583><U+2581><U+2587><U+2581><U+2581><U+2587><U+2581><U+2583>
FU1_Q181	I am not at all sorry to see many of the traditional values change	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	251	0.7662942	1	3	4	2.569866	0.8398041	4	<U+2582><U+2581><U+2586><U+2581><U+2581><U+2587><U+2581><U+2582>
FU1_Q190	High moral standards are the most important thing parents can teach their children	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	245	0.7718808	1	3	4	3.055489	0.7704127	4	<U+2581><U+2581><U+2582><U+2581><U+2581><U+2587><U+2581><U+2585>

Scale: AC_3

Overview

Reliability: .

Missing: 384.

Likert plot of scale AC_3 items

Distribution of scale AC_3

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	FU3_AC_10, FU3_AC_55, FU3_AC_80, FU3_AC_98, FU3_AC_110_R, FU3_AC_124, FU3_AC_136, FU3_AC_180, FU3_AC_196_R, FU3_AC_213, FU3_AC_223 & FU3_AC_294
Observations:	690
Positive correlations:	66
Number of correlations:	66
Percentage positive correlations:	100

Estimates assuming interval level

Omega (total):	0.90
Omega (hierarchical):	0.73
Revelle’s Omega (total):	0.90
Greatest Lower Bound (GLB):	0.92
Coefficient H:	0.89
Coefficient Alpha:	0.88

(Estimates assuming ordinal level not computed, as the polychoric correlation matrix has missing values.)

Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help (‘?ufs::scaleStructure’) for more information.

Eigen values

5.25, 0.991, 0.947, 0.759, 0.67, 0.641, 0.561, 0.521, 0.443, 0.436, 0.399 & 0.382

Factor analysis (reproducing only shared variance)

	ML1
FU3_AC_10	0.595
FU3_AC_55	0.574
FU3_AC_80	0.686
FU3_AC_98	0.659
FU3_AC_110_R	0.571
FU3_AC_124	0.620
FU3_AC_136	0.691
FU3_AC_180	0.551
FU3_AC_196_R	0.532
FU3_AC_213	0.721
FU3_AC_223	0.624
FU3_AC_294	0.616

Component analysis (reproducing full covariance matrix)

	PC1
FU3_AC_10	0.638
FU3_AC_55	0.620
FU3_AC_80	0.720
FU3_AC_98	0.697
FU3_AC_110_R	0.617
FU3_AC_124	0.657
FU3_AC_136	0.726
FU3_AC_180	0.592
FU3_AC_196_R	0.577
FU3_AC_213	0.746
FU3_AC_223	0.666
FU3_AC_294	0.657

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
FU3_AC_10	3.04492753623188	3	0.556759428703645	0.746163138129756	1	0.0284059452009418	1	2	4	4	-0.367080300894273	-0.334261409008068	0.140579710144928	690	690
FU3_AC_55	2.58840579710145	3	0.750518499821207	0.866324708074984	1	0.0329804179893975	1	2	4	4	-0.0523246204487594	-0.668369858597851	0.178260869565217	690	690
FU3_AC_80	3.11739130434783	3	0.594327001956206	0.770926067762795	1	0.0293486538208476	1	2	4	4	-0.452162752749099	-0.493671659253724	0.171739130434783	690	690
FU3_AC_98	2.88405797101449	3	0.52935361056772	0.727566911402464	1	0.0276979989484858	1	2	4	4	-0.272357967487207	-0.134037810103148	0.121014492753623	690	690
FU3_AC_110_R	3.18115942028985	3	0.557844807639722	0.746890090736061	1	0.0284336198136949	1	2	4	4	-0.558942077507674	-0.234918008975182	0.184057971014493	690	690
FU3_AC_124	3.11304347826087	3	0.495185208556825	0.703693973653906	1	0.0267891717405769	1	2	4	4	-0.412303071477149	-0.0972508769977824	0.147826086956522	690	690
FU3_AC_136	3.19855072463768	3	0.43221850613155	0.657433271238648	1	0.025028056897704	1	2	4	4	-0.48041969429118	0.309613473039979	0.161594202898551	690	690
FU3_AC_180	2.30579710144928	2	0.726381439178814	0.852280141255687	1	0.032445750468244	1	1	3	4	0.244847055446181	-0.530247404751895	0.146376811594203	690	690
FU3_AC_196_R	3.11014492753623	3	0.574207526135336	0.757764822445154	1	0.0288476137745567	1	2	4	4	-0.427035894703452	-0.458346740984486	0.165217391304348	690	690
FU3_AC_213	2.90289855072464	3	0.566755011463789	0.752831330022728	1	0.0286597989278571	1	2	4	4	-0.124915046042336	-0.60364304593572	0.13768115942029	690	690
FU3_AC_223	2.82028985507246	3	0.513375822973854	0.716502493347967	1	0.0272767837518679	1	2	4	4	-0.0526161525970284	-0.428977932464269	0.150724637681159	690	690
FU3_AC_294	3.33913043478261	3	0.450861361771944	0.671462107472897	1	0.0255621255657193	1	2	4	4	-0.639281271932739	-0.169082008333844	0.223188405797101	690	690

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
FU3_AC_10	I often keep working on a problem even if I am very tired	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	378	0.6480447	1	3	4	3.045977	0.7457590	4	<U+2581><U+2581><U+2583><U+2581><U+2581><U+2587><U+2581><U+2585>
FU3_AC_55	I enjoy putting in long hours	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	378	0.6480447	1	3	4	2.590517	0.8668951	4	<U+2582><U+2581><U+2587><U+2581><U+2581><U+2587><U+2581><U+2583>
FU3_AC_80	People say that I drive myself hard	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	378	0.6480447	1	3	4	3.114943	0.7744152	4	<U+2581><U+2581><U+2583><U+2581><U+2581><U+2587><U+2581><U+2586>
FU3_AC_98	I often keep working on a problem long after others would have given up	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	379	0.6471136	1	3	4	2.883453	0.7317026	4	<U+2581><U+2581><U+2583><U+2581><U+2581><U+2587><U+2581><U+2583>
FU3_AC_110_R	I try to work just hard enough to get by because I don’t want to overdo it	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	382	0.6443203	1	3	4	3.179191	0.7471900	4	<U+2581><U+2581><U+2582><U+2581><U+2581><U+2587><U+2581><U+2586>
FU3_AC_124	I like to try difficult things	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	383	0.6433892	1	3	4	3.111433	0.7044575	4	<U+2581><U+2581><U+2582><U+2581><U+2581><U+2587><U+2581><U+2585>
FU3_AC_136	I like hard work	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	383	0.6433892	1	3	4	3.198263	0.6570001	4	<U+2581><U+2581><U+2582><U+2581><U+2581><U+2587><U+2581><U+2585>
FU3_AC_180	Some people say that I put my work ahead of too many other things	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	383	0.6433892	1	2	4	2.305355	0.8517418	4	<U+2583><U+2581><U+2587><U+2581><U+2581><U+2585><U+2581><U+2582>
FU3_AC_196_R	I am not a terribly ambitious person	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	383	0.6433892	1	3	4	3.109986	0.7572271	4	<U+2581><U+2581><U+2583><U+2581><U+2581><U+2587><U+2581><U+2586>
FU3_AC_213	I push myself to my limits	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	383	0.6433892	1	3	4	2.901592	0.7530693	4	<U+2581><U+2581><U+2585><U+2581><U+2581><U+2587><U+2581><U+2583>
FU3_AC_223	I find it really hard to give up on a project when it proves too difficult	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	383	0.6433892	1	3	4	2.819103	0.7166628	4	<U+2581><U+2581><U+2585><U+2581><U+2581><U+2587><U+2581><U+2582>
FU3_AC_294	I set extremely high standards for myself in my work	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	383	0.6433892	1	3	4	3.338640	0.6710994	4	<U+2581><U+2581><U+2582><U+2581><U+2581><U+2587><U+2581><U+2587>

Scale: AG_3

Overview

Reliability: .

Missing: 384.

Likert plot of scale AG_3 items

Distribution of scale AG_3

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	FU3_AG_22, FU3_AG_66, FU3_AG_82, FU3_AG_97, FU3_AG_112, FU3_AG_127_R, FU3_AG_158, FU3_AG_172, FU3_AG_202, FU3_AG_232, FU3_AG_261 & FU3_AG_293
Observations:	690
Positive correlations:	66
Number of correlations:	66
Percentage positive correlations:	100

Estimates assuming interval level

Omega (total):	0.89
Omega (hierarchical):	0.63
Revelle’s Omega (total):	0.89
Greatest Lower Bound (GLB):	0.90
Coefficient H:	0.87
Coefficient Alpha:	0.85

(Estimates assuming ordinal level not computed, as the polychoric correlation matrix has missing values.)

Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help (‘?ufs::scaleStructure’) for more information.

Eigen values

4.7, 1.68, 0.901, 0.789, 0.697, 0.631, 0.547, 0.505, 0.471, 0.39, 0.361 & 0.329

Factor analysis (reproducing only shared variance)

	ML1	ML2
FU3_AG_22	-0.041	0.813
FU3_AG_66	0.139	0.397
FU3_AG_82	0.467	0.209
FU3_AG_97	0.726	0.034
FU3_AG_112	0.028	0.499
FU3_AG_127_R	-0.042	0.645
FU3_AG_158	0.249	0.444
FU3_AG_172	0.640	0.056
FU3_AG_202	0.705	0.002
FU3_AG_232	0.583	0.024
FU3_AG_261	0.026	0.753
FU3_AG_293	0.852	-0.075

Component analysis (reproducing full covariance matrix)

	TC1	TC2
FU3_AG_22	-0.027	0.826
FU3_AG_66	0.106	0.527
FU3_AG_82	0.554	0.193
FU3_AG_97	0.757	0.044
FU3_AG_112	-0.029	0.643
FU3_AG_127_R	-0.083	0.743
FU3_AG_158	0.231	0.547
FU3_AG_172	0.755	0.013
FU3_AG_202	0.770	-0.019
FU3_AG_232	0.706	-0.022
FU3_AG_261	0.034	0.788
FU3_AG_293	0.850	-0.051

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
FU3_AG_22	2.04347826086957	2	0.581561178772007	0.762601585870373	0	0.0290317462112663	1	1	3	4	0.458435576044647	0.00479368251892833	0.115217391304348	690	690
FU3_AG_66	1.88550724637681	2	0.502111861340737	0.708598519149411	1	0.0269758845966019	1	1	3	4	0.339003856842366	-0.40209970377067	0.152173913043478	690	690
FU3_AG_82	1.57536231884058	1	0.558172945457605	0.74710972785636	1	0.0284419812559647	1	NA	2	4	1.10214746989456	0.458733405988666	0.155072463768116	690	690
FU3_AG_97	1.21159420289855	1	0.268660734944574	0.518324931818424	0	0.0197322929224569	1	NA	2	4	2.73823550357358	8.00464940250659	0.0659420289855072	690	690
FU3_AG_112	2.50144927536232	3	0.717704718032856	0.847174549920414	1	0.0322513839279031	1	2	4	4	-0.299009614155979	-0.600434022519738	0.146376811594203	690	690
FU3_AG_127_R	2.14927536231884	2	0.501632275299215	0.70826003367352	1	0.0269629986747597	1	1	3	4	0.417584533048845	0.2776221239986	0.111594202898551	690	690
FU3_AG_158	1.58695652173913	1	0.533066195494415	0.730113823656569	1	0.0277949582409309	1	NA	2	4	0.862939391736527	-0.467012487240044	0.152898550724638	690	690
FU3_AG_172	1.49710144927536	1	0.502894343829537	0.709150438080339	1	0.0269968957912136	1	NA	2	4	1.27145938871116	0.887105211214288	0.139855072463768	690	690
FU3_AG_202	1.22463768115942	1	0.281830420058476	0.530877029130547	0	0.0202101431005008	1	NA	2	4	2.55203326429971	6.58558600209881	0.0673913043478261	690	690
FU3_AG_232	1.53478260869565	1	0.629412507099135	0.793355221259138	1	0.0302025171016276	1	NA	2	4	1.34591015219631	0.914407292613335	0.116666666666667	690	690
FU3_AG_261	2.00144927536232	2	0.523945646915294	0.723840898896501	0	0.027556152076597	1	1	3	4	0.297182886985964	-0.258245363435322	0.121014492753623	690	690
FU3_AG_293	1.21159420289855	1	0.286077280663007	0.53486192672783	0	0.0203618455593806	1	NA	2	4	2.99033744441651	9.93193431946691	0.0659420289855072	690	690

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
FU3_AG_22	When someone hurts me, I try to retaliate (get even)	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	378	0.6480447	1	2	4	2.045977	0.7629258	4	<U+2583><U+2581><U+2587><U+2581><U+2581><U+2583><U+2581><U+2581>
FU3_AG_66	I see no objection to stepping on people’s toes a little if it is to my advantage	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	378	0.6480447	1	2	4	1.885058	0.7084329	4	<U+2585><U+2581><U+2587><U+2581><U+2581><U+2582><U+2581><U+2581>
FU3_AG_82	When I get angry I am often ready to hit someone	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	378	0.6480447	1	1	4	1.577586	0.7508368	4	<U+2587><U+2581><U+2585><U+2581><U+2581><U+2582><U+2581><U+2581>
FU3_AG_97	I admit that I sometimes take pleasure in hurting someone physically	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	378	0.6480447	1	1	4	1.211207	0.5172598	4	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581>
FU3_AG_112	I can’t help but enjoy it when someone I dislike makes a fool of herself/himself	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	382	0.6443203	1	3	4	2.500000	0.8480846	4	<U+2582><U+2581><U+2585><U+2581><U+2581><U+2587><U+2581><U+2582>
FU3_AG_127_R	I would rather turn the other cheek than get even when someone treats me badly	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	383	0.6433892	1	2	4	2.150507	0.7084862	4	<U+2582><U+2581><U+2587><U+2581><U+2581><U+2583><U+2581><U+2581>
FU3_AG_158	Sometimes I seem to enjoy hurting someone by saying something mean	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	383	0.6433892	1	1	4	1.587554	0.7297537	4	<U+2587><U+2581><U+2585><U+2581><U+2581><U+2582><U+2581><U+2581>
FU3_AG_172	I enjoy a good brawl	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	383	0.6433892	1	1	4	1.497829	0.7088946	4	<U+2587><U+2581><U+2583><U+2581><U+2581><U+2581><U+2581><U+2581>
FU3_AG_202	Sometimes I hit people who have done something to deserve it	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	383	0.6433892	1	1	4	1.225760	0.5313116	4	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581>
FU3_AG_232	I like to watch a good, vicious fight	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	383	0.6433892	1	1	4	1.535456	0.7929776	4	<U+2587><U+2581><U+2583><U+2581><U+2581><U+2582><U+2581><U+2581>
FU3_AG_261	When people insult me, I try to get even	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	384	0.6424581	1	2	4	2.001449	0.7238409	4	<U+2583><U+2581><U+2587><U+2581><U+2581><U+2583><U+2581><U+2581>
FU3_AG_293	Sometimes I just like to hit someone	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	383	0.6433892	1	1	4	1.211288	0.5345348	4	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581>

Scale: CON_3

Overview

Reliability: .

Missing: 384.

Likert plot of scale CON_3 items

Distribution of scale CON_3

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	FU3_CON_26, FU3_CON_51, FU3_CON_64_R, FU3_CON_78, FU3_CON_90, FU3_CON_104_R, FU3_CON_115, FU3_CON_151_R, FU3_CON_162, FU3_CON_228, FU3_CON_239_R & FU3_CON_274
Observations:	690
Positive correlations:	66
Number of correlations:	66
Percentage positive correlations:	100

Estimates assuming interval level

Omega (total):	0.89
Omega (hierarchical):	0.69
Revelle’s Omega (total):	0.89
Greatest Lower Bound (GLB):	0.91
Coefficient H:	0.88
Coefficient Alpha:	0.87

(Estimates assuming ordinal level not computed, as the polychoric correlation matrix has missing values.)

Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help (‘?ufs::scaleStructure’) for more information.

Eigen values

4.966, 1.322, 0.982, 0.844, 0.719, 0.631, 0.518, 0.494, 0.451, 0.413, 0.358 & 0.302

Factor analysis (reproducing only shared variance)

	ML1	ML2
FU3_CON_26	0.761	-0.101
FU3_CON_51	0.810	-0.070
FU3_CON_64_R	-0.055	0.834
FU3_CON_78	0.265	0.221
FU3_CON_90	0.515	0.016
FU3_CON_104_R	0.519	0.221
FU3_CON_115	0.331	0.314
FU3_CON_151_R	0.320	0.546
FU3_CON_162	0.735	0.048
FU3_CON_228	0.493	0.206
FU3_CON_239_R	-0.006	0.710
FU3_CON_274	0.417	0.210

Component analysis (reproducing full covariance matrix)

	TC1	TC2
FU3_CON_26	0.822	-0.137
FU3_CON_51	0.841	-0.072
FU3_CON_64_R	-0.054	0.871
FU3_CON_78	0.265	0.330
FU3_CON_90	0.636	-0.037
FU3_CON_104_R	0.567	0.249
FU3_CON_115	0.359	0.392
FU3_CON_151_R	0.342	0.591
FU3_CON_162	0.768	0.066
FU3_CON_228	0.544	0.249
FU3_CON_239_R	-0.057	0.841
FU3_CON_274	0.430	0.295

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
FU3_CON_26	3.33333333333333	3	0.417029511369134	0.645778221504205	1	0.0245843567373066	1	2	4	4	-0.480439519944098	-0.534357926451001	0.214492753623188	690	690
FU3_CON_51	3.23188405797101	3	0.454134326160577	0.673894892517058	1	0.0256547401095352	1	2	4	4	-0.486430502380994	-0.0747231107823631	0.180434782608696	690	690
FU3_CON_64_R	2.80144927536232	3	0.751521844302812	0.866903595737619	1	0.0330024558660788	1	2	4	4	-0.369031641472353	-0.487537456583609	0.123188405797101	690	690
FU3_CON_78	2.75942028985507	3	0.586449590879451	0.765799967928604	1	0.0291535065352961	1	2	4	4	-0.125637304236758	-0.40755630612324	0.157971014492754	690	690
FU3_CON_90	3.08405797101449	3	0.410921099682379	0.641031278240289	0	0.0244036436956992	1	2	4	4	-0.275225995081794	0.14911645280901	0.121014492753623	690	690
FU3_CON_104_R	2.87101449275362	3	0.617591131865127	0.78586966595303	1	0.029917546881366	1	2	4	4	-0.380469164511571	-0.18460298691952	0.116666666666667	690	690
FU3_CON_115	2.62608695652174	3	0.591481037420332	0.769078043777309	1	0.029278300750079	1	2	4	4	-0.0537125471095791	-0.386925249753563	0.184782608695652	690	690
FU3_CON_151_R	2.67391304347826	3	0.559695841484193	0.748128225295766	1	0.0284807547908294	1	2	4	4	-0.242740796448633	-0.180449450497447	0.158695652173913	690	690
FU3_CON_162	3.14782608695652	3	0.410626617025304	0.640801542620884	1	0.0243948978101387	1	2	4	4	-0.407689972318362	0.461415437013068	0.139130434782609	690	690
FU3_CON_228	2.96086956521739	3	0.455650911844513	0.675019193686012	0	0.0256975415235459	1	2	4	4	-0.350701156198009	0.290755410802721	0.0942028985507246	690	690
FU3_CON_239_R	2.95652173913043	3	0.558339117814097	0.747220929721657	1	0.0284462146386265	1	2	4	4	-0.285275812136594	-0.329507781051488	0.116666666666667	690	690
FU3_CON_274	3.26231884057971	3	0.362148461328117	0.601787721151003	1	0.0229096670099004	1	2	4	4	-0.386156033944519	0.462891147356406	0.169565217391304	690	690

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
FU3_CON_26	When faced with a decision, I usually take time to consider and weigh all aspects	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	378	0.6480447	1	3	4	3.330460	0.6459550	4	<U+2581><U+2581><U+2582><U+2581><U+2581><U+2587><U+2581><U+2587>
FU3_CON_51	I like to stop and think things over before I do them	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	378	0.6480447	1	3	4	3.229885	0.6734624	4	<U+2581><U+2581><U+2582><U+2581><U+2581><U+2587><U+2581><U+2586>
FU3_CON_64_R	I often prefer to “play things by ear” rather than to plan ahead	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	378	0.6480447	1	3	4	2.800287	0.8660170	4	<U+2582><U+2581><U+2585><U+2581><U+2581><U+2587><U+2581><U+2583>
FU3_CON_78	I don’t like to start a project until I know exactly how to proceed	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	378	0.6480447	1	3	4	2.755747	0.7703844	4	<U+2581><U+2581><U+2585><U+2581><U+2581><U+2587><U+2581><U+2582>
FU3_CON_90	I am very level-headed and always like to keep my feet on the ground	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	378	0.6480447	1	3	4	3.083333	0.6405558	4	<U+2581><U+2581><U+2582><U+2581><U+2581><U+2587><U+2581><U+2583>
FU3_CON_104_R	I am more likely to be fast and careless than to be slow and plodding	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	379	0.6471136	1	3	4	2.873381	0.7860982	4	<U+2581><U+2581><U+2583><U+2581><U+2581><U+2587><U+2581><U+2583>
FU3_CON_115	I almost never do anything reckless	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	382	0.6443203	1	3	4	2.625723	0.7684651	4	<U+2581><U+2581><U+2586><U+2581><U+2581><U+2587><U+2581><U+2582>
FU3_CON_151_R	I often act on the spur of the moment	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	383	0.6433892	1	3	4	2.672938	0.7480254	4	<U+2581><U+2581><U+2585><U+2581><U+2581><U+2587><U+2581><U+2582>
FU3_CON_162	I usually make up my mind through careful reasoning	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	383	0.6433892	1	3	4	3.146165	0.6418241	4	<U+2581><U+2581><U+2582><U+2581><U+2581><U+2587><U+2581><U+2583>
FU3_CON_228	I am a cautious person	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	383	0.6433892	1	3	4	2.959479	0.6755196	4	<U+2581><U+2581><U+2582><U+2581><U+2581><U+2587><U+2581><U+2582>
FU3_CON_239_R	I generally do not like to have detailed plans	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	383	0.6433892	1	3	4	2.955138	0.7475654	4	<U+2581><U+2581><U+2583><U+2581><U+2581><U+2587><U+2581><U+2583>
FU3_CON_274	Before I get into a new situation, I like to find out what to expect from it	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	384	0.6424581	1	3	4	3.262319	0.6017877	4	<U+2581><U+2581><U+2581><U+2581><U+2581><U+2587><U+2581><U+2585>

Scale: HA_3

Overview

Reliability: .

Missing: 385.

Likert plot of scale HA_3 items

Distribution of scale HA_3

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	FU3_HA_119, FU3_HA_33_R, FU3_HA_77_R, FU3_HA_106_R, FU3_HA_139, FU3_HA_149_R, FU3_HA_160, FU3_HA_171_R, FU3_HA_183, FU3_HA_225, FU3_HA_259 & FU3_HA_290_R
Observations:	689
Positive correlations:	66
Number of correlations:	66
Percentage positive correlations:	100

Estimates assuming interval level

Omega (total):	0.83
Omega (hierarchical):	0.61
Revelle’s Omega (total):	0.83
Greatest Lower Bound (GLB):	0.81
Coefficient H:	0.83
Coefficient Alpha:	0.80

(Estimates assuming ordinal level not computed, as the polychoric correlation matrix has missing values.)

Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help (‘?ufs::scaleStructure’) for more information.

Eigen values

3.933, 1.213, 0.966, 0.894, 0.841, 0.744, 0.715, 0.65, 0.617, 0.543, 0.499 & 0.387

Factor analysis (reproducing only shared variance)

	ML1	ML2
FU3_HA_119	0.021	0.558
FU3_HA_33_R	0.441	0.297
FU3_HA_77_R	0.740	0.064
FU3_HA_106_R	0.258	0.122
FU3_HA_139	0.224	0.467
FU3_HA_149_R	0.509	0.120
FU3_HA_160	0.451	0.204
FU3_HA_171_R	0.737	-0.182
FU3_HA_183	0.187	0.373
FU3_HA_225	0.360	0.185
FU3_HA_259	-0.091	0.544
FU3_HA_290_R	0.371	0.117

Component analysis (reproducing full covariance matrix)

	TC1	TC2
FU3_HA_119	0.063	0.714
FU3_HA_33_R	0.523	0.307
FU3_HA_77_R	0.762	0.054
FU3_HA_106_R	0.437	-0.006
FU3_HA_139	0.343	0.485
FU3_HA_149_R	0.654	0.022
FU3_HA_160	0.611	0.123
FU3_HA_171_R	0.779	-0.247
FU3_HA_183	0.294	0.417
FU3_HA_225	0.526	0.097
FU3_HA_259	-0.110	0.774
FU3_HA_290_R	0.475	0.088

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
FU3_HA_119	3.39767779390421	4	0.914296925102103	0.956188749725755	1	0.0364278901807656	1	2	NA	4	-1.36693465252535	0.543837675881004	0.0732946298984035	689	689
FU3_HA_33_R	3.06676342525399	3	0.905419887264995	0.951535541777077	2	0.0362506170762752	1	2	4	4	-0.570154227602216	-0.839482836829866	0.13933236574746	689	689
FU3_HA_77_R	3.09143686502177	3	1.07738296148783	1.03797059760276	2	0.0395435304495913	1	2	4	4	-0.731089759764765	-0.796404092912521	0.110304789550073	689	689
FU3_HA_106_R	2.69811320754717	3	1.37966213251426	1.17459019769205	2	0.0447483226938216	1	1	4	4	-0.254912095914221	-1.43169400025339	0.115384615384615	689	689
FU3_HA_139	3.3933236574746	4	0.820362338407534	0.905738559633813	1	0.0345058910097911	1	3	NA	4	-1.36331057195	0.777537949367879	0.106676342525399	689	689
FU3_HA_149_R	2.88243831640058	3	0.981798697134371	0.99085755642997	2	0.0377486665271528	1	2	4	4	-0.410048614082369	-0.938101478313941	0.159651669085631	689	689
FU3_HA_160	2.58925979680697	3	1.30633796874473	1.14295142886508	2	0.0435429815970829	1	2	4	4	-0.0622739067836462	-1.42119924773024	0.131349782293179	689	689
FU3_HA_171_R	2.7155297532656	3	0.866633476221015	0.930931509951734	1	0.0354656659786704	1	2	4	4	-0.0782330188096231	-0.957988541353438	0.161828737300435	689	689
FU3_HA_183	3.11611030478955	4	1.14928949944308	1.0720492057005	2	0.0408418220198005	1	2	NA	4	-0.814589249712128	-0.748985183127257	0.0979680696661829	689	689
FU3_HA_225	3.11320754716981	3	1.06856077226854	1.03371213220535	2	0.0393812958386112	1	2	4	4	-0.805914320434937	-0.65051408876702	0.119013062409289	689	689
FU3_HA_259	3.25253991291727	4	0.898340196442434	0.947808101063941	1	0.0361086128945774	1	3	NA	4	-1.01583647037951	-0.109682603021708	0.124092888243832	689	689
FU3_HA_290_R	2.9622641509434	3	1.0857832382624	1.04200923137101	2	0.0396973901424942	1	2	4	4	-0.558396960712094	-0.948351312795712	0.135703918722787	689	689

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
FU3_HA_119	Of the following two situations I would dislike more: (A) Having a pilot announce that the plane has engine trouble and he may have to make an emergency landing. (B) Working in a field digging potatoes.	haven_labelled	4. Definitely A, 3. Probably A, 2. Probably B, 1. Definitely B	383	0.6433892	1	4	4	3.399421	0.9553509	4	<U+2581><U+2581><U+2582><U+2581><U+2581><U+2582><U+2581><U+2587>
FU3_HA_33_R	It might be fun and exciting to experience an earthquake	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	378	0.6480447	1	3	4	3.068966	0.9495850	4	<U+2581><U+2581><U+2585><U+2581><U+2581><U+2585><U+2581><U+2587>
FU3_HA_77_R	I might enjoy riding in an open elevator to the top of a tall building under construction	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	378	0.6480447	1	3	4	3.094828	1.0358616	4	<U+2582><U+2581><U+2583><U+2581><U+2581><U+2583><U+2581><U+2587>
FU3_HA_106_R	Of the following two situations I would dislike more: (A) Having to walk around all day on a blistered foot. (B) Sleeping out on a camping trip in an area where there are rattlesnakes.	haven_labelled	1. Definitely A, 2. Probably A, 3. Probably B, 4. Definitely B	378	0.6480447	1	3	4	2.702586	1.1724876	4	<U+2585><U+2581><U+2585><U+2581><U+2581><U+2585><U+2581><U+2587>
FU3_HA_139	Of the following two situations I would dislike more: (A) Being out on a sailboat during a great storm at sea. (B) Having to stay home every night for two weeks with a sick relative.	haven_labelled	4. Definitely A, 3. Probably A, 2. Probably B, 1. Definitely B	383	0.6433892	1	4	4	3.395080	0.9050128	4	<U+2581><U+2581><U+2581><U+2581><U+2581><U+2583><U+2581><U+2587>
FU3_HA_149_R	I would enjoy trying to cross the ocean in a small but seaworthy sailboat	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	383	0.6433892	1	3	4	2.878437	0.9925729	4	<U+2582><U+2581><U+2586><U+2581><U+2581><U+2587><U+2581><U+2587>
FU3_HA_160	Of the following two situations I would dislike more: (A) Riding a long stretch of rapids in a canoe. (B) Waiting for someone who’s late.	haven_labelled	4. Definitely A, 3. Probably A, 2. Probably B, 1. Definitely B	383	0.6433892	1	3	4	2.589001	1.1441574	4	<U+2586><U+2581><U+2587><U+2581><U+2581><U+2586><U+2581><U+2587>
FU3_HA_171_R	It might be fun learning to walk a tightrope	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	383	0.6433892	1	3	4	2.714906	0.9331546	4	<U+2582><U+2581><U+2587><U+2581><U+2581><U+2587><U+2581><U+2586>
FU3_HA_183	Of the following two situations I would dislike more: (A) Being in the circus when two lions suddenly get loose down in the ring. (B) Bringing my whole family to the circus and then not being able to get in because a clerk sold me tickets for the wrong night.	haven_labelled	4. Definitely A, 3. Probably A, 2. Probably B, 1. Definitely B	383	0.6433892	1	4	4	3.118669	1.0715485	4	<U+2582><U+2581><U+2582><U+2581><U+2581><U+2583><U+2581><U+2587>
FU3_HA_225	Of the following two situations I would dislike more: (A) Being chosen as the “target” for a knife-throwing act. (B) Being sick to my stomach for 24 hours.	haven_labelled	4. Definitely A, 3. Probably A, 2. Probably B, 1. Definitely B	383	0.6433892	1	3	4	3.111433	1.0358919	4	<U+2582><U+2581><U+2583><U+2581><U+2581><U+2583><U+2581><U+2587>
FU3_HA_259	Of the following two situations I would dislike more: (A) Being in a flood. (B) Carrying a ton of coal from the backyard into the basement.	haven_labelled	4. Definitely A, 3. Probably A, 2. Probably B, 1. Definitely B	383	0.6433892	1	4	4	3.254703	0.9472861	4	<U+2581><U+2581><U+2582><U+2581><U+2581><U+2583><U+2581><U+2587>
FU3_HA_290_R	Of the following two situations I would dislike more: (A) Being seasick every day for a week while on an ocean voyage. (B) Having to stand on the ledge of the 25th floor of a hotel because there’s a fire in my room.	haven_labelled	1. Definitely A, 2. Probably A, 3. Probably B, 4. Definitely B	384	0.6424581	1	3	4	2.962319	1.0412538	4	<U+2582><U+2581><U+2585><U+2581><U+2581><U+2586><U+2581><U+2587>

Scale: SP_3

Overview

Reliability: .

Missing: 386.

Likert plot of scale SP_3 items

Distribution of scale SP_3

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	FU3_SP_1, FU3_SP_25, FU3_SP_47_R, FU3_SP_94, FU3_SP_105, FU3_SP_129, FU3_SP_150_R, FU3_SP_187_R, FU3_SP_218_R, FU3_SP_233, FU3_SP_257_R & FU3_SP_278
Observations:	688
Positive correlations:	66
Number of correlations:	66
Percentage positive correlations:	100

Estimates assuming interval level

Omega (total):	0.90
Omega (hierarchical):	0.70
Revelle’s Omega (total):	0.90
Greatest Lower Bound (GLB):	0.91
Coefficient H:	0.89
Coefficient Alpha:	0.87

(Estimates assuming ordinal level not computed, as the polychoric correlation matrix has missing values.)

Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help (‘?ufs::scaleStructure’) for more information.

Eigen values

5.061, 1.35, 1.105, 0.847, 0.764, 0.615, 0.539, 0.476, 0.391, 0.32, 0.281 & 0.25

Factor analysis (reproducing only shared variance)

	ML1	ML2	ML3
FU3_SP_1	0.025	0.083	0.690
FU3_SP_25	0.042	0.779	0.025
FU3_SP_47_R	-0.003	0.442	0.345
FU3_SP_94	0.897	-0.001	-0.061
FU3_SP_105	0.773	0.050	0.029
FU3_SP_129	0.148	0.017	0.345
FU3_SP_150_R	-0.007	0.925	-0.047
FU3_SP_187_R	-0.078	-0.034	0.508
FU3_SP_218_R	0.085	0.497	0.151
FU3_SP_233	0.799	-0.024	0.051
FU3_SP_257_R	0.483	0.089	0.092
FU3_SP_278	0.252	-0.096	0.474

Component analysis (reproducing full covariance matrix)

	TC1	TC2	TC3
FU3_SP_1	0.201	0.246	0.541
FU3_SP_25	0.059	0.815	-0.037
FU3_SP_47_R	-0.038	0.727	0.219
FU3_SP_94	0.876	0.013	-0.036
FU3_SP_105	0.807	0.080	0.001
FU3_SP_129	0.334	-0.010	0.363
FU3_SP_150_R	0.009	0.883	-0.060
FU3_SP_187_R	-0.145	0.040	0.821
FU3_SP_218_R	0.024	0.776	-0.010
FU3_SP_233	0.879	-0.024	0.013
FU3_SP_257_R	0.637	0.111	-0.017
FU3_SP_278	0.391	-0.109	0.572

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
FU3_SP_1	2.80087209302326	3	0.686636792931857	0.82863550064661	1	0.0315914322938625	1	2	4	4	-0.30730213194921	-0.427236397615996	0.132994186046512	688	688
FU3_SP_25	2.17732558139535	2	0.833138688602282	0.912764311639254	2	0.0347988131439026	1	1	3	4	0.298854321442459	-0.77307838201555	0.135901162790698	688	688
FU3_SP_47_R	2.25145348837209	2	0.680492789682137	0.824919868643092	1	0.0314497751517579	1	1	3	4	0.268898622043073	-0.429161647657731	0.14171511627907	688	688
FU3_SP_94	2.82267441860465	3	0.509994583798788	0.714139050744873	1	0.0272262960643191	1	2	4	4	-0.279686821003913	-0.011276133239418	0.129360465116279	688	688
FU3_SP_105	2.70639534883721	3	0.580337497038015	0.761798856023042	1	0.0290433091061319	1	2	4	4	-0.143354537039903	-0.328809883343347	0.163517441860465	688	688
FU3_SP_129	2.07558139534884	2	0.58525439220067	0.765019210347472	1	0.0291660839637419	1	1	3	4	0.262591359671376	-0.407338601723174	0.12281976744186	688	688
FU3_SP_150_R	2.20639534883721	2	0.752098777969602	0.867236287276773	1	0.033063073487566	1	1	3	4	0.299966754817856	-0.578091441728165	0.134447674418605	688	688
FU3_SP_187_R	2.51889534883721	3	0.742000524694492	0.861394523255455	1	0.0328403583221981	1	2	4	4	-0.051734587843657	-0.643169687273775	0.180232558139535	688	688
FU3_SP_218_R	2.32412790697674	2	0.577466487255001	0.759912157591258	1	0.028971379402758	1	1	3	4	0.0392830269097841	-0.406262908025214	0.179505813953488	688	688
FU3_SP_233	2.69912790697674	3	0.484307826410751	0.695922284749347	1	0.0265317883717188	1	2	4	4	-0.372253212196375	0.124600577668673	0.146802325581395	688	688
FU3_SP_257_R	2.55523255813953	3	0.523873599404218	0.72379112968053	1	0.0275942781239254	1	2	4	4	-0.158817824476026	-0.228176703616517	0.191133720930233	688	688
FU3_SP_278	2.85901162790698	3	0.456075877593853	0.675333900817849	1	0.0257468635929658	1	2	4	4	-0.277494410993033	0.151835151458169	0.119186046511628	688	688

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
FU3_SP_1	When I work on a committee, I like to take charge of things	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	379	0.6471136	1	3	4	2.801439	0.8286986	4	<U+2581><U+2581><U+2585><U+2581><U+2581><U+2587><U+2581><U+2583>
FU3_SP_25	I like to be in the spotlight	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	378	0.6480447	1	2	4	2.173851	0.9119227	4	<U+2586><U+2581><U+2587><U+2581><U+2581><U+2586><U+2581><U+2582>
FU3_SP_47_R	I usually prefer to let someone else take the lead on social occasions	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	378	0.6480447	1	2	4	2.250000	0.8262771	4	<U+2583><U+2581><U+2587><U+2581><U+2581><U+2585><U+2581><U+2581>
FU3_SP_94	I am quite effective at talking people into things	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	379	0.6471136	1	3	4	2.817266	0.7160096	4	<U+2581><U+2581><U+2583><U+2581><U+2581><U+2587><U+2581><U+2582>
FU3_SP_105	I have a natural talent for influencing people	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	379	0.6471136	1	3	4	2.703597	0.7619755	4	<U+2581><U+2581><U+2586><U+2581><U+2581><U+2587><U+2581><U+2582>
FU3_SP_129	People consider me forceful	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	383	0.6433892	1	2	4	2.075253	0.7633705	4	<U+2583><U+2581><U+2587><U+2581><U+2581><U+2583><U+2581><U+2581>
FU3_SP_150_R	I do not like to be the center of attention on a social occasion	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	383	0.6433892	1	2	4	2.206946	0.8676193	4	<U+2583><U+2581><U+2587><U+2581><U+2581><U+2585><U+2581><U+2582>
FU3_SP_187_R	I do not like to organize other people’s activities	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	383	0.6433892	1	3	4	2.518090	0.8601684	4	<U+2582><U+2581><U+2587><U+2581><U+2581><U+2587><U+2581><U+2582>
FU3_SP_218_R	On social occasions I usually allow others to dominate the conversation	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	383	0.6433892	1	2	4	2.322721	0.7604664	4	<U+2582><U+2581><U+2587><U+2581><U+2581><U+2586><U+2581><U+2581>
FU3_SP_233	I am quite good at convincing others to see things my way	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	383	0.6433892	1	3	4	2.698987	0.6951064	4	<U+2581><U+2581><U+2585><U+2581><U+2581><U+2587><U+2581><U+2581>
FU3_SP_257_R	I don’t enjoy trying to convince people of something	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	383	0.6433892	1	3	4	2.552822	0.7251407	4	<U+2581><U+2581><U+2586><U+2581><U+2581><U+2587><U+2581><U+2581>
FU3_SP_278	People seem naturally to turn to me when decisions have to be made	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	385	0.6415270	1	3	4	2.859216	0.6748643	4	<U+2581><U+2581><U+2583><U+2581><U+2581><U+2587><U+2581><U+2582>

Scale: TR_3

Overview

Reliability: .

Missing: 395.

Likert plot of scale TR_3 items

Distribution of scale TR_3

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	FU3_TR_9, FU3_TR_63, FU3_TR_89, FU3_TR_100_R, FU3_TR_167, FU3_TR_177, FU3_TR_199, FU3_TR_230, FU3_TR_253, FU3_TR_262, FU3_TR_275_R & FU3_TR_285
Observations:	679
Positive correlations:	66
Number of correlations:	66
Percentage positive correlations:	100

Estimates assuming interval level

Omega (total):	0.81
Omega (hierarchical):	0.57
Revelle’s Omega (total):	0.81
Greatest Lower Bound (GLB):	0.81
Coefficient H:	0.82
Coefficient Alpha:	0.76

(Estimates assuming ordinal level not computed, as the polychoric correlation matrix has missing values.)

Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help (‘?ufs::scaleStructure’) for more information.

Eigen values

3.627, 1.642, 1.023, 0.96, 0.798, 0.7, 0.663, 0.608, 0.575, 0.498, 0.486 & 0.42

Factor analysis (reproducing only shared variance)

	ML1	ML2	ML3
FU3_TR_9	-0.053	0.682	0.086
FU3_TR_63	0.001	0.605	-0.155
FU3_TR_89	0.686	-0.027	-0.047
FU3_TR_100_R	0.454	-0.078	0.130
FU3_TR_167	0.198	0.510	-0.040
FU3_TR_177	0.547	-0.095	0.265
FU3_TR_199	-0.052	0.295	0.414
FU3_TR_230	0.074	0.155	-0.059
FU3_TR_253	0.740	0.023	-0.075
FU3_TR_262	0.245	0.448	-0.082
FU3_TR_275_R	0.625	0.193	-0.006
FU3_TR_285	0.008	0.676	0.090

Component analysis (reproducing full covariance matrix)

	TC1	TC2	TC3
FU3_TR_9	0.717	-0.058	0.238
FU3_TR_63	0.718	-0.028	-0.104
FU3_TR_89	0.050	0.736	-0.139
FU3_TR_100_R	-0.156	0.629	0.171
FU3_TR_167	0.603	0.203	-0.004
FU3_TR_177	-0.164	0.700	0.328
FU3_TR_199	0.233	-0.024	0.763
FU3_TR_230	0.352	-0.008	-0.415
FU3_TR_253	0.137	0.736	-0.171
FU3_TR_262	0.577	0.231	-0.103
FU3_TR_275_R	0.284	0.648	-0.071
FU3_TR_285	0.710	0.019	0.194

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
FU3_TR_9	2.98821796759941	3	0.457088117611792	0.676082922141798	0	0.0259456812678585	1	2	4	4	-0.445393866582805	0.528951415176668	0.0994108983799705	679	679
FU3_TR_63	2.91310751104566	3	0.516037379279784	0.71835741750175	0	0.0275680275015041	1	2	4	4	-0.324630672125084	-0.00233752835409477	0.110456553755523	679	679
FU3_TR_89	2.14874815905744	2	0.740378224093214	0.860452336909613	1	0.0330211300248736	1	1	3	4	0.350074227877342	-0.536718618645566	0.125920471281296	679	679
FU3_TR_100_R	1.96170839469809	2	0.691746929590192	0.831713249618035	1	0.0319182250787847	1	1	3	4	0.565438328003696	-0.265721733651177	0.159057437407953	679	679
FU3_TR_167	3.04270986745214	3	0.421477011569156	0.6492126089111	0	0.0249144932880725	1	2	4	4	-0.463133440713435	0.793873765709892	0.106774668630339	679	679
FU3_TR_177	1.76730486008837	2	0.644888153235932	0.803049284437719	1	0.0308182030547326	1	1	3	4	0.890586056019886	0.321983923959152	0.20839469808542	679	679
FU3_TR_199	3.19440353460972	3	0.590470108306072	0.768420528295589	1	0.0294892733626176	1	2	4	4	-0.679671422087197	-0.0242276157558056	0.192930780559647	679	679
FU3_TR_230	2.45508100147275	3	0.915014705818465	0.956564010309015	1	0.0367095575275851	1	2	4	4	-0.15542541911487	-0.972282920028088	0.12739322533137	679	679
FU3_TR_253	1.92341678939617	2	0.7168402257354	0.846664175299392	2	0.0324919889466236	1	1	3	4	0.453267507351967	-0.749261467918817	0.184094256259205	679	679
FU3_TR_262	2.45066273932253	2	0.581264309391305	0.762406918509601	1	0.0292584922000314	1	1	3	4	-0.123381884056153	-0.395542047686182	0.201030927835052	679	679
FU3_TR_275_R	2.46539027982327	3	0.67689774568709	0.822737956877577	1	0.0315737849559785	1	2	4	4	-0.104113441837446	-0.549299187060449	0.184094256259205	679	679
FU3_TR_285	3.07216494845361	3	0.497734391630934	0.705502935239063	1	0.0270747177480283	1	2	4	4	-0.456290108635511	0.168317595924338	0.133284241531664	679	679

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
FU3_TR_9	The best way to achieve a peaceful world is to improve people’s morals	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	378	0.6480447	1	3	4	2.984195	0.6836489	4	<U+2581><U+2581><U+2582><U+2581><U+2581><U+2587><U+2581><U+2582>
FU3_TR_63	Higher standards of conduct are what this country needs most	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	378	0.6480447	1	3	4	2.910919	0.7241736	4	<U+2581><U+2581><U+2583><U+2581><U+2581><U+2587><U+2581><U+2583>
FU3_TR_89	I would prefer to see: (A) Stricter observance of the Sabbath, (B) Greater freedom in regard to divorce.	haven_labelled	4. Definitely A, 3. Probably A, 2. Probably B, 1. Definitely B	381	0.6452514	1	2	4	2.157287	0.8667390	4	<U+2585><U+2581><U+2587><U+2581><U+2581><U+2585><U+2581><U+2581>
FU3_TR_100_R	More censorship of books and movies is a violation of free speech and should be abolished	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	379	0.6471136	1	2	4	1.969784	0.8405822	4	<U+2586><U+2581><U+2587><U+2581><U+2581><U+2583><U+2581><U+2581>
FU3_TR_167	People should observe moral laws more strictly than they do	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	383	0.6433892	1	3	4	3.034732	0.6584638	4	<U+2581><U+2581><U+2582><U+2581><U+2581><U+2587><U+2581><U+2583>
FU3_TR_177	I am disgusted by foul language	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	383	0.6433892	1	2	4	1.774240	0.8100648	4	<U+2587><U+2581><U+2587><U+2581><U+2581><U+2582><U+2581><U+2581>
FU3_TR_199	No decent person could ever think of hurting a close friend or relative	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	384	0.6424581	1	3	4	3.192754	0.7670309	4	<U+2581><U+2581><U+2582><U+2581><U+2581><U+2587><U+2581><U+2587>
FU3_TR_230	It is a pretty callous (unfeeling) person who does not feel love and gratitude toward her/his parents	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	384	0.6424581	1	3	4	2.452174	0.9569255	4	<U+2585><U+2581><U+2585><U+2581><U+2581><U+2587><U+2581><U+2582>
FU3_TR_253	I don’t like to see religious authority overturned by so-called progress and logical reasoning	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	387	0.6396648	1	2	4	1.927220	0.8489069	4	<U+2587><U+2581><U+2587><U+2581><U+2581><U+2585><U+2581><U+2581>
FU3_TR_262	Strict discipline in the home would prevent much of the crime in our society	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	385	0.6415270	1	2	4	2.457184	0.7634329	4	<U+2582><U+2581><U+2587><U+2581><U+2581><U+2587><U+2581><U+2581>
FU3_TR_275_R	I am not at all sorry to see many of the traditional values change	haven_labelled	1. Definitely True, 2. Probably True, 3. Probably False, 4. Definitely False	384	0.6424581	1	3	4	2.462319	0.8255009	4	<U+2582><U+2581><U+2587><U+2581><U+2581><U+2587><U+2581><U+2582>
FU3_TR_285	High moral standards are the most important thing parents can teach their children	haven_labelled	4. Definitely True, 3. Probably True, 2. Probably False, 1. Definitely False	384	0.6424581	1	3	4	3.073913	0.7099034	4	<U+2581><U+2581><U+2582><U+2581><U+2581><U+2587><U+2581><U+2583>

Codebook SIBS 8282

Linh Nguyen

08-Dec-2020

Metadata

Description

Variables

IDSEX

Distribution

Summary statistics

Value labels

IDAB

Distribution

Summary statistics

Value labels

IDFAMAB

Distribution

Summary statistics

Value labels

IN_MPQ_AGE

Distribution

Summary statistics

FU1_MPQ_AGE

Distribution

Summary statistics

FU3_MPQ_AGE

Distribution

Summary statistics

IN_NCDATE

Distribution

Summary statistics

FU1_NCDATE

Distribution

Summary statistics

FU3_NCDATE

Distribution

Summary statistics

Scale: AC_1

Overview

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Estimates assuming interval level

Eigen values

Factor analysis (reproducing only shared variance)

Component analysis (reproducing full covariance matrix)

Item descriptives

Scattermatrix

Summary statistics

Scale: AG_1

Overview

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Estimates assuming interval level

Eigen values

Factor analysis (reproducing only shared variance)

Component analysis (reproducing full covariance matrix)

Item descriptives

Scattermatrix

Summary statistics

Scale: CON_1

Overview

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Estimates assuming interval level

Eigen values

Factor analysis (reproducing only shared variance)

Component analysis (reproducing full covariance matrix)

Item descriptives

Scattermatrix

Summary statistics

Scale: HA_1

Overview