OS Culture Codebook

age

What is your age?

Distribution

Distribution of values for age

109 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
age	What is your age?	haven_labelled	109	0.7061995	2	3.5	7	3.751908	1.149503	7	<U+2582><U+2587><U+2581><U+2585><U+2583><U+2581><U+2582><U+2581>

Value labels

Response choices
name	value
18-22	1
23-29	2
30-39	3
40-49	4
50-59	5
60-69	6
70+	7

gender_f

Gender Coded as Factor

Distribution

Distribution of values for gender_f

119 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
gender_f	Gender Coded as Factor	haven_labelled	119	0.6792453	1	1	2	1.313492	0.4648357	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2583>

Value labels

Response choices
name	value
female	1
male	2

race_f

Race/Ethnicity Coded as Factor

Distribution

Distribution of values for race_f

122 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
race_f	Race/Ethnicity Coded as Factor	haven_labelled	122	0.671159	1	5	6	3.586345	1.732509	6	<U+2583><U+2582><U+2581><U+2583><U+2581><U+2581><U+2587><U+2581>

Value labels

Response choices
name	value
Asian	1
Black	2
Hispanic	3
Native American	4
Non-Hispanic White	5
Mixed	6

continent

In which continent do you primarily live and work?

Distribution

Distribution of values for continent

109 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
continent	In which continent do you primarily live and work?	haven_labelled	109	0.7061995	1	5	6	4.885496	0.5272821	6	<U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2587><U+2581>

Value labels

Response choices
name	value
Africa	1
Asia	2
Australia/Oceania	3
Europe	4
North America	5
South America	6

career

What is your career stage?

Distribution

Distribution of values for career

110 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
career	What is your career stage?	haven_labelled	110	0.703504	2	5	7	4.375479	1.148918	7	<U+2582><U+2581><U+2581><U+2585><U+2587><U+2581><U+2581><U+2581>

Value labels

Response choices
name	value
Undergraduate student	1
Graduate student	2
Post-doctoral fellow	3
Assistant professor/lecturer	4
Associate/full professor	5
Research scientist	6
Other	7

career_o

What is your career stage? - Text

Distribution

Distribution of values for career_o

361 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
career_o	What is your career stage? - Text	character	361	0.0269542	10	0	12	88	0

Scale: lead

Overview

Reliability: .

Missing: 0.

Likert plot of scale lead items

Distribution of scale lead

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	lead_1, lead_2 & lead_3
Observations:	371
Positive correlations:	3
Number of correlations:	3
Percentage positive correlations:	100

Estimates assuming interval level

Omega (total):	0.53
Omega (hierarchical):	0.09
Revelle’s Omega (total):	0.53
Greatest Lower Bound (GLB):	0.53
Coefficient H:	0.53
Coefficient Alpha:	0.51

(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

1.53, 0.785 & 0.685

Factor analysis (reproducing only shared variance)

	ML1
lead_1	0.531
lead_2	0.588
lead_3	0.429

Component analysis (reproducing full covariance matrix)

	PC1
lead_1	0.727
lead_2	0.746
lead_3	0.667

Item descriptives

	mean	var	sd	se	q1	q3	max	skew	kurt	dip	n	valid
lead_1	0.202156334231806	0.161725067385445	0.402150553133332	0.0208786164216033	NA	1	1	1.48928301725181	0.219116000942618	0.101078167115903	371	371
lead_2	0.134770889487871	0.116922852771909	0.341939837942158	0.017752631844056	NA	1	1	2.1477969592349	2.62716546141488	0.0673854447439353	371	371
lead_3	0.245283018867925	0.185619581845997	0.430835910580811	0.0223678859759932	NA	1	1	1.18884036676685	-0.589867648258422	0.122641509433962	371	371

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	complete_rate	max	mean	sd	n_value_labels	hist
lead_1	Leadership position - Your institution	haven_labelled	0. No, 1. Yes	1	1	0.2021563	0.4021506	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2582>
lead_2	Leadership position - Journal editorialship	haven_labelled	0. No, 1. Yes	1	1	0.1347709	0.3419398	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581>
lead_3	Leadership position - Professional societies	haven_labelled	0. No, 1. Yes	1	1	0.2452830	0.4308359	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2582>

culture

Do you consider any of your work to be in the subfield of cultural/ethnic minority psychology?

Distribution

Distribution of values for culture

108 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
culture	Do you consider any of your work to be in the subfield of cultural/ethnic minority psychology?	haven_labelled	108	0.7088949	0	1	1	0.8707224	0.3361466	2	<U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2587>

Value labels

Response choices
name	value
No	0
Yes	1

politics

Which of the following best describes how you would label your political views?

Distribution

Distribution of values for politics

111 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
politics	Which of the following best describes how you would label your political views?	haven_labelled	111	0.7008086	1	2	7	2.161538	1.053062	7	<U+2583><U+2587><U+2582><U+2581><U+2581><U+2581><U+2581><U+2581>

Value labels

Response choices
name	value
Extremely liberal	1
Liberal	2
Slightly liberal	3
Moderate	4
Sligthly conservative	5
Conservative	6
Extremely conservative	7

c19stress

Your current level of stress associated with the COVID-19/coronavirus pandemic

Distribution

Distribution of values for c19stress

108 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
c19stress	Your current level of stress associated with the COVID-19/coronavirus pandemic	haven_labelled	108	0.7088949	1	6	10	6.140684	2.161243	2	<U+2582><U+2583><U+2585><U+2585><U+2586><U+2587><U+2586><U+2586>

Value labels

Response choices
name	value
Low stress	1
High stress	10

group

Recruitment method

Distribution

Distribution of values for group

19 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
group	Recruitment method	haven_labelled	19	0.9487871	1	1	2	1.448864	0.4980862	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2586>

Value labels

Response choices
name	value
Flat	1
Raffle	2

Scale: agree

Overview

Reliability: .

Missing: 109.

Likert plot of scale agree items

Distribution of scale agree

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	tipi_2 & tipi_7
Observations:	262
Positive correlations:	1
Number of correlations:	1
Percentage positive correlations:	100

Estimates assuming interval level

Estimates for two-item measures

Spearman Brown coefficient:	0.50
Coefficient Alpha:	0.49
Pearson Correlation:	0.33

Eigen values

1.333 & 0.667

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	NA	valid
tipi_2	3.66793893129771	4	1.10387236407242	1.05065330346048	2	0.0649095778601766	1	3	5	5	-0.320898701284228	-0.926856876813772	0.125954198473282	262	0	262
tipi_7	4.08778625954198	4	0.762378988622737	0.8731431661662	1	0.0539429649539744	1	3	5	5	-1.07637518489251	1.45049393172587	0.17175572519084	262	0	262

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
tipi_2	I see myself as critical, quarrelsome	haven_labelled	5. Strongly disagree, 3. Neither agree nor disagree, 1. Strongly agree	109	0.7061995	1	4	5	3.667939	1.0506533	3	<U+2581><U+2583><U+2581><U+2586><U+2581><U+2587><U+2581><U+2586>
tipi_7	I see myself as sympathetic, warm	haven_labelled	1. Strongly disagree, 3. Neither agree nor disagree, 5. Strongly agree	108	0.7088949	1	4	5	4.087453	0.8714921	3	<U+2581><U+2581><U+2581><U+2582><U+2581><U+2587><U+2581><U+2586>

Scale: consci

Overview

Reliability: .

Missing: 108.

Likert plot of scale consci items

Distribution of scale consci

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	tipi_3 & tipi_8
Observations:	263
Positive correlations:	1
Number of correlations:	1
Percentage positive correlations:	100

Estimates assuming interval level

Estimates for two-item measures

Spearman Brown coefficient:	0.69
Coefficient Alpha:	0.69
Pearson Correlation:	0.53

Eigen values

1.526 & 0.474

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	NA	valid
tipi_3	4.24714828897338	4	0.812730386323397	0.901515605146909	1	0.0555898336550163	1	3	5	5	-1.42175030435064	2.06014744280001	0.199619771863118	263	0	263
tipi_8	4.13688212927757	4	0.935390241778655	0.967155748459706	1	0.0596373782865429	1	3	5	5	-0.91536446439323	-0.0699099394997029	0.159695817490494	263	0	263

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
tipi_3	I see myself as dependable, self-disciplined	haven_labelled	1. Strongly disagree, 3. Neither agree nor disagree, 5. Strongly agree	108	0.7088949	1	4	5	4.247148	0.9015156	3	<U+2581><U+2581><U+2581><U+2581><U+2581><U+2587><U+2581><U+2587>
tipi_8	I see myself as disorganized, careless	haven_labelled	5. Strongly disagree, 3. Neither agree nor disagree, 1. Strongly agree	108	0.7088949	1	4	5	4.136882	0.9671557	3	<U+2581><U+2582><U+2581><U+2582><U+2581><U+2586><U+2581><U+2587>

Scale: extra

Overview

Reliability: .

Missing: 108.

Likert plot of scale extra items

Distribution of scale extra

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	tipi_1 & tipi_6
Observations:	263
Positive correlations:	1
Number of correlations:	1
Percentage positive correlations:	100

Estimates assuming interval level

Estimates for two-item measures

Spearman Brown coefficient:	0.81
Coefficient Alpha:	0.81
Pearson Correlation:	0.69

Eigen values

1.686 & 0.314

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	NA	valid
tipi_1	3.1787072243346	3	1.42214030708501	1.19253524354	2	0.0735348733151771	1	2	4	5	-0.200154756935808	-0.855782690259789	0.134980988593156	263	0	263
tipi_6	2.95437262357414	3	1.3719559980263	1.17130525399073	2	0.072225776078475	1	2	4	5	0.0890981604474295	-0.888746821318586	0.134980988593156	263	0	263

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
tipi_1	I see myself as extraverted, enthusiastic	haven_labelled	1. Strongly disagree, 3. Neither agree nor disagree, 5. Strongly agree	108	0.7088949	1	3	5	3.178707	1.192535	3	<U+2583><U+2586><U+2581><U+2587><U+2581><U+2587><U+2581><U+2583>
tipi_6	I see myself as reserved, quiet	haven_labelled	5. Strongly disagree, 3. Neither agree nor disagree, 1. Strongly agree	108	0.7088949	1	3	5	2.954373	1.171305	3	<U+2583><U+2587><U+2581><U+2587><U+2581><U+2587><U+2581><U+2583>

Scale: neuro

Overview

Reliability: .

Missing: 108.

Likert plot of scale neuro items

Distribution of scale neuro

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	tipi_4 & tipi_9
Observations:	263
Positive correlations:	1
Number of correlations:	1
Percentage positive correlations:	100

Estimates assuming interval level

Estimates for two-item measures

Spearman Brown coefficient:	0.63
Coefficient Alpha:	0.62
Pearson Correlation:	0.46

Eigen values

1.46 & 0.54

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	NA	valid
tipi_4	2.56653992395437	3	1.19307462339999	1.09227955368577	1	0.0673528426435535	1	2	4	5	0.271221777198003	-0.654187194849791	0.14828897338403	263	0	263
tipi_9	2.22053231939163	2	0.790874524714829	0.889311264246006	1	0.0548372817561063	1	1	3	5	0.37233823606494	-0.394597934882847	0.133079847908745	263	0	263

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
tipi_4	I see myself as anxious, easily upset	haven_labelled	1. Strongly disagree, 3. Neither agree nor disagree, 5. Strongly agree	108	0.7088949	1	3	5	2.566540	1.0922796	3	<U+2585><U+2587><U+2581><U+2587><U+2581><U+2585><U+2581><U+2581>
tipi_9	I see myself as calm, emotionally stable	haven_labelled	5. Strongly disagree, 3. Neither agree nor disagree, 1. Strongly agree	108	0.7088949	1	2	5	2.220532	0.8893113	3	<U+2583><U+2587><U+2581><U+2585><U+2581><U+2582><U+2581><U+2581>

Scale: open

Overview

Reliability: .

Missing: 108.

Likert plot of scale open items

Distribution of scale open

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	tipi_5 & tipi_10
Observations:	263
Positive correlations:	1
Number of correlations:	1
Percentage positive correlations:	100

Estimates assuming interval level

Estimates for two-item measures

Spearman Brown coefficient:	0.44
Coefficient Alpha:	0.44
Pearson Correlation:	0.29

Eigen values

1.286 & 0.714

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	NA	valid
tipi_5	3.90874524714829	4	0.76263315241053	0.873288699348921	2	0.0538492880793795	1	3	5	5	-0.687780360944063	0.460400222159906	0.127376425855513	263	0	263
tipi_10	3.69201520912548	4	0.946768060836502	0.973020072165267	1	0.0599989879774125	1	3	5	5	-0.4514215942755	-0.332401333606577	0.131178707224335	263	0	263

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
tipi_5	I see myself as open to new experiences, complex	haven_labelled	1. Strongly disagree, 3. Neither agree nor disagree, 5. Strongly agree	108	0.7088949	1	4	5	3.908745	0.8732887	3	<U+2581><U+2581><U+2581><U+2583><U+2581><U+2587><U+2581><U+2585>
tipi_10	I see myself as conventional, uncreative	haven_labelled	5. Strongly disagree, 3. Neither agree nor disagree, 1. Strongly agree	108	0.7088949	1	4	5	3.692015	0.9730201	3	<U+2581><U+2582><U+2581><U+2585><U+2581><U+2587><U+2581><U+2585>

Scale: selfQRP

Overview

Reliability: .

Missing: 107.

Likert plot of scale selfQRP items

Distribution of scale selfQRP

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	qrp1_2, qrp2_2, qrp3_2, qrp4_2, qrp5_2, qrp6_2, qrp7_2, qrp8_2, qrp9_2 & qrp10_2
Observations:	264
Positive correlations:	45
Number of correlations:	45
Percentage positive correlations:	100

Estimates assuming interval level

Omega (total):	0.70
Omega (hierarchical):	0.45
Revelle’s Omega (total):	0.70
Greatest Lower Bound (GLB):	0.73
Coefficient H:	0.70
Coefficient Alpha:	0.65

(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

2.518, 1.186, 1.057, 1.008, 0.931, 0.809, 0.746, 0.674, 0.574 & 0.497

Factor analysis (reproducing only shared variance)

	ML1	ML2	ML3	ML4
qrp1_2	-0.055	0.729	0.051	0.016
qrp2_2	0.109	0.567	-0.087	-0.018
qrp3_2	-0.011	0.018	0.631	0.019
qrp4_2	0.229	0.190	0.319	-0.220
qrp5_2	0.063	-0.109	0.238	0.136
qrp6_2	0.052	0.294	0.126	0.351
qrp7_2	0.213	0.027	-0.036	0.335
qrp8_2	0.998	-0.005	0.002	0.007
qrp9_2	0.120	0.019	0.271	-0.051
qrp10_2	0.017	-0.130	0.274	0.221

Component analysis (reproducing full covariance matrix)

	TC1	TC4	TC2	TC3
qrp1_2	0.753	0.064	-0.048	0.004
qrp2_2	0.771	-0.058	-0.103	0.030
qrp3_2	0.218	0.483	0.302	-0.050
qrp4_2	0.457	0.429	0.158	-0.250
qrp5_2	-0.026	-0.096	0.859	-0.091
qrp6_2	0.484	-0.141	0.302	0.358
qrp7_2	0.019	0.018	-0.064	0.889
qrp8_2	0.307	0.435	0.101	0.266
qrp9_2	-0.078	0.825	-0.147	0.032
qrp10_2	-0.267	0.265	0.482	0.295

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
qrp1_2	2.40151515151515	3	1.1917847678304	1.09168895195948	2	0.067188810391179	1	1	4	5	-0.0902296317028737	-1.09776307620976	0.162878787878788	264	264
qrp2_2	1.88636363636364	1	1.12011752506049	1.05835604834124	2	0.0651373119886591	1	NA	3	5	0.616689494081706	-1.01964843779976	0.162878787878788	264	264
qrp3_2	1.82575757575758	1	1.04937204747091	1.02438862131073	2	0.0630467613697007	1	NA	3	5	0.740130666834008	-0.850621906471039	0.134469696969697	264	264
qrp4_2	2.23484848484848	3	1.35908514805853	1.16579807344949	2	0.0717499115208654	1	1	4	5	0.287146673041679	-1.06886637655915	0.195075757575758	264	264
qrp5_2	1.76136363636364	1	1.28504147943311	1.13359670052145	2	0.0697680540182186	1	NA	3	5	1.22178501708444	0.348458167837494	0.0984848484848485	264	264
qrp6_2	1.44318181818182	1	0.635542689249914	0.797209313323617	1	0.049064841499807	1	NA	3	4	1.38979430111458	0.182452416750788	0.0909090909090909	264	264
qrp7_2	1.35606060606061	1	0.579963129392787	0.76155310346212	0	0.0468703534825452	1	NA	3	4	2.00514235736426	2.80024862855935	0.053030303030303	264	264
qrp8_2	2.11363636363636	2	1.05167646042171	1.02551277925812	2	0.0631159485086205	1	1	3	4	0.0899480206909443	-1.53265504600842	0.208333333333333	264	264
qrp9_2	1.28787878787879	1	0.426316395898145	0.652929089486864	0	0.0401850075643581	1	NA	2	5	2.35187182485643	5.43439367997153	0.0492424242424242	264	264
qrp10_2	1.08712121212121	1	0.133065445327803	0.364781366475596	0	0.0224507411404797	1	NA	2	3	4.39478830941166	18.9323823092036	0.0170454545454545	264	264

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
qrp1_2	Not reporting nonsignificance	haven_labelled	1. Never, 2. Once, 3. Occasionally, 4. Frequently, 5. Almost always	93	0.7493261	1	3	5	2.392086	1.0985100	5	<U+2586><U+2582><U+2581><U+2587><U+2581><U+2582><U+2581><U+2581>
qrp2_2	Not reporting nonsignificance (covariate)	haven_labelled	1. Never, 2. Once, 3. Occasionally, 4. Frequently, 5. Almost always	90	0.7574124	1	1	5	1.886121	1.0595752	5	<U+2587><U+2581><U+2581><U+2585><U+2581><U+2581><U+2581><U+2581>
qrp3_2	HARKing	haven_labelled	1. Never, 2. Once, 3. Occasionally, 4. Frequently, 5. Almost always	85	0.7708895	1	1	5	1.825175	1.0416902	5	<U+2587><U+2582><U+2581><U+2583><U+2581><U+2581><U+2581><U+2581>
qrp4_2	Not reporting alternative models	haven_labelled	1. Never, 2. Once, 3. Occasionally, 4. Frequently, 5. Almost always	90	0.7574124	1	2	5	2.213523	1.1667853	5	<U+2587><U+2582><U+2581><U+2587><U+2581><U+2582><U+2581><U+2581>
qrp5_2	Rounding p-value	haven_labelled	1. Never, 2. Once, 3. Occasionally, 4. Frequently, 5. Almost always	89	0.7601078	1	1	5	1.776596	1.1458195	5	<U+2587><U+2581><U+2581><U+2582><U+2581><U+2581><U+2581><U+2581>
qrp6_2	Excluding data	haven_labelled	1. Never, 2. Once, 3. Occasionally, 4. Frequently, 5. Almost always	85	0.7708895	1	1	4	1.454546	0.8184476	5	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2582><U+2581><U+2581>
qrp7_2	Increasing sample	haven_labelled	1. Never, 2. Once, 3. Occasionally, 4. Frequently, 5. Almost always	84	0.7735849	1	1	4	1.344948	0.7452652	5	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581>
qrp8_2	Changing analysis	haven_labelled	1. Never, 2. Once, 3. Occasionally, 4. Frequently, 5. Almost always	90	0.7574124	1	2	4	2.113879	1.0322581	5	<U+2587><U+2581><U+2582><U+2581><U+2581><U+2587><U+2581><U+2581>
qrp9_2	Not reporting problems	haven_labelled	1. Never, 2. Once, 3. Occasionally, 4. Frequently, 5. Almost always	87	0.7654987	1	1	5	1.292253	0.6796979	5	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581>
qrp10_2	Imputing data	haven_labelled	1. Never, 2. Once, 3. Occasionally, 4. Frequently, 5. Almost always	88	0.7628032	1	1	3	1.102474	0.4040060	5	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581>

Scale: peerQRP

Overview

Reliability: .

Missing: 128.

Distribution of scale peerQRP

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	qrp1_1, qrp2_1, qrp3_1, qrp4_1, qrp5_1, qrp6_1, qrp7_1, qrp8_1, qrp9_1 & qrp10_1
Observations:	243
Positive correlations:	45
Number of correlations:	45
Percentage positive correlations:	100

Estimates assuming interval level

Omega (total):	0.89
Omega (hierarchical):	0.71
Revelle’s Omega (total):	0.89
Greatest Lower Bound (GLB):	0.90
Coefficient H:	0.86
Coefficient Alpha:	0.85

(Estimates assuming ordinal level not computed, as at least one item seems to have more than 8 levels; the highest number of distinct levels is 67 and the highest range is 101. This last number needs to be lower than 9 for the polychoric function to work. If this is unexpected, you may want to check for outliers.)

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

4.396, 1.136, 0.911, 0.712, 0.585, 0.543, 0.488, 0.471, 0.391 & 0.368

Factor analysis (reproducing only shared variance)

	ML1	ML2
qrp1_1	-0.061	0.777
qrp2_1	0.069	0.683
qrp3_1	0.471	0.254
qrp4_1	0.136	0.598
qrp5_1	0.380	0.154
qrp6_1	0.671	0.033
qrp7_1	0.686	-0.040
qrp8_1	0.572	0.179
qrp9_1	0.590	0.097
qrp10_1	0.724	-0.141

Component analysis (reproducing full covariance matrix)

	TC1	TC2
qrp1_1	-0.073	0.857
qrp2_1	0.074	0.752
qrp3_1	0.490	0.337
qrp4_1	0.059	0.772
qrp5_1	0.378	0.266
qrp6_1	0.680	0.122
qrp7_1	0.746	-0.015
qrp8_1	0.544	0.310
qrp9_1	0.667	0.112
qrp10_1	0.852	-0.191

Item descriptives

	mean	median	var	sd	IQR	se	q1	q3	max	skew	kurt	dip	n	valid
qrp1_1	58.8353909465021	66	791.931469577934	28.1412769713447	45	1.80526375941619	35	80	100	-0.383692539014826	-0.965469480090109	0.0448102423411065	243	243
qrp2_1	48.3991769547325	50	728.984627418971	26.9997153210728	44	1.73203254540718	20	71	100	0.00664065337977772	-0.971616549699875	0.0385802469135802	243	243
qrp3_1	45.6502057613169	50	778.459783015339	27.9008921544695	50	1.78984306622374	20	70	100	0.0166501449020511	-1.06494474387619	0.0401234567901235	243	243
qrp4_1	53.5061728395062	60	793.341903887358	28.1663257079683	50	1.8068706366198	30	81	100	-0.107678370123019	-1.07506403932118	0.0380658436213992	243	243
qrp5_1	45.40329218107	42	916.489575893616	30.2735788418485	51	1.94205098818606	20	71	100	0.195858491488025	-1.21244239297868	0.0390946502057613	243	243
qrp6_1	35.1975308641975	30	611.853382307928	24.7356702417365	38	1.58679398585026	10	54	100	0.432602438942964	-0.796839607407768	0.0495884773662552	243	243
qrp7_1	35.6460905349794	30	627.34530490086	25.046862176745	41	1.6067569577888	14	60	100	0.567056519910227	-0.65726469579524	0.0450617283950617	243	243
qrp8_1	49.2921810699589	50	781.860558446417	27.9617695871777	46	1.79374835535282	20	71	100	-0.103751993128007	-1.14185416428924	0.0417695473251029	243	243
qrp9_1	33.6296296296296	29	619.870523415978	24.897199107851	40	1.59715606744283	11	51	100	0.688665139079811	-0.346182804582853	0.0487654320987654	243	243
qrp10_1	19.9382716049383	10	422.835016835017	20.5629525320421	25	1.31911401996756	2.5	30	100	1.41333458385419	1.66829324729269	0.0742798353909465	243	243

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	n_missing	complete_rate	median	max	mean	sd	hist
qrp1_1	Not reporting nonsignificance	numeric	97	0.7385445	64	100	58.07664	28.56311	<U+2585><U+2583><U+2585><U+2587><U+2586>
qrp2_1	Not reporting nonsignificance (covariate)	numeric	96	0.7412399	50	100	48.52364	27.42732	<U+2587><U+2586><U+2587><U+2587><U+2585>
qrp3_1	HARKing	numeric	92	0.7520216	50	100	45.64158	28.17291	<U+2587><U+2585><U+2586><U+2586><U+2583>
qrp4_1	Not reporting alternative models	numeric	96	0.7412399	54	100	52.28727	28.51228	<U+2587><U+2587><U+2587><U+2587><U+2587>
qrp5_1	Rounding p-value	numeric	101	0.7277628	42	100	45.55926	30.24919	<U+2587><U+2586><U+2585><U+2583><U+2585>
qrp6_1	Excluding data	numeric	91	0.7547170	30	100	35.52857	25.35156	<U+2587><U+2585><U+2583><U+2582><U+2581>
qrp7_1	Increasing sample	numeric	93	0.7493261	30	100	35.10791	25.36170	<U+2587><U+2585><U+2583><U+2582><U+2581>
qrp8_1	Changing analysis	numeric	93	0.7493261	51	100	49.72662	27.92300	<U+2587><U+2585><U+2586><U+2587><U+2585>
qrp9_1	Not reporting problems	numeric	96	0.7412399	29	100	33.54909	24.84963	<U+2587><U+2585><U+2583><U+2582><U+2581>
qrp10_1	Imputing data	numeric	91	0.7547170	11	100	20.47500	20.49214	<U+2587><U+2583><U+2581><U+2581><U+2581>

Scale: opinionQRP

Overview

Reliability: .

Missing: 117.

Likert plot of scale opinionQRP items

Distribution of scale opinionQRP

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	qrp1_3, qrp2_3, qrp3_3, qrp4_3, qrp5_3, qrp6_3, qrp7_3, qrp8_3, qrp9_3 & qrp10_3
Observations:	254
Positive correlations:	45
Number of correlations:	45
Percentage positive correlations:	100

Estimates assuming interval level

Omega (total):	0.76
Omega (hierarchical):	0.54
Revelle’s Omega (total):	0.76
Greatest Lower Bound (GLB):	0.79
Coefficient H:	0.73
Coefficient Alpha:	0.71

(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

2.852, 1.091, 1.022, 0.904, 0.841, 0.783, 0.746, 0.641, 0.597 & 0.523

Factor analysis (reproducing only shared variance)

	ML2	ML1	ML3
qrp1_3	0.585	-0.020	0.046
qrp2_3	0.606	0.075	-0.123
qrp3_3	0.259	-0.045	0.407
qrp4_3	0.439	-0.066	0.193
qrp5_3	-0.032	0.179	0.437
qrp6_3	0.005	0.995	0.004
qrp7_3	0.325	0.111	0.057
qrp8_3	0.326	0.117	0.257
qrp9_3	0.218	-0.010	0.196
qrp10_3	-0.045	0.003	0.491

Component analysis (reproducing full covariance matrix)

	TC1	TC2	TC3
qrp1_3	0.673	-0.009	0.100
qrp2_3	0.682	-0.216	0.150
qrp3_3	0.413	0.487	-0.042
qrp4_3	0.660	0.163	-0.119
qrp5_3	-0.119	0.560	0.499
qrp6_3	0.063	0.008	0.797
qrp7_3	0.370	-0.136	0.445
qrp8_3	0.415	0.169	0.356
qrp9_3	0.443	0.342	-0.246
qrp10_3	0.009	0.757	-0.013

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
qrp1_3	1.86614173228346	2	0.42469888892347	0.651689257946968	1	0.0408906208045004	1	1	3	3	0.140459016569553	-0.666462271764254	0.143700787401575	254	254
qrp2_3	1.72834645669291	2	0.475319784631664	0.689434394726332	1	0.043258961323295	1	1	3	4	0.706281802691002	0.466370400179342	0.196850393700787	254	254
qrp3_3	1.5748031496063	1	0.63272229311257	0.795438428234751	1	0.0499102459425867	1	NA	2	4	1.29597320201262	0.993001988781937	0.141732283464567	254	254
qrp4_3	1.97637795275591	2	0.600230307179982	0.774745317623787	1	0.0486118447046651	1	1	3	4	0.349239026068767	-0.481877244243003	0.143700787401575	254	254
qrp5_3	1.55905511811024	1	0.642743767700974	0.801713020787971	1	0.0503039488948262	1	NA	2	4	1.19749543629212	0.352776737399655	0.112204724409449	254	254
qrp6_3	1.40157480314961	1	0.328218854066167	0.572903878557448	1	0.0359471864387037	1	NA	2	4	1.21849422319138	1.19709684040793	0.163385826771654	254	254
qrp7_3	1.72047244094488	2	0.526298590146587	0.725464396195008	1	0.0455196846813607	1	1	3	4	0.732571879238658	0.113386796314962	0.21259842519685	254	254
qrp8_3	1.84251968503937	2	0.417789673524011	0.646366516400727	1	0.0405566422962565	1	1	3	3	0.16123959646035	-0.647534901540905	0.149606299212598	254	254
qrp9_3	1.20866141732283	1	0.229015592418537	0.478555735958244	0	0.0300272574609164	1	NA	2	4	2.48721103833651	6.86299538770684	0.078740157480315	254	254
qrp10_3	1.13779527559055	1	0.14299274843609	0.378143819777727	0	0.0237268534896652	1	NA	2	3	2.75413052309218	7.29373738855994	0.0570866141732283	254	254

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
qrp1_3	Not reporting nonsignificance	haven_labelled	1. It should never be used, 2. It should only be used rarely, 3. It should be used often, 4. It should be used almost always	99	0.7331536	1	2	3	1.852941	0.6489209	4	<U+2585><U+2581><U+2581><U+2587><U+2581><U+2581><U+2581><U+2582>
qrp2_3	Not reporting nonsignificance (covariate)	haven_labelled	1. It should never be used, 2. It should only be used rarely, 3. It should be used often, 4. It should be used almost always	93	0.7493261	1	2	4	1.730216	0.6923152	4	<U+2586><U+2581><U+2587><U+2581><U+2581><U+2582><U+2581><U+2581>
qrp3_3	HARKing	haven_labelled	1. It should never be used, 2. It should only be used rarely, 3. It should be used often, 4. It should be used almost always	87	0.7654987	1	1	4	1.570423	0.7966173	4	<U+2587><U+2581><U+2583><U+2581><U+2581><U+2581><U+2581><U+2581>
qrp4_3	Not reporting alternative models	haven_labelled	1. It should never be used, 2. It should only be used rarely, 3. It should be used often, 4. It should be used almost always	92	0.7520216	1	2	4	1.953405	0.7736540	4	<U+2585><U+2581><U+2587><U+2581><U+2581><U+2583><U+2581><U+2581>
qrp5_3	Rounding p-value	haven_labelled	1. It should never be used, 2. It should only be used rarely, 3. It should be used often, 4. It should be used almost always	96	0.7412399	1	1	4	1.563636	0.8096957	4	<U+2587><U+2581><U+2583><U+2581><U+2581><U+2582><U+2581><U+2581>
qrp6_3	Excluding data	haven_labelled	1. It should never be used, 2. It should only be used rarely, 3. It should be used often, 4. It should be used almost always	88	0.7628032	1	1	4	1.406360	0.5781744	4	<U+2587><U+2581><U+2585><U+2581><U+2581><U+2581><U+2581><U+2581>
qrp7_3	Increasing sample	haven_labelled	1. It should never be used, 2. It should only be used rarely, 3. It should be used often, 4. It should be used almost always	90	0.7574124	1	2	4	1.693950	0.7163392	4	<U+2587><U+2581><U+2587><U+2581><U+2581><U+2582><U+2581><U+2581>
qrp8_3	Changing analysis	haven_labelled	1. It should never be used, 2. It should only be used rarely, 3. It should be used often, 4. It should be used almost always	93	0.7493261	1	2	3	1.830935	0.6610733	4	<U+2585><U+2581><U+2581><U+2587><U+2581><U+2581><U+2581><U+2582>
qrp9_3	Not reporting problems	haven_labelled	1. It should never be used, 2. It should only be used rarely, 3. It should be used often, 4. It should be used almost always	88	0.7628032	1	1	4	1.204947	0.4914628	4	<U+2587><U+2581><U+2582><U+2581><U+2581><U+2581><U+2581><U+2581>
qrp10_3	Imputing data	haven_labelled	1. It should never be used, 2. It should only be used rarely, 3. It should be used often, 4. It should be used almost always	90	0.7574124	1	1	3	1.145908	0.3827429	4	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581>

Scale: awarePRRP

Overview

Reliability: .

Missing: 88.

Likert plot of scale awarePRRP items

Distribution of scale awarePRRP

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	prrp1_2, prrp2_2 & prrp3_2
Observations:	283
Positive correlations:	3
Number of correlations:	3
Percentage positive correlations:	100

Estimates assuming interval level

Omega (total):	0.58
Omega (hierarchical):	0.05
Revelle’s Omega (total):	0.58
Greatest Lower Bound (GLB):	0.60
Coefficient H:	0.62
Coefficient Alpha:	0.55

(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

1.591, 0.814 & 0.595

Factor analysis (reproducing only shared variance)

	ML1
prrp1_2	0.568
prrp2_2	0.373
prrp3_2	0.704

Component analysis (reproducing full covariance matrix)

	PC1
prrp1_2	0.759
prrp2_2	0.624
prrp3_2	0.791

Item descriptives

	mean	median	var	sd	se	q3	max	skew	kurt	dip	n	valid
prrp1_2	0.858657243816254	1	0.121795353732802	0.348991910698231	0.0207454157508162	NA	1	-2.07001912273632	2.30119229634651	0.0706713780918728	283	283
prrp2_2	0.840989399293286	1	0.134200436057439	0.366333776844887	0.0217762826909341	NA	1	-1.87488237128716	1.52591792588922	0.0795053003533569	283	283
prrp3_2	0.76678445229682	1	0.179460190963085	0.423627419984927	0.0251820362639639	NA	1	-1.26848858853807	-0.393769718154322	0.11660777385159	283	283

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	median	max	mean	sd	n_value_labels	hist
prrp1_2	Posting data	haven_labelled	0. No, 1. Yes	85	0.7708895	1	1	0.8601399	0.3474498	2	<U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2587>
prrp2_2	Posting instruments	haven_labelled	0. No, 1. Yes	84	0.7735849	1	1	0.8432056	0.3642420	2	<U+2582><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2587>
prrp3_2	Preregistration	haven_labelled	0. No, 1. Yes	82	0.7789757	1	1	0.7681661	0.4227355	2	<U+2582><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2587>

Scale: selfPRRP

Overview

Reliability: .

Missing: 90.

Likert plot of scale selfPRRP items

Distribution of scale selfPRRP

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	prrp1_3, prrp2_3 & prrp3_3
Observations:	281
Positive correlations:	3
Number of correlations:	3
Percentage positive correlations:	100

Estimates assuming interval level

Omega (total):	0.67
Omega (hierarchical):	0.01
Revelle’s Omega (total):	0.67
Greatest Lower Bound (GLB):	0.70
Coefficient H:	0.76
Coefficient Alpha:	0.62

(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

1.733, 0.778 & 0.489

Factor analysis (reproducing only shared variance)

	ML1
prrp1_3	0.838
prrp2_3	0.593
prrp3_3	0.411

Component analysis (reproducing full covariance matrix)

	PC1
prrp1_3	0.835
prrp2_3	0.782
prrp3_3	0.652

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
prrp1_3	1.74021352313167	1	1.1644128113879	1.07907961309067	2	0.0643724928375517	1	NA	3	5	1.21960536779836	0.472512956845054	0.103202846975089	281	281
prrp2_3	2.20640569395018	2	1.52153024911032	1.23350324244013	2	0.0735846342343997	1	1	3	5	0.463281109624557	-0.956648885139312	0.169039145907473	281	281
prrp3_3	1.81850533807829	1	1.37051347229283	1.17068931501609	2	0.0698374694801498	1	NA	3	5	1.16494896010288	0.180802712318851	0.0907473309608541	281	281

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
prrp1_3	Posting data	haven_labelled	1. Never, 2. Once, 3. Occasionally, 4. Frequently, 5. Almost always	85	0.7708895	1	1	5	1.727273	1.073978	5	<U+2587><U+2581><U+2581><U+2582><U+2581><U+2581><U+2581><U+2581>
prrp2_3	Posting instruments	haven_labelled	1. Never, 2. Once, 3. Occasionally, 4. Frequently, 5. Almost always	86	0.7681941	1	2	5	2.203509	1.230762	5	<U+2587><U+2581><U+2581><U+2586><U+2581><U+2582><U+2581><U+2581>
prrp3_3	Preregistration	haven_labelled	1. Never, 2. Once, 3. Occasionally, 4. Frequently, 5. Almost always	82	0.7789757	1	1	5	1.826990	1.174600	5	<U+2587><U+2581><U+2581><U+2582><U+2581><U+2581><U+2581><U+2581>

Scale: peerPRRP

Overview

Reliability: .

Missing: 105.

Distribution of scale peerPRRP

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	prrp1_1, prrp2_1 & prrp3_1
Observations:	266
Positive correlations:	3
Number of correlations:	3
Percentage positive correlations:	100

Estimates assuming interval level

Omega (total):	0.68
Omega (hierarchical):	0.05
Revelle’s Omega (total):	0.68
Greatest Lower Bound (GLB):	0.68
Coefficient H:	0.68
Coefficient Alpha:	0.67

(Estimates assuming ordinal level not computed, as at least one item seems to have more than 8 levels; the highest number of distinct levels is 65 and the highest range is 101. This last number needs to be lower than 9 for the polychoric function to work. If this is unexpected, you may want to check for outliers.)

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

1.815, 0.629 & 0.555

Factor analysis (reproducing only shared variance)

	ML1
prrp1_1	0.639
prrp2_1	0.689
prrp3_1	0.589

Component analysis (reproducing full covariance matrix)

	PC1
prrp1_1	0.780
prrp2_1	0.797
prrp3_1	0.756

Item descriptives

	mean	median	var	sd	IQR	se	q1	q3	max	skew	kurt	dip	n	valid
prrp1_1	25.2556390977444	20	344.7721378919	18.5680407661094	20	1.13847962508622	10	32	100	1.34809502429879	2.0002195023154	0.0644736842105263	266	266
prrp2_1	37.7406015037594	30	528.094722655696	22.9803116309526	33	1.4090133094561	19	60	100	0.624775740992544	-0.491566041933891	0.057758031442242	266	266
prrp3_1	28.1691729323308	25	484.405234785076	22.0092079545148	30	1.34947112278184	10	40	100	1.23405841224116	1.4537137416041	0.0567669172932331	266	266

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	n_missing	complete_rate	median	max	mean	sd	hist
prrp1_1	Posting data	numeric	93	0.7493261	20	100	25.32374	18.29471	<U+2587><U+2585><U+2581><U+2581><U+2581>
prrp2_1	Posting instruments	numeric	98	0.7358491	30	100	37.83883	23.00806	<U+2586><U+2587><U+2583><U+2583><U+2581>
prrp3_1	Preregistration	numeric	90	0.7574124	25	100	28.13879	21.85321	<U+2587><U+2586><U+2582><U+2581><U+2581>

Scale: recentPRRP

Overview

Reliability: .

Missing: 96.

Likert plot of scale recentPRRP items

Distribution of scale recentPRRP

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	prrp1_4, prrp2_4 & prrp3_4
Observations:	275
Positive correlations:	3
Number of correlations:	3
Percentage positive correlations:	100

Estimates assuming interval level

Omega (total):	0.54
Omega (hierarchical):	0.09
Revelle’s Omega (total):	0.54
Greatest Lower Bound (GLB):	0.54
Coefficient H:	0.54
Coefficient Alpha:	0.53

(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

1.551, 0.767 & 0.682

Factor analysis (reproducing only shared variance)

	ML1
prrp1_4	0.583
prrp2_4	0.543
prrp3_4	0.451

Component analysis (reproducing full covariance matrix)

	PC1
prrp1_4	0.745
prrp2_4	0.731
prrp3_4	0.680

Item descriptives

	mean	var	sd	IQR	se	q1	q3	max	skew	kurt	dip	n	valid
prrp1_4	0.149090909090909	0.127325812873258	0.35682742729961	0	0.0215175034774659	NA	1	1	1.98123701507426	1.93935177380713	0.0745454545454545	275	275
prrp2_4	0.272727272727273	0.19907100199071	0.446173735209403	1	0.026905288563654	NA	1	1	1.0262268299154	-0.9538488472312	0.136363636363636	275	275
prrp3_4	0.16	0.134890510948905	0.367274435468772	0	0.0221474817734457	NA	1	1	1.86504046791987	1.48915335364915	0.08	275	275

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	max	mean	sd	n_value_labels	hist
prrp1_4	Posting data	haven_labelled	0. No, 1. Yes	91	0.7547170	1	0.1500000	0.3577108	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2582>
prrp2_4	Posting instruments	haven_labelled	0. No, 1. Yes	89	0.7601078	1	0.2695035	0.4444907	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2583>
prrp3_4	Preregistration	haven_labelled	0. No, 1. Yes	88	0.7628032	1	0.1660777	0.3728097	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2582>

Scale: opinionPRRP

Overview

Reliability: .

Missing: 101.

Likert plot of scale opinionPRRP items

Distribution of scale opinionPRRP

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	prrp1_6, prrp2_6 & prrp3_6
Observations:	270
Positive correlations:	3
Number of correlations:	3
Percentage positive correlations:	100

Estimates assuming interval level

Omega (total):	0.64
Omega (hierarchical):	0.14
Revelle’s Omega (total):	0.64
Greatest Lower Bound (GLB):	0.64
Coefficient H:	0.65
Coefficient Alpha:	0.64

(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

1.735, 0.701 & 0.564

Factor analysis (reproducing only shared variance)

	ML1
prrp1_6	0.658
prrp2_6	0.503
prrp3_6	0.663

Component analysis (reproducing full covariance matrix)

	PC1
prrp1_6	0.784
prrp2_6	0.709
prrp3_6	0.786

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
prrp1_6	2.81851851851852	3	0.453930882555418	0.673743929512851	1	0.0410027497973732	1	2	4	4	-0.207023227548719	0.0342865497252829	0.133333333333333	270	270
prrp2_6	3.1037037037037	3	0.383257607049429	0.619078029855226	0	0.0376758890897294	1	2	4	4	-0.353194400105707	0.708350738160816	0.118518518518519	270	270
prrp3_6	2.85185185185185	3	0.498416632245629	0.705986283326828	1	0.0429649569630375	1	2	4	4	-0.293056271970838	0.0557020430614203	0.122222222222222	270	270

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
prrp1_6	Posting data	haven_labelled	1. It should never be used, 2. It should only be used rarely, 3. It should be used often, 4. It should be used almost always	93	0.7493261	1	3	4	2.809353	0.6821491	4	<U+2581><U+2581><U+2583><U+2581><U+2581><U+2587><U+2581><U+2582>
prrp2_6	Posting instruments	haven_labelled	1. It should never be used, 2. It should only be used rarely, 3. It should be used often, 4. It should be used almost always	90	0.7574124	1	3	4	3.099644	0.6245283	4	<U+2581><U+2581><U+2582><U+2581><U+2581><U+2587><U+2581><U+2583>
prrp3_6	Preregistration	haven_labelled	1. It should never be used, 2. It should only be used rarely, 3. It should be used often, 4. It should be used almost always	90	0.7574124	1	3	4	2.846975	0.6980072	4	<U+2581><U+2581><U+2583><U+2581><U+2581><U+2587><U+2581><U+2582>

Scale: prrp1_5

Overview

Reliability: .

Missing: 0.

Likert plot of scale prrp1_5 items

Distribution of scale prrp1_5

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	prrp1_5_1, prrp1_5_2, prrp1_5_3, prrp1_5_4, prrp1_5_5, prrp1_5_6, prrp1_5_7, prrp1_5_8, prrp1_5_9 & prrp1_5_10
Observations:	371
Positive correlations:	20
Number of correlations:	45
Percentage positive correlations:	44

Estimates assuming interval level

Omega (total):	0.43
Omega (hierarchical):	0.13
Revelle’s Omega (total):	0.43
Greatest Lower Bound (GLB):	0.36
Coefficient H:	0.51
Coefficient Alpha:	0.12

(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

1.57, 1.221, 1.106, 1.078, 1.056, 0.911, 0.834, 0.791, 0.76 & 0.673

Factor analysis (reproducing only shared variance)

	ML1	ML2	ML3	ML4	ML5
prrp1_5_1	-0.017	-0.009	-0.001	0.601	0.019
prrp1_5_2	0.009	0.013	0.570	0.030	0.002
prrp1_5_3	-0.012	-0.050	0.383	-0.128	0.160
prrp1_5_4	0.070	0.012	0.108	0.311	0.026
prrp1_5_5	-0.009	0.001	-0.022	0.043	0.496
prrp1_5_6	-0.102	-0.073	-0.064	-0.022	-0.093
prrp1_5_7	-0.025	-0.002	0.484	0.040	-0.100
prrp1_5_8	-0.041	0.066	0.195	-0.096	0.107
prrp1_5_9	0.000	0.997	0.000	-0.001	0.001
prrp1_5_10	0.997	0.000	-0.001	-0.001	0.000

Component analysis (reproducing full covariance matrix)

	TC1	TC2	TC4	TC3	TC5
prrp1_5_1	-0.035	0.774	0.093	-0.023	-0.101
prrp1_5_2	0.729	0.063	-0.081	-0.037	-0.043
prrp1_5_3	0.597	-0.212	0.256	-0.221	0.096
prrp1_5_4	0.116	0.688	-0.041	-0.059	0.211
prrp1_5_5	-0.086	0.050	0.866	-0.091	0.080
prrp1_5_6	-0.052	-0.066	-0.151	-0.181	-0.835
prrp1_5_7	0.695	0.130	-0.231	0.059	0.026
prrp1_5_8	0.322	-0.233	0.291	0.360	-0.065
prrp1_5_9	-0.073	-0.048	-0.117	0.851	0.120
prrp1_5_10	-0.140	-0.166	-0.309	-0.377	0.544

Item descriptives

	mean	var	sd	se	q1	q3	max	skew	kurt	dip	n	valid
prrp1_5_1	0.207547169811321	0.164915859255482	0.406098336927747	0.0210835751439445	NA	1	1	1.44811201446372	0.0975250153404984	0.10377358490566	371	371
prrp1_5_2	0.134770889487871	0.116922852771909	0.341939837942158	0.017752631844056	NA	1	1	2.1477969592349	2.62716546141488	0.0673854447439353	371	371
prrp1_5_3	0.0619946091644205	0.0583084432141036	0.241471412829974	0.0125365711074582	NA	1	1	3.64746616282997	11.3652493521709	0.0309973045822102	371	371
prrp1_5_4	0.107816711590297	0.0964522473956436	0.310567621293083	0.0161238675103804	NA	1	1	2.53927915246079	4.47201773763107	0.0539083557951483	371	371
prrp1_5_5	0.0350404312668464	0.0339039848473811	0.184130347437301	0.00955957132413879	NA	1	1	5.07770371699247	23.9119531836375	0.0175202156334232	371	371
prrp1_5_6	0.0404312668463612	0.0389014351278502	0.197234467393126	0.0102399033340506	NA	1	1	4.68538411874261	20.0609420157465	0.0202156334231806	371	371
prrp1_5_7	0.0485175202156334	0.0462883368543746	0.215147244589315	0.0111698883886798	NA	1	1	4.21971046073008	15.8915974695732	0.0242587601078167	371	371
prrp1_5_8	0.132075471698113	0.11494135645079	0.339030022934239	0.0176015617760558	NA	1	1	2.18221794037836	2.77701665755518	0.0660377358490566	371	371
prrp1_5_9	0.0646900269541779	0.0606687550083777	0.2463102819786	0.0127877926762993	NA	1	1	3.55380516946338	10.6871153635888	0.032345013477089	371	371
prrp1_5_10	0.118598382749326	0.104815327456837	0.323751953595398	0.0168083639378259	NA	1	1	2.36890514747336	3.63125825908692	0.0592991913746631	371	371

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	complete_rate	max	mean	sd	n_value_labels	hist
prrp1_5_1	Posting data - The data were propritary or access was restricted	haven_labelled	0. No, 1. Yes	1	1	0.2075472	0.4060983	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2582>
prrp1_5_2	Posting data - It was too time-consuming	haven_labelled	0. No, 1. Yes	1	1	0.1347709	0.3419398	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581>
prrp1_5_3	Posting data - I didn’t want to be scooped	haven_labelled	0. No, 1. Yes	1	1	0.0619946	0.2414714	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581>
prrp1_5_4	Posting data - The data were too difficult to deidentify	haven_labelled	0. No, 1. Yes	1	1	0.1078167	0.3105676	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581>
prrp1_5_5	Posting data - I didn’t perceive my field to be in favor of this	haven_labelled	0. No, 1. Yes	1	1	0.0350404	0.1841303	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581>
prrp1_5_6	Posting data - The data were already publicly available	haven_labelled	0. No, 1. Yes	1	1	0.0404313	0.1972345	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581>
prrp1_5_7	Posting data - I was nervous that someone would discover a mistake	haven_labelled	0. No, 1. Yes	1	1	0.0485175	0.2151472	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581>
prrp1_5_8	Posting data - I was unfamiliar with the practice	haven_labelled	0. No, 1. Yes	1	1	0.1320755	0.3390300	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581>
prrp1_5_9	Posting data - I am planning to but haven’t done it yet	haven_labelled	0. No, 1. Yes	1	1	0.0646900	0.2463103	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581>
prrp1_5_10	Posting data - Other reason	haven_labelled	0. No, 1. Yes	1	1	0.1185984	0.3237520	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581>

Scale: prrp2_5

Overview

Reliability: .

Missing: 0.

Likert plot of scale prrp2_5 items

Distribution of scale prrp2_5

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	prrp2_5_1, prrp2_5_2, prrp2_5_3, prrp2_5_4, prrp2_5_5, prrp2_5_6, prrp2_5_7, prrp2_5_8 & prrp2_5_9
Observations:	371
Positive correlations:	21
Number of correlations:	36
Percentage positive correlations:	58

Estimates assuming interval level

Omega (total):	0.50
Omega (hierarchical):	0.18
Revelle’s Omega (total):	0.50
Greatest Lower Bound (GLB):	0.46
Coefficient H:	0.51
Coefficient Alpha:	0.19

(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

1.621, 1.204, 1.152, 1.059, 0.907, 0.888, 0.811, 0.748 & 0.61

Factor analysis (reproducing only shared variance)

	ML2	ML1	ML3	ML4
prrp2_5_1	0.096	0.049	0.208	-0.109
prrp2_5_2	0.166	0.169	0.279	0.036
prrp2_5_3	-0.028	-0.026	0.699	0.031
prrp2_5_4	0.038	0.042	0.453	-0.094
prrp2_5_5	-0.004	0.997	-0.003	0.002
prrp2_5_6	0.998	-0.004	-0.003	0.000
prrp2_5_7	0.001	0.012	0.011	0.533
prrp2_5_8	-0.049	-0.070	-0.060	0.146
prrp2_5_9	-0.134	-0.031	0.036	-0.173

Component analysis (reproducing full covariance matrix)

	TC1	TC2	TC3	TC4
prrp2_5_1	0.416	-0.249	0.408	0.241
prrp2_5_2	0.323	0.440	0.326	-0.190
prrp2_5_3	0.767	0.107	-0.103	0.029
prrp2_5_4	0.737	-0.038	0.006	-0.025
prrp2_5_5	0.020	0.710	0.071	-0.183
prrp2_5_6	-0.033	-0.059	0.790	-0.126
prrp2_5_7	0.027	0.637	-0.238	0.283
prrp2_5_8	0.040	-0.061	-0.075	0.812
prrp2_5_9	0.179	-0.263	-0.505	-0.454

Item descriptives

	mean	var	sd	se	q1	q3	max	skew	kurt	dip	n	valid
prrp2_5_1	0.175202156334232	0.144896918481824	0.380653278564397	0.019762533535884	NA	1	1	1.71577802673469	0.948980971874117	0.0876010781671159	371	371
prrp2_5_2	0.0970350404312668	0.0878560501202011	0.296405212707538	0.0153885918924315	NA	1	1	2.7337511900661	5.50303280639339	0.0485175202156334	371	371
prrp2_5_3	0.0296495956873315	0.0288482552633496	0.169847741413743	0.00881805536613915	NA	1	1	5.5685136000169	29.1655435139661	0.0148247978436658	371	371
prrp2_5_4	0.0215633423180593	0.021155387193123	0.1454489160947	0.0075513314713069	NA	1	1	6.61441588172319	41.9767614324095	0.0107816711590297	371	371
prrp2_5_5	0.0431266846361186	0.0413783055292489	0.203416581254452	0.0105608626936229	NA	1	1	4.51634365953029	18.4970469023046	0.0215633423180593	371	371
prrp2_5_6	0.207547169811321	0.164915859255482	0.406098336927747	0.0210835751439445	NA	1	1	1.44811201446372	0.0975250153404984	0.10377358490566	371	371
prrp2_5_7	0.113207547169811	0.100662927078021	0.317274214328901	0.0164720564719513	NA	1	1	2.45143709337658	4.03124678795354	0.0566037735849057	371	371
prrp2_5_8	0.0377358490566038	0.0364099949005609	0.190814032242288	0.00990657094962473	NA	1	1	4.87144097564409	21.8486924639067	0.0188679245283019	371	371
prrp2_5_9	0.0889487870619946	0.0812559189917681	0.285054238684093	0.0147992786842298	NA	1	1	2.89965260435462	6.44268806394592	0.0444743935309973	371	371

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	complete_rate	max	mean	sd	n_value_labels	hist
prrp2_5_1	Posting instruments - The materials were proprietary or access was restricted	haven_labelled	0. No, 1. Yes	1	1	0.1752022	0.3806533	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2582>
prrp2_5_2	Posting instruments - It was too time-consuming	haven_labelled	0. No, 1. Yes	1	1	0.0970350	0.2964052	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581>
prrp2_5_3	Posting instruments - I didn’t want to be scooped	haven_labelled	0. No, 1. Yes	1	1	0.0296496	0.1698477	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581>
prrp2_5_4	Posting instruments - Materials were too difficult to deidentify	haven_labelled	0. No, 1. Yes	1	1	0.0215633	0.1454489	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581>
prrp2_5_5	Posting instruments - I didn’t perceive my field to be in favor of this	haven_labelled	0. No, 1. Yes	1	1	0.0431267	0.2034166	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581>
prrp2_5_6	Posting instruments - The materials were already publicly available	haven_labelled	0. No, 1. Yes	1	1	0.2075472	0.4060983	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2582>
prrp2_5_7	Posting instruments - I was unfamiliar with the practice	haven_labelled	0. No, 1. Yes	1	1	0.1132075	0.3172742	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581>
prrp2_5_8	Posting instruments - I am planning to but haven’t done it yet	haven_labelled	0. No, 1. Yes	1	1	0.0377358	0.1908140	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581>
prrp2_5_9	Posting instruments - Other reason	haven_labelled	0. No, 1. Yes	1	1	0.0889488	0.2850542	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581>

Scale: prrp3_5

Overview

Reliability: .

Missing: 0.

Likert plot of scale prrp3_5 items

Distribution of scale prrp3_5

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	prrp3_5_1, prrp3_5_2, prrp3_5_3, prrp3_5_4, prrp3_5_5 & prrp3_5_6
Observations:	371
Positive correlations:	4
Number of correlations:	15
Percentage positive correlations:	27

Estimates assuming interval level

Omega (total):	0.61
Omega (hierarchical):	0.29
Revelle’s Omega (total):	0.61
Greatest Lower Bound (GLB):	0.31
Coefficient H:	0.63
Coefficient Alpha:	-0.23

(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

1.412, 1.17, 1.093, 0.925, 0.748 & 0.652

Factor analysis (reproducing only shared variance)

	ML3	ML1	ML2
prrp3_5_1	0.209	-0.071	-0.025
prrp3_5_2	0.989	0.003	0.002
prrp3_5_3	0.258	-0.112	-0.072
prrp3_5_4	-0.052	-0.107	-0.129
prrp3_5_5	0.000	-0.001	0.997
prrp3_5_6	0.000	0.997	-0.001

Component analysis (reproducing full covariance matrix)

	TC1	TC2	TC3
prrp3_5_1	0.544	0.033	0.344
prrp3_5_2	0.772	-0.031	0.139
prrp3_5_3	0.662	0.033	-0.202
prrp3_5_4	-0.068	-0.003	-0.865
prrp3_5_5	-0.184	0.767	0.304
prrp3_5_6	-0.189	-0.766	0.296

Item descriptives

	mean	var	sd	IQR	se	q1	q3	max	skew	kurt	dip	n	valid
prrp3_5_1	0.134770889487871	0.116922852771909	0.341939837942158	0	0.017752631844056	NA	1	1	2.1477969592349	2.62716546141488	0.0673854447439353	371	371
prrp3_5_2	0.0566037735849057	0.0535441101478837	0.231396002877932	0	0.0120134818861701	NA	1	1	3.85313015307142	12.9162130316955	0.0283018867924528	371	371
prrp3_5_3	0.0835579514824798	0.0767829824433598	0.27709742410091	0	0.0143861814540365	NA	1	1	3.02203593808503	7.17133210654357	0.0417789757412399	371	371
prrp3_5_4	0.0296495956873315	0.0288482552633496	0.169847741413743	0	0.00881805536613915	NA	1	1	5.5685136000169	29.1655435139661	0.0148247978436658	371	371
prrp3_5_5	0.280323450134771	0.202287462664821	0.44976378540832	1	0.0233505722737505	NA	1	1	0.982147588746264	-1.04102734300332	0.140161725067385	371	371
prrp3_5_6	0.175202156334232	0.144896918481824	0.380653278564397	0	0.019762533535884	NA	1	1	1.71577802673469	0.948980971874117	0.0876010781671159	371	371

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	complete_rate	max	mean	sd	n_value_labels	hist
prrp3_5_1	Preregistration - It was too time-consuming	haven_labelled	0. No, 1. Yes	1	1	0.1347709	0.3419398	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581>
prrp3_5_2	Preregistration - I didn’t want to be scooped	haven_labelled	0. No, 1. Yes	1	1	0.0566038	0.2313960	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581>
prrp3_5_3	Preregistration - I didn’t perceive my field to be in favor of this	haven_labelled	0. No, 1. Yes	1	1	0.0835580	0.2770974	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581>
prrp3_5_4	Preregistration - The materials were already publicly available	haven_labelled	0. No, 1. Yes	1	1	0.0296496	0.1698477	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581>
prrp3_5_5	Preregistration - I was unfamiliar with the practice	haven_labelled	0. No, 1. Yes	1	1	0.2803235	0.4497638	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2583>
prrp3_5_6	Preregistration - Other reason	haven_labelled	0. No, 1. Yes	1	1	0.1752022	0.3806533	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2582>

prrp1_5_o

If answered “No” above. Why not? - Text - Posting data

Distribution

Distribution of values for prrp1_5_o

328 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
prrp1_5_o	If answered “No” above. Why not? - Text - Posting data	character	328	0.115903	43	0	3	265	0

prrp2_5_o

If answered “No” above. Why not? - Text - Posting instruments

Distribution

Distribution of values for prrp2_5_o

340 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
prrp2_5_o	If answered “No” above. Why not? - Text - Posting instruments	character	340	0.083558	31	0	3	138	0

prrp3_5_o

If answered “No” above. Why not? - Text - Preregistration

Distribution

Distribution of values for prrp3_5_o

307 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
prrp3_5_o	If answered “No” above. Why not? - Text - Preregistration	character	307	0.1725067	64	0	5	600	0

Scale: participate

Overview

Reliability: .

Missing: 105.

Likert plot of scale participate items

Distribution of scale participate

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	participate_1, participate_2, participate_3 & participate_4
Observations:	266
Positive correlations:	6
Number of correlations:	6
Percentage positive correlations:	100

Estimates assuming interval level

Omega (total):	0.88
Omega (hierarchical):	0.83
Revelle’s Omega (total):	0.88
Greatest Lower Bound (GLB):	0.88
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

2.772, 0.623, 0.342 & 0.263

Factor analysis (reproducing only shared variance)

	ML1
participate_1	0.680
participate_2	0.835
participate_3	0.683
participate_4	0.886

Component analysis (reproducing full covariance matrix)

	PC1
participate_1	0.772
participate_2	0.881
participate_3	0.769
participate_4	0.899

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
participate_1	3.19548872180451	3	3.44088523194779	1.854962326288	4	0.113735037550972	1	1	5	7	0.347442763159845	-1.07276670868598	0.0864661654135338	266	266
participate_2	3.6203007518797	4	2.7571712299617	1.66047319459294	3	0.101810143776521	1	2	5	7	0.0812584044844383	-0.942264699674576	0.0977443609022556	266	266
participate_3	2.62406015037594	2	3.02040005674564	1.73792981928087	3	0.10655931414651	1	1	4	7	0.748119486530506	-0.636425559676063	0.0845864661654135	266	266
participate_4	3.21804511278195	3	2.35982408852319	1.53617189419778	2	0.0941887420543795	1	2	5	7	0.327425805096657	-0.750513835678495	0.112781954887218	266	266

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
participate_1	In your department	haven_labelled	1. Not at all, 7. Extremely	105	0.7169811	1	3	7	3.195489	1.854962	2	<U+2587><U+2585><U+2583><U+2585><U+2581><U+2585><U+2582><U+2582>
participate_2	At conference or other professional gatherings outside of your department	haven_labelled	1. Not at all, 7. Extremely	105	0.7169811	1	4	7	3.620301	1.660473	2	<U+2585><U+2587><U+2587><U+2587><U+2581><U+2587><U+2585><U+2582>
participate_3	Online	haven_labelled	1. Not at all, 7. Extremely	105	0.7169811	1	2	7	2.624060	1.737930	2	<U+2587><U+2583><U+2582><U+2582><U+2581><U+2582><U+2581><U+2581>
participate_4	In general	haven_labelled	1. Not at all, 7. Extremely	105	0.7169811	1	3	7	3.218045	1.536172	2	<U+2585><U+2587><U+2587><U+2586><U+2581><U+2585><U+2583><U+2581>

Scale: comfort

Overview

Reliability: .

Missing: 107.

Likert plot of scale comfort items

Distribution of scale comfort

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	comfort_1, comfort_2, comfort_3 & comfort_4
Observations:	264
Positive correlations:	6
Number of correlations:	6
Percentage positive correlations:	100

Estimates assuming interval level

Omega (total):	0.93
Omega (hierarchical):	0.87
Revelle’s Omega (total):	0.93
Greatest Lower Bound (GLB):	0.94
Coefficient H:	0.95
Coefficient Alpha:	0.89

(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

3.086, 0.544, 0.229 & 0.14

Factor analysis (reproducing only shared variance)

	ML1
comfort_1	0.791
comfort_2	0.883
comfort_3	0.718
comfort_4	0.960

Component analysis (reproducing full covariance matrix)

	PC1
comfort_1	0.850
comfort_2	0.920
comfort_3	0.787
comfort_4	0.948

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
comfort_1	5.03030303030303	5	2.99527595345086	1.73068655551803	2	0.1065163942683	1	3	7	7	-0.681152422451347	-0.48702842675317	0.115530303030303	264	264
comfort_2	4.84848484848485	5	2.72980758151861	1.6522129346784	2	0.101686676772452	1	3	6	7	-0.530703639948529	-0.525516358744471	0.111742424242424	264	264
comfort_3	4.20075757575758	4	3.82646330222376	1.95613478631299	3	0.120391773701902	1	2	6	7	-0.176713869456117	-1.20281661867317	0.0732323232323232	264	264
comfort_4	4.70833333333333	5	2.66365652724968	1.63207123841139	2	0.100447041060272	1	3	6	7	-0.457820025500902	-0.608168783793895	0.109848484848485	264	264

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
comfort_1	With other psychology researchers in your department	haven_labelled	1. Not at all, 7. Extremely	105	0.7169811	1	5	7	5.037594	1.726185	2	<U+2581><U+2582><U+2583><U+2583><U+2581><U+2587><U+2587><U+2587>
comfort_2	With other psychology researchers at conferences or other professional gatherings outside of your department	haven_labelled	1. Not at all, 7. Extremely	105	0.7169811	1	5	7	4.853383	1.647505	2	<U+2581><U+2582><U+2585><U+2585><U+2581><U+2587><U+2587><U+2586>
comfort_3	With other psychology researchers online	haven_labelled	1. Not at all, 7. Extremely	106	0.7142857	1	4	7	4.200000	1.952465	2	<U+2585><U+2585><U+2586><U+2586><U+2581><U+2585><U+2587><U+2585>
comfort_4	With other psychology researchers in general	haven_labelled	1. Not at all, 7. Extremely	106	0.7142857	1	5	7	4.713208	1.630909	2	<U+2581><U+2582><U+2585><U+2586><U+2581><U+2587><U+2587><U+2585>

Scale: positive

Overview

Reliability: .

Missing: 169.

Likert plot of scale positive items

Distribution of scale positive

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	experience_1, experience_2, experience_3, experience_4, experience_5, experience_8, experience_12, experience_13, experience_14, experience_15, experience_17 & experience_18
Observations:	202
Positive correlations:	58
Number of correlations:	66
Percentage positive correlations:	88

Estimates assuming interval level

Omega (total):	0.92
Omega (hierarchical):	0.85
Revelle’s Omega (total):	0.92
Greatest Lower Bound (GLB):	0.92
Coefficient H:	0.93
Coefficient Alpha:	0.88

(Estimates assuming ordinal level not computed, as at least one item seems to have more than 8 levels; the highest number of distinct levels is 11 and the highest range is 11. This last number needs to be lower than 9 for the polychoric function to work. If this is unexpected, you may want to check for outliers.)

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

6.124, 1.188, 0.824, 0.702, 0.69, 0.524, 0.418, 0.4, 0.361, 0.316, 0.238 & 0.214

Factor analysis (reproducing only shared variance)

	ML1	ML2
experience_1	0.795	0.007
experience_2	0.834	-0.019
experience_3	0.753	-0.025
experience_4	0.670	0.305
experience_5	-0.119	0.337
experience_8	0.435	0.065
experience_12	0.814	-0.192
experience_13	0.731	0.322
experience_14	0.779	-0.155
experience_15	0.530	0.135
experience_17	0.736	-0.366
experience_18	0.728	0.293

Component analysis (reproducing full covariance matrix)

	TC1	TC2
experience_1	0.813	-0.070
experience_2	0.841	-0.049
experience_3	0.781	-0.041
experience_4	0.750	0.248
experience_5	0.004	0.867
experience_8	0.498	0.081
experience_12	0.784	-0.230
experience_13	0.803	0.249
experience_14	0.778	-0.163
experience_15	0.614	0.206
experience_17	0.668	-0.404
experience_18	0.794	0.163

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
experience_1	5.2970297029703	5	5.19491650657603	2.27923594798258	3	0.160366481686156	0	3	7	10	0.00519892473665971	-0.462694819844098	0.0693069306930693	202	202
experience_2	5.12871287128713	5	4.63011674301759	2.1517706065047	2	0.151398051555951	0	3	7	10	-0.247029645366685	0.0796759268004615	0.0965346534653465	202	202
experience_3	5.47029702970297	5	4.74786956307571	2.17896066120426	3	0.153311137128721	0	3	7	10	0.0172640163242719	-0.367607196381161	0.0816831683168317	202	202
experience_4	5.07920792079208	5	6.72006305108123	2.59230844057593	3	0.182394185397284	0	2	7	10	-0.138185079780887	-0.473587719563758	0.0767326732673267	202	202
experience_5	4.93069306930693	5	8.1941776267179	2.86254740165432	4	0.201408132347806	0	2	7	10	-0.297231141797095	-0.91875742184187	0.0668316831683168	202	202
experience_8	5.36138613861386	6	5.56526772080193	2.35908196568113	3	0.165984427887075	0	3	7	10	-0.162008621445725	-0.451448332004855	0.0792079207920792	202	202
experience_12	5.03960396039604	5	4.58548839958623	2.14137535233462	3	0.15066664402486	0	3	7	10	0.0125276015260756	-0.146898603219973	0.0792079207920792	202	202
experience_13	5.53465346534653	6	5.08585783951529	2.25518465752038	3	0.158674238794476	0	4	8	10	-0.22980080909168	-0.27012306619847	0.0816831683168317	202	202
experience_14	4.81188118811881	5	4.2828432096941	2.06950313111483	3	0.145609732186405	0	3	7	10	0.295466331263207	-0.175594503186639	0.0891089108910891	202	202
experience_15	3.65346534653465	3	5.73006255849466	2.39375490777453	3	0.168424007579625	0	1	5	10	0.339145224331557	-0.548920871484198	0.0829207920792079	202	202
experience_17	5.54455445544554	6	4.44825378060194	2.10908837666939	3	0.148394940344378	1	4	7	10	0.0239541171745921	-0.355290688181978	0.0841584158415842	202	202
experience_18	5.44059405940594	6	4.91436382444215	2.21683644512674	3	0.15597606798598	0	4	8	10	-0.18999117175152	-0.425621422397793	0.0841584158415842	202	202

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
experience_1	Collaborative	haven_labelled	0. Not at all, 10. Extremely	151	0.5929919	0	5	10	5.313636	2.290898	2	<U+2581><U+2582><U+2582><U+2587><U+2583><U+2583><U+2582><U+2582>
experience_2	Supportive	haven_labelled	0. Not at all, 10. Extremely	154	0.5849057	0	5	10	5.092166	2.217519	2	<U+2582><U+2581><U+2582><U+2587><U+2585><U+2583><U+2582><U+2582>
experience_3	Open	haven_labelled	0. Not at all, 10. Extremely	150	0.5956873	0	5	10	5.502262	2.185956	2	<U+2581><U+2581><U+2582><U+2587><U+2583><U+2583><U+2582><U+2582>
experience_4	Exciting	haven_labelled	0. Not at all, 10. Extremely	153	0.5876011	0	5	10	5.105505	2.601465	2	<U+2582><U+2582><U+2582><U+2587><U+2583><U+2583><U+2582><U+2583>
experience_5	Competitive	haven_labelled	0. Not at all, 10. Extremely	158	0.5741240	0	5	10	5.009390	2.908982	2	<U+2587><U+2582><U+2583><U+2587><U+2585><U+2587><U+2582><U+2585>
experience_8	Easy to follow	haven_labelled	0. Not at all, 10. Extremely	153	0.5876011	0	6	10	5.357798	2.330020	2	<U+2582><U+2583><U+2585><U+2587><U+2586><U+2586><U+2583><U+2582>
experience_12	Friendly	haven_labelled	0. Not at all, 10. Extremely	152	0.5902965	0	5	10	5.105023	2.167932	2	<U+2581><U+2581><U+2583><U+2587><U+2583><U+2583><U+2582><U+2582>
experience_13	Helpful	haven_labelled	0. Not at all, 10. Extremely	152	0.5902965	0	6	10	5.511416	2.232703	2	<U+2581><U+2582><U+2582><U+2587><U+2586><U+2585><U+2583><U+2582>
experience_14	Comfortable	haven_labelled	0. Not at all, 10. Extremely	151	0.5929919	0	5	10	4.827273	2.121252	2	<U+2581><U+2582><U+2583><U+2587><U+2583><U+2583><U+2581><U+2581>
experience_15	Diverse	haven_labelled	0. Not at all, 10. Extremely	157	0.5768194	0	3	10	3.672897	2.440948	2	<U+2587><U+2583><U+2585><U+2587><U+2582><U+2582><U+2581><U+2581>
experience_17	Respectful	haven_labelled	0. Not at all, 10. Extremely	150	0.5956873	1	6	10	5.502262	2.092464	2	<U+2583><U+2583><U+2583><U+2586><U+2587><U+2586><U+2582><U+2583>
experience_18	Productive	haven_labelled	0. Not at all, 10. Extremely	153	0.5876011	0	6	10	5.454128	2.214366	2	<U+2582><U+2582><U+2583><U+2587><U+2586><U+2585><U+2583><U+2582>

Scale: negative

Overview

Reliability: .

Missing: 173.

Likert plot of scale negative items

Distribution of scale negative

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	experience_6, experience_7, experience_9, experience_10, experience_11 & experience_16
Observations:	198
Positive correlations:	15
Number of correlations:	15
Percentage positive correlations:	100

Estimates assuming interval level

Omega (total):	0.91
Omega (hierarchical):	0.75
Revelle’s Omega (total):	0.91
Greatest Lower Bound (GLB):	0.86
Coefficient H:	0.91
Coefficient Alpha:	0.82

(Estimates assuming ordinal level not computed, as at least one item seems to have more than 8 levels; the highest number of distinct levels is 11 and the highest range is 11. This last number needs to be lower than 9 for the polychoric function to work. If this is unexpected, you may want to check for outliers.)

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

3.252, 0.983, 0.688, 0.528, 0.356 & 0.192

Factor analysis (reproducing only shared variance)

	ML1
experience_6	0.851
experience_7	0.913
experience_9	0.358
experience_10	0.518
experience_11	0.681
experience_16	0.588

Component analysis (reproducing full covariance matrix)

	PC1
experience_6	0.827
experience_7	0.870
experience_9	0.466
experience_10	0.667
experience_11	0.794
experience_16	0.720

Item descriptives

	mean	median	var	sd	IQR	se	q1	q3	max	skew	kurt	dip	n	valid
experience_6	3.65151515151515	3	7.09113982464236	2.66291941760211	3	0.189245442476678	1	5	10	0.282378729084326	-0.825604003439775	0.0833333333333333	198	198
experience_7	3.84343434343434	4	8.21394144490591	2.86599746072915	5	0.203677570566938	1	6	10	0.256994179467568	-0.991125445055775	0.071969696969697	198	198
experience_9	3.65151515151515	3	6.13682510383018	2.47726161392578	4	0.176051316896411	1	6	10	0.367425585666395	-0.610690002866982	0.0732323232323232	198	198
experience_10	5.38888888888889	6	7.99520586576424	2.82757950653279	4	0.200947325448412	3	8	10	-0.331217822922146	-0.63195577911501	0.0757575757575758	198	198
experience_11	5.2979797979798	6	8.42344767471671	2.90231763849457	5	0.206258733206189	3	8	10	-0.372869193717614	-0.834944995422701	0.0656565656565657	198	198
experience_16	4.71717171717172	5	6.57950058965287	2.56505372061734	4	0.18229043024208	2	7	10	-0.0406384777760869	-0.528260998578667	0.0782828282828283	198	198

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	median	max	mean	sd	n_value_labels	hist
experience_6	Hostile	haven_labelled	0. Not at all, 10. Extremely	156	0.5795148	3	10	3.553488	2.636139	2	<U+2587><U+2585><U+2585><U+2587><U+2582><U+2582><U+2582><U+2581>
experience_7	Aggressive	haven_labelled	0. Not at all, 10. Extremely	157	0.5768194	3	10	3.733645	2.824954	2	<U+2587><U+2583><U+2583><U+2586><U+2583><U+2582><U+2582><U+2581>
experience_9	Difficult to follow	haven_labelled	0. Not at all, 10. Extremely	158	0.5741240	3	10	3.666667	2.468035	2	<U+2587><U+2585><U+2586><U+2587><U+2585><U+2582><U+2582><U+2581>
experience_10	Status-oriented	haven_labelled	0. Not at all, 10. Extremely	164	0.5579515	6	10	5.415459	2.842355	2	<U+2585><U+2582><U+2583><U+2587><U+2586><U+2585><U+2585><U+2585>
experience_11	Cliquey	haven_labelled	0. Not at all, 10. Extremely	161	0.5660377	6	10	5.233333	2.894944	2	<U+2586><U+2582><U+2583><U+2587><U+2585><U+2586><U+2585><U+2585>
experience_16	Stressful	haven_labelled	0. Not at all, 10. Extremely	157	0.5768194	5	10	4.616822	2.558773	2	<U+2583><U+2583><U+2583><U+2587><U+2585><U+2585><U+2581><U+2582>

Scale: entity

Overview

Reliability: .

Missing: 115.

Likert plot of scale entity items

Distribution of scale entity

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	entity_1 & entity_2
Observations:	256
Positive correlations:	1
Number of correlations:	1
Percentage positive correlations:	100

Estimates assuming interval level

Estimates for two-item measures

Spearman Brown coefficient:	0.27
Coefficient Alpha:	0.27
Pearson Correlation:	0.16

Eigen values

1.157 & 0.843

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	NA	valid
entity_1	4.9296875	5	2.53621323529412	1.59254928818361	2	0.0995343305114755	1	3.5	6	7	-0.565109033169177	-0.30273311971762	0.099609375	256	0	256
entity_2	3.32421875	3	2.13368566176471	1.46071409309444	2	0.0912946308184024	1	2	4	7	0.450272711171177	-0.0578615779584348	0.1171875	256	0	256

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
entity_1	Within an entitative group?	haven_labelled	1. Not at all, 7. Extremely	114	0.6927224	1	5	7	4.937743	1.594674	2	<U+2581><U+2582><U+2582><U+2586><U+2581><U+2587><U+2586><U+2586>
entity_2	Between entitative groups?	haven_labelled	1. Not at all, 7. Extremely	115	0.6900270	1	3	7	3.324219	1.460714	2	<U+2583><U+2586><U+2587><U+2587><U+2581><U+2583><U+2581><U+2581>

Scale: repConf

Overview

Reliability: .

Missing: 99.

Likert plot of scale repConf items

Distribution of scale repConf

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	rep_1_1, rep_1_2, rep_1_3 & rep_1_4
Observations:	272
Positive correlations:	6
Number of correlations:	6
Percentage positive correlations:	100

Estimates assuming interval level

Omega (total):	0.88
Omega (hierarchical):	0.69
Revelle’s Omega (total):	0.88
Greatest Lower Bound (GLB):	0.88
Coefficient H:	0.87
Coefficient Alpha:	0.81

(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

2.568, 0.831, 0.332 & 0.269

Factor analysis (reproducing only shared variance)

	ML1
rep_1_1	0.895
rep_1_2	0.720
rep_1_3	0.674
rep_1_4	0.578

Component analysis (reproducing full covariance matrix)

	PC1
rep_1_1	0.864
rep_1_2	0.742
rep_1_3	0.831
rep_1_4	0.762

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
rep_1_1	3.55882352941176	4	0.705014108964619	0.839651182911463	1	0.050911331114982	1	3	5	5	-0.56373919298193	-0.0569978761336583	0.130514705882353	272	272
rep_1_2	3.49632352941176	4	0.737993813761667	0.859065663242145	1	0.0520885068954214	1	3	5	5	-0.445884675463495	-0.138973765821954	0.152573529411765	272	272
rep_1_3	3.55147058823529	4	0.661547644888214	0.81335579231245	1	0.0493169388663555	1	3	5	5	-0.457491402332683	0.0334593430608312	0.15625	272	272
rep_1_4	3.49264705882353	4	0.693672672020838	0.832870141150971	1	0.0505001700645374	1	3	5	5	-0.478413456548778	-0.00121511859451121	0.159926470588235	272	272

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
rep_1_1	Influential research findings	haven_labelled	1. Very low confidence, 2. Low confidence, 3. Neither high nor low confidence, 4. Moderate confidence, 5. High confidence	98	0.7358491	1	4	5	3.560440	0.8385315	5	<U+2581><U+2582><U+2581><U+2583><U+2581><U+2587><U+2581><U+2581>
rep_1_2	Canonical research findings	haven_labelled	1. Very low confidence, 2. Low confidence, 3. Neither high nor low confidence, 4. Moderate confidence, 5. High confidence	99	0.7331536	1	4	5	3.496323	0.8590657	5	<U+2581><U+2582><U+2581><U+2585><U+2581><U+2587><U+2581><U+2582>
rep_1_3	Recent research findings	haven_labelled	1. Very low confidence, 2. Low confidence, 3. Neither high nor low confidence, 4. Moderate confidence, 5. High confidence	98	0.7358491	1	4	5	3.553114	0.8123130	5	<U+2581><U+2582><U+2581><U+2585><U+2581><U+2587><U+2581><U+2582>
rep_1_4	Latest issues of your field’s top journal	haven_labelled	1. Very low confidence, 2. Low confidence, 3. Neither high nor low confidence, 4. Moderate confidence, 5. High confidence	98	0.7358491	1	4	5	3.494505	0.8319046	5	<U+2581><U+2582><U+2581><U+2585><U+2581><U+2587><U+2581><U+2581>

Scale: integrity

Overview

Reliability: .

Missing: 108.

Likert plot of scale integrity items

Distribution of scale integrity

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	int_1_1, int_1_2, int_1_3, int_1_4, int_1_5, int_2_1, int_2_2, int_2_3, int_2_4 & int_2_5
Observations:	263
Positive correlations:	45
Number of correlations:	45
Percentage positive correlations:	100

Estimates assuming interval level

Omega (total):	0.92
Omega (hierarchical):	0.70
Revelle’s Omega (total):	0.92
Greatest Lower Bound (GLB):	0.95
Coefficient H:	0.90
Coefficient Alpha:	0.89

(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

5.138, 1.328, 0.807, 0.724, 0.514, 0.476, 0.33, 0.249, 0.245 & 0.188

Factor analysis (reproducing only shared variance)

	ML1	ML2
int_1_1	0.707	0.067
int_1_2	0.863	0.014
int_1_3	0.524	0.190
int_1_4	0.853	-0.033
int_1_5	0.688	-0.039
int_2_1	0.158	0.553
int_2_2	0.021	0.819
int_2_3	0.036	0.768
int_2_4	0.047	0.775
int_2_5	-0.182	0.671

Component analysis (reproducing full covariance matrix)

	TC1	TC2
int_1_1	0.783	0.052
int_1_2	0.869	0.029
int_1_3	0.646	0.141
int_1_4	0.865	-0.010
int_1_5	0.755	-0.044
int_2_1	0.270	0.540
int_2_2	0.148	0.758
int_2_3	0.133	0.762
int_2_4	0.114	0.783
int_2_5	-0.260	0.859

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
int_1_1	1.79087452471483	2	0.372130148317998	0.610024711235535	1	0.0376157351347309	1	1	3	3	0.145252021672122	-0.494228434941472	0.155893536121673	263	263
int_1_2	1.61977186311787	2	0.389225901953386	0.62387971753647	1	0.038470071422601	1	1	3	3	0.487523901306244	-0.640981000515971	0.228136882129278	263	263
int_1_3	1.66159695817491	2	0.407947058311323	0.63870733384808	1	0.0393843814129738	1	1	3	3	0.43838954422186	-0.680698517561674	0.214828897338403	263	263
int_1_4	1.63498098859316	2	0.362435782079935	0.602026396497641	1	0.0371225379196616	1	1	3	3	0.366201292599991	-0.663694285579543	0.214828897338403	263	263
int_1_5	1.45247148288973	1	0.263953792122602	0.513764335199128	1	0.0316800660671265	1	NA	2	3	0.361996525802919	-1.46939222327506	0.218631178707224	263	263
int_2_1	1.4638783269962	1	0.310713145444519	0.557416491902167	1	0.0343717733608779	1	NA	2	3	0.676380154135319	-0.599504504126857	0.201520912547529	263	263
int_2_2	1.3041825095057	1	0.242997707021159	0.492947975978357	1	0.0303964743691246	1	NA	2	3	1.23615510110959	0.375297772287927	0.136882129277567	263	263
int_2_3	1.29277566539924	1	0.246016312077323	0.496000314593976	1	0.0305846896312146	1	NA	2	3	1.3800790528495	0.877996965927718	0.127376425855513	263	263
int_2_4	1.28136882129278	1	0.241140103909674	0.49106018359227	1	0.0302800681038102	1	NA	2	3	1.45547228315005	1.12291817499834	0.121673003802281	263	263
int_2_5	1.08365019011407	1	0.0769454038835515	0.277390345692765	0	0.0171046214691485	1	NA	2	2	3.02490866318568	7.20480535346754	0.0418250950570342	263	263

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
int_1_1	Mild issues/questionable research practices - In research from other institutions?	haven_labelled	1. Never, 2. Once or Twice, 3. Often	103	0.7223720	1	2	3	1.791045	0.6067612	3	<U+2585><U+2581><U+2581><U+2587><U+2581><U+2581><U+2581><U+2582>
int_1_2	Mild issues/questionable research practices - In research at your institutions?	haven_labelled	1. Never, 2. Once or Twice, 3. Often	103	0.7223720	1	2	3	1.611940	0.6230341	3	<U+2587><U+2581><U+2581><U+2587><U+2581><U+2581><U+2581><U+2581>
int_1_3	Mild issues/questionable research practices - In graduate student research at your institution?	haven_labelled	1. Never, 2. Once or Twice, 3. Often	106	0.7142857	1	2	3	1.656604	0.6388642	3	<U+2587><U+2581><U+2581><U+2587><U+2581><U+2581><U+2581><U+2582>
int_1_4	Mild issues/questionable research practices - Of senior colleagues and/or collaborators?	haven_labelled	1. Never, 2. Once or Twice, 3. Often	103	0.7223720	1	2	3	1.634328	0.6063465	3	<U+2587><U+2581><U+2581><U+2587><U+2581><U+2581><U+2581><U+2581>
int_1_5	Mild issues/questionable research practices - In your own research?	haven_labelled	1. Never, 2. Once or Twice, 3. Often	103	0.7223720	1	1	3	1.451493	0.5133769	3	<U+2587><U+2581><U+2581><U+2586><U+2581><U+2581><U+2581><U+2581>
int_2_1	Serious issues/scientific misconducts - In research from other institutions?	haven_labelled	1. Never, 2. Once or Twice, 3. Often	103	0.7223720	1	1	3	1.466418	0.5565334	3	<U+2587><U+2581><U+2581><U+2586><U+2581><U+2581><U+2581><U+2581>
int_2_2	Serious issues/scientific misconducts - In research at your institutions?	haven_labelled	1. Never, 2. Once or Twice, 3. Often	103	0.7223720	1	1	3	1.302239	0.4915719	3	<U+2587><U+2581><U+2581><U+2583><U+2581><U+2581><U+2581><U+2581>
int_2_3	Serious issues/scientific misconducts - In graduate student research at your institution?	haven_labelled	1. Never, 2. Once or Twice, 3. Often	107	0.7115903	1	1	3	1.291667	0.4953843	3	<U+2587><U+2581><U+2581><U+2583><U+2581><U+2581><U+2581><U+2581>
int_2_4	Serious issues/scientific misconducts - Of senior colleagues and/or collaborators?	haven_labelled	1. Never, 2. Once or Twice, 3. Often	103	0.7223720	1	1	3	1.283582	0.4913017	3	<U+2587><U+2581><U+2581><U+2583><U+2581><U+2581><U+2581><U+2581>
int_2_5	Serious issues/scientific misconducts - In your own research?	haven_labelled	1. Never, 2. Once or Twice, 3. Often	104	0.7196765	1	1	2	1.082397	0.2754850	3	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581>

Scale: intMild

Overview

Reliability: .

Missing: 106.

Likert plot of scale intMild items

Distribution of scale intMild

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	int_1_1, int_1_2, int_1_3, int_1_4 & int_1_5
Observations:	265
Positive correlations:	10
Number of correlations:	10
Percentage positive correlations:	100

Estimates assuming interval level

Omega (total):	0.89
Omega (hierarchical):	0.82
Revelle’s Omega (total):	0.89
Greatest Lower Bound (GLB):	0.89
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

3.272, 0.611, 0.529, 0.323 & 0.264

Factor analysis (reproducing only shared variance)

	ML1
int_1_1	0.739
int_1_2	0.881
int_1_3	0.652
int_1_4	0.827
int_1_5	0.669

Component analysis (reproducing full covariance matrix)

	PC1
int_1_1	0.798
int_1_2	0.889
int_1_3	0.739
int_1_4	0.862
int_1_5	0.746

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
int_1_1	1.78867924528302	2	0.371841052029731	0.609787710625371	1	0.037458961294252	1	1	3	3	0.14702106443572	-0.496637596020182	0.156603773584906	265	265
int_1_2	1.61509433962264	2	0.389165237278445	0.623831096754919	1	0.0383216396465715	1	1	3	3	0.499096030384462	-0.636118970708686	0.230188679245283	265	265
int_1_3	1.65660377358491	2	0.408147512864494	0.638864236645388	1	0.0392451180891112	1	1	3	3	0.44987118439655	-0.678148356912257	0.216981132075472	265	265
int_1_4	1.63018867924528	2	0.362721555174385	0.602263692392614	1	0.0369967645283168	1	1	3	3	0.378083971303195	-0.66409982409902	0.216981132075472	265	265
int_1_5	1.44905660377358	1	0.26349342481418	0.51331610613167	1	0.0315327577388903	1	NA	2	3	0.375057053481523	-1.46128317074733	0.216981132075472	265	265

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
int_1_1	Mild issues/questionable research practices - In research from other institutions?	haven_labelled	1. Never, 2. Once or Twice, 3. Often	103	0.7223720	1	2	3	1.791045	0.6067612	3	<U+2585><U+2581><U+2581><U+2587><U+2581><U+2581><U+2581><U+2582>
int_1_2	Mild issues/questionable research practices - In research at your institutions?	haven_labelled	1. Never, 2. Once or Twice, 3. Often	103	0.7223720	1	2	3	1.611940	0.6230341	3	<U+2587><U+2581><U+2581><U+2587><U+2581><U+2581><U+2581><U+2581>
int_1_3	Mild issues/questionable research practices - In graduate student research at your institution?	haven_labelled	1. Never, 2. Once or Twice, 3. Often	106	0.7142857	1	2	3	1.656604	0.6388642	3	<U+2587><U+2581><U+2581><U+2587><U+2581><U+2581><U+2581><U+2582>
int_1_4	Mild issues/questionable research practices - Of senior colleagues and/or collaborators?	haven_labelled	1. Never, 2. Once or Twice, 3. Often	103	0.7223720	1	2	3	1.634328	0.6063465	3	<U+2587><U+2581><U+2581><U+2587><U+2581><U+2581><U+2581><U+2581>
int_1_5	Mild issues/questionable research practices - In your own research?	haven_labelled	1. Never, 2. Once or Twice, 3. Often	103	0.7223720	1	1	3	1.451493	0.5133769	3	<U+2587><U+2581><U+2581><U+2586><U+2581><U+2581><U+2581><U+2581>

Scale: intSerious

Overview

Reliability: .

Missing: 108.

Likert plot of scale intSerious items

Distribution of scale intSerious

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	int_2_1, int_2_2, int_2_3, int_2_4 & int_2_5
Observations:	263
Positive correlations:	10
Number of correlations:	10
Percentage positive correlations:	100

Estimates assuming interval level

Omega (total):	0.88
Omega (hierarchical):	0.83
Revelle’s Omega (total):	0.88
Greatest Lower Bound (GLB):	0.85
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

3.121, 0.744, 0.466, 0.383 & 0.286

Factor analysis (reproducing only shared variance)

	ML1
int_2_1	0.658
int_2_2	0.841
int_2_3	0.770
int_2_4	0.816
int_2_5	0.547

Component analysis (reproducing full covariance matrix)

	PC1
int_2_1	0.733
int_2_2	0.859
int_2_3	0.830
int_2_4	0.854
int_2_5	0.654

Item descriptives

	mean	median	var	sd	IQR	se	min	q1	q3	max	skew	kurt	dip	n	valid
int_2_1	1.4638783269962	1	0.310713145444519	0.557416491902167	1	0.0343717733608779	1	NA	2	3	0.676380154135319	-0.599504504126857	0.201520912547529	263	263
int_2_2	1.3041825095057	1	0.242997707021159	0.492947975978357	1	0.0303964743691246	1	NA	2	3	1.23615510110959	0.375297772287927	0.136882129277567	263	263
int_2_3	1.29277566539924	1	0.246016312077323	0.496000314593976	1	0.0305846896312146	1	NA	2	3	1.3800790528495	0.877996965927718	0.127376425855513	263	263
int_2_4	1.28136882129278	1	0.241140103909674	0.49106018359227	1	0.0302800681038102	1	NA	2	3	1.45547228315005	1.12291817499834	0.121673003802281	263	263
int_2_5	1.08365019011407	1	0.0769454038835515	0.277390345692765	0	0.0171046214691485	1	NA	2	2	3.02490866318568	7.20480535346754	0.0418250950570342	263	263

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
int_2_1	Serious issues/scientific misconducts - In research from other institutions?	haven_labelled	1. Never, 2. Once or Twice, 3. Often	103	0.7223720	1	1	3	1.466418	0.5565334	3	<U+2587><U+2581><U+2581><U+2586><U+2581><U+2581><U+2581><U+2581>
int_2_2	Serious issues/scientific misconducts - In research at your institutions?	haven_labelled	1. Never, 2. Once or Twice, 3. Often	103	0.7223720	1	1	3	1.302239	0.4915719	3	<U+2587><U+2581><U+2581><U+2583><U+2581><U+2581><U+2581><U+2581>
int_2_3	Serious issues/scientific misconducts - In graduate student research at your institution?	haven_labelled	1. Never, 2. Once or Twice, 3. Often	107	0.7115903	1	1	3	1.291667	0.4953843	3	<U+2587><U+2581><U+2581><U+2583><U+2581><U+2581><U+2581><U+2581>
int_2_4	Serious issues/scientific misconducts - Of senior colleagues and/or collaborators?	haven_labelled	1. Never, 2. Once or Twice, 3. Often	103	0.7223720	1	1	3	1.283582	0.4913017	3	<U+2587><U+2581><U+2581><U+2583><U+2581><U+2581><U+2581><U+2581>
int_2_5	Serious issues/scientific misconducts - In your own research?	haven_labelled	1. Never, 2. Once or Twice, 3. Often	104	0.7196765	1	1	2	1.082397	0.2754850	3	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581>

Scale: rep_2

Overview

Reliability: .

Missing: 0.

Likert plot of scale rep_2 items

Distribution of scale rep_2

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Dataframe:	res$dat
Items:	rep_2_1, rep_2_2, rep_2_3, rep_2_4, rep_2_5, rep_2_6, rep_2_7, rep_2_8 & rep_2_9
Observations:	371
Positive correlations:	24
Number of correlations:	36
Percentage positive correlations:	67

Estimates assuming interval level

Omega (total):	0.73
Omega (hierarchical):	0.47
Revelle’s Omega (total):	0.73
Greatest Lower Bound (GLB):	0.73
Coefficient H:	0.73
Coefficient Alpha:	0.64

(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

2.55, 1.119, 1.114, 0.929, 0.873, 0.776, 0.615, 0.564 & 0.46

Factor analysis (reproducing only shared variance)

	ML2	ML1	ML3
rep_2_1	0.219	0.089	0.267
rep_2_2	0.413	0.038	0.312
rep_2_3	0.626	0.128	-0.060
rep_2_4	0.722	-0.073	0.007
rep_2_5	0.003	0.997	0.000
rep_2_6	0.015	0.307	0.367
rep_2_7	-0.048	-0.045	0.399
rep_2_8	0.044	-0.047	-0.137
rep_2_9	-0.048	0.106	-0.099

Component analysis (reproducing full covariance matrix)

	TC1	TC2	TC3
rep_2_1	0.351	0.360	-0.140
rep_2_2	0.614	0.240	-0.079
rep_2_3	0.756	0.061	0.056
rep_2_4	0.802	-0.065	0.006
rep_2_5	0.247	0.645	0.021
rep_2_6	0.083	0.732	-0.022
rep_2_7	-0.181	0.612	0.071
rep_2_8	0.178	-0.256	0.724
rep_2_9	-0.142	0.244	0.754

Item descriptives

	mean	var	sd	IQR	se	q1	q3	max	skew	kurt	dip	n	valid
rep_2_1	0.307277628032345	0.213433379471115	0.461988505778137	1	0.0239852481320183	NA	1	1	0.838838781683588	-1.30340518383503	0.153638814016173	371	371
rep_2_2	0.366576819407008	0.232825817731478	0.482520277015876	1	0.0250512045823797	NA	1	1	0.556023644407386	-1.70003157114474	0.183288409703504	371	371
rep_2_3	0.417789757412399	0.243898885408319	0.493861200549627	1	0.0256399959951555	NA	1	1	0.334733024041072	-1.89821606247463	0.208894878706199	371	371
rep_2_4	0.223719676549865	0.174138559044219	0.417299124183384	0	0.02166509104367	NA	1	1	1.33131253664317	-0.228869887763615	0.111859838274933	371	371
rep_2_5	0.390835579514825	0.238726597217163	0.4885965587447	1	0.0253666694114027	NA	1	1	0.449270857915825	-1.80793123835233	0.195417789757412	371	371
rep_2_6	0.261455525606469	0.193618416259926	0.440020927070436	1	0.0228447482720134	NA	1	1	1.09011814492901	-0.816070938521698	0.130727762803235	371	371
rep_2_7	0.0269541778975741	0.026298535732498	0.162168232809321	0	0.0084193551450183	NA	1	1	5.86563407466848	32.5812768232464	0.0134770889487871	371	371
rep_2_8	0.0431266846361186	0.0413783055292489	0.203416581254452	0	0.0105608626936229	NA	1	1	4.51634365953029	18.4970469023046	0.0215633423180593	371	371
rep_2_9	0.132075471698113	0.11494135645079	0.339030022934239	0	0.0176015617760558	NA	1	1	2.18221794037836	2.77701665755518	0.0660377358490566	371	371

Scattermatrix

Scatterplot

Summary statistics

name	label	data_type	value_labels	complete_rate	max	mean	sd	n_value_labels	hist
rep_2_1	Replication failure - Outdated methods	haven_labelled	0. No, 1. Yes	1	1	0.3072776	0.4619885	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2583>
rep_2_2	Replication failure - Low quality data	haven_labelled	0. No, 1. Yes	1	1	0.3665768	0.4825203	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2585>
rep_2_3	Replication failure - Lack of external validity	haven_labelled	0. No, 1. Yes	1	1	0.4177898	0.4938612	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2586>
rep_2_4	Replication failure - Lack of internal validity	haven_labelled	0. No, 1. Yes	1	1	0.2237197	0.4172991	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2582>
rep_2_5	Replication failure - Publication bias	haven_labelled	0. No, 1. Yes	1	1	0.3908356	0.4885966	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2585>
rep_2_6	Replication failure - Author bias	haven_labelled	0. No, 1. Yes	1	1	0.2614555	0.4400209	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2583>
rep_2_7	Replication failure - Fraud	haven_labelled	0. No, 1. Yes	1	1	0.0269542	0.1621682	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581>
rep_2_8	Replication failure - I don’t think there is a replication problem	haven_labelled	0. No, 1. Yes	1	1	0.0431267	0.2034166	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581>
rep_2_9	Replication failure - Other explanation	haven_labelled	0. No, 1. Yes	1	1	0.1320755	0.3390300	2	<U+2587><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581>

rep_2_o

When studies in your field do not replicate, what do you think are the primary explanations? - Text

Distribution

Distribution of values for rep_2_o

322 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
rep_2_o	When studies in your field do not replicate, what do you think are the primary explanations? - Text	character	322	0.1320755	49	0	7	315	0

beh_1

What is the likelihood that you will pre-register hypotheses or analyses online in advance of your next new empirical project?

Distribution

Distribution of values for beh_1

111 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
beh_1	What is the likelihood that you will pre-register hypotheses or analyses online in advance of your next new empirical project?	numeric	111	0.7008086	0	30	100	38.92308	30.01277	<U+2587><U+2585><U+2583><U+2583><U+2582>

beh_2

What is the likelihood that you will post the data or code online for your next completed empirical project?

Distribution

Distribution of values for beh_2

111 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
beh_2	What is the likelihood that you will post the data or code online for your next completed empirical project?	numeric	111	0.7008086	0	30	100	37.42308	30.13313	<U+2587><U+2583><U+2583><U+2582><U+2582>

beh_3

What is the likelihood that you will post the study instruments online for your next completed empirical project?

Distribution

Distribution of values for beh_3

113 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	hist
beh_3	What is the likelihood that you will post the study instruments online for your next completed empirical project?	numeric	113	0.6954178	0	60	100	53.52713	31.75112	<U+2587><U+2583><U+2585><U+2587><U+2585>

barrier

Specific barriers for EMCP researchers to engaging in open science practices?

Distribution

Distribution of values for barrier

114 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
barrier	Specific barriers for EMCP researchers to engaging in open science practices?	haven_labelled	114	0.6927224	0	1	2	1.18677	0.6875995	3	<U+2582><U+2581><U+2581><U+2587><U+2581><U+2581><U+2581><U+2586>

Value labels

Response choices
name	value
No	0
Yes	1
Maybe	2

barrier_o

What are some specific barriers to engaging in open science practices in ethnic minority/cultural psychology?

Distribution

Distribution of values for barrier_o

203 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
barrier_o	What are some specific barriers to engaging in open science practices in ethnic minority/cultural psychology?	character	203	0.4528302	165	0	3	637	0

opportunity

Specific opportunities for EMCP researchers to engaging in open science practices?

Distribution

Distribution of values for opportunity

116 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
opportunity	Specific opportunities for EMCP researchers to engaging in open science practices?	haven_labelled	116	0.6873315	0	1	2	1.364706	0.678936	3	<U+2582><U+2581><U+2581><U+2587><U+2581><U+2581><U+2581><U+2587>

Value labels

Response choices
name	value
No	0
Yes	1
Maybe	2

opportunity_o

What are some specific opportunities related to open science practices that would improve ethnic minority/cultural psychology?

Distribution

Distribution of values for opportunity_o

240 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
opportunity_o	What are some specific opportunities related to open science practices that would improve ethnic minority/cultural psychology?	character	240	0.3530997	130	0	3	511	0

engagemotiv01

First motivation for engagement in open science practices:

Distribution

Distribution of values for engagemotiv01

170 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
engagemotiv01	First motivation for engagement in open science practices:	character	170	0.541779	185	0	5	245	0

engagemotiv02

Second motivation for engagement in open science practices:

Distribution

Distribution of values for engagemotiv02

191 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
engagemotiv02	Second motivation for engagement in open science practices:	character	191	0.4851752	175	0	4	138	0

engagemotiv03

Third motivation for engagement in open science practices:

Distribution

Distribution of values for engagemotiv03

225 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
engagemotiv03	Third motivation for engagement in open science practices:	character	225	0.393531	140	0	3	201	0

engagebarrier01

First barrier for engagement in open science practices:

Distribution

Distribution of values for engagebarrier01

164 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
engagebarrier01	First barrier for engagement in open science practices:	character	164	0.5579515	189	0	3	601	0

engagebarrier02

Second barrier for engagement in open science practices:

Distribution

Distribution of values for engagebarrier02

198 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
engagebarrier02	Second barrier for engagement in open science practices:	character	198	0.4663073	171	0	3	623	0

engagebarrier03

Third barrier for engagement in open science practices:

Distribution

Distribution of values for engagebarrier03

250 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
engagebarrier03	Third barrier for engagement in open science practices:	character	250	0.3261456	113	0	3	414	0

convomotiv01

First motivation for discussion participation:

Distribution

Distribution of values for convomotiv01

216 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
convomotiv01	First motivation for discussion participation:	character	216	0.4177898	150	0	3	408	0

convomotiv02

Second motivation for discussion participation:

Distribution

Distribution of values for convomotiv02

264 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
convomotiv02	Second motivation for discussion participation:	character	264	0.2884097	106	0	3	137	0

convomotiv03

Third motivation for discussion participation:

Distribution

Distribution of values for convomotiv03

296 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
convomotiv03	Third motivation for discussion participation:	character	296	0.2021563	72	0	2	90	0

convoconcern01

First concern for discussion participation:

Distribution

Distribution of values for convoconcern01

224 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
convoconcern01	First concern for discussion participation:	character	224	0.3962264	136	0	4	499	0

convoconcern02

Second concern for discussion participation:

Distribution

Distribution of values for convoconcern02

288 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
convoconcern02	Second concern for discussion participation:	character	288	0.2237197	77	0	2	277	0

convoconcern03

Third concern for discussion participation:

Distribution

Distribution of values for convoconcern03

313 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
convoconcern03	Third concern for discussion participation:	character	313	0.1563342	49	0	2	134	0

attcheck

Please select occasionally for this question.

Distribution

Distribution of values for attcheck

100 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
attcheck	Please select occasionally for this question.	haven_labelled	100	0.7304582	0	1	1	0.8118081	0.3915885	2	<U+2582><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2587>

Value labels

Response choices
name	value
Incorrect	0
Correct	1

experience_19

Please choose 3

Distribution

Distribution of values for experience_19

128 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	min	median	max	mean	sd	n_value_labels	hist
experience_19	Please choose 3	haven_labelled	128	0.6549865	0	1	1	0.7201646	0.4498448	2	<U+2583><U+2581><U+2581><U+2581><U+2581><U+2581><U+2581><U+2587>

Value labels

Response choices
name	value
Incorrect	0
Correct	1

qrp1_4

Why do you think this practice should or should not be used? - Not reporting nonsignificance

Distribution

Distribution of values for qrp1_4

218 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
qrp1_4	Why do you think this practice should or should not be used? - Not reporting nonsignificance	character	218	0.4123989	153	0	3	1099	0

qrp2_4

Why do you think this practice should or should not be used? - Not reporting nonsignificance (covariate)

Distribution

Distribution of values for qrp2_4

230 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
qrp2_4	Why do you think this practice should or should not be used? - Not reporting nonsignificance (covariate)	character	230	0.3800539	141	0	9	601	0

qrp3_4

Why do you think this practice should or should not be used? - HARKing

Distribution

Distribution of values for qrp3_4

227 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
qrp3_4	Why do you think this practice should or should not be used? - HARKing	character	227	0.3881402	144	0	9	449	0

qrp4_4

Why do you think this practice should or should not be used? - Not reporting alternative models

Distribution

Distribution of values for qrp4_4

235 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
qrp4_4	Why do you think this practice should or should not be used? - Not reporting alternative models	character	235	0.3665768	136	0	12	1508	0

qrp5_4

Why do you think this practice should or should not be used? - Rounding p-value

Distribution

Distribution of values for qrp5_4

227 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
qrp5_4	Why do you think this practice should or should not be used? - Rounding p-value	character	227	0.3881402	144	0	9	715	0

qrp6_4

Why do you think this practice should or should not be used? - Excluding data

Distribution

Distribution of values for qrp6_4

238 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
qrp6_4	Why do you think this practice should or should not be used? - Excluding data	character	238	0.3584906	133	0	9	822	0

qrp7_4

Why do you think this practice should or should not be used? - Increasing sample

Distribution

Distribution of values for qrp7_4

221 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
qrp7_4	Why do you think this practice should or should not be used? - Increasing sample	character	221	0.4043127	150	0	9	922	0

qrp8_4

Why do you think this practice should or should not be used? - Changing analysis

Distribution

Distribution of values for qrp8_4

243 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
qrp8_4	Why do you think this practice should or should not be used? - Changing analysis	character	243	0.3450135	128	0	9	759	0

qrp9_4

Why do you think this practice should or should not be used? - Not reporting problems

Distribution

Distribution of values for qrp9_4

243 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
qrp9_4	Why do you think this practice should or should not be used? - Not reporting problems	character	243	0.3450135	127	0	6	590	0

qrp10_4

Why do you think this practice should or should not be used? - Imputing data

Distribution

Distribution of values for qrp10_4

241 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
qrp10_4	Why do you think this practice should or should not be used? - Imputing data	character	241	0.3504043	129	0	5	406	0

prrp1_7

Why do you think this practice should or should not be used? - Posting data

Distribution

Distribution of values for prrp1_7

241 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
prrp1_7	Why do you think this practice should or should not be used? - Posting data	character	241	0.3504043	130	0	7	698	0

prrp2_7

Why do you think this practice should or should not be used? - Posting instruments

Distribution

Distribution of values for prrp2_7

242 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
prrp2_7	Why do you think this practice should or should not be used? - Posting instruments	character	242	0.3477089	129	0	15	1103	0

prrp3_7

Why do you think this practice should or should not be used? - Preregistration

Distribution

Distribution of values for prrp3_7

242 missing values.

Summary statistics

name	label	data_type	n_missing	complete_rate	n_unique	empty	min	max	whitespace
prrp3_7	Why do you think this practice should or should not be used? - Preregistration	character	242	0.3477089	129	0	22	604	0

OS Culture Codebook

Linh Nguyen

14-Jan-2021

Metadata

Description

Variables

age

Distribution

Summary statistics

Value labels

gender_f

Distribution

Summary statistics

Value labels

race_f

Distribution

Summary statistics

Value labels

continent

Distribution

Summary statistics

Value labels

career

Distribution

Summary statistics

Value labels

career_o

Distribution

Summary statistics

Scale: lead

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

culture

Distribution

Summary statistics

Value labels

politics

Distribution

Summary statistics

Value labels

c19stress

Distribution

Summary statistics

Value labels

group

Distribution

Summary statistics

Value labels

Scale: agree

Overview

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Estimates assuming interval level

Estimates for two-item measures

Eigen values

Item descriptives

Scattermatrix

Summary statistics

Scale: consci

Overview

Reliability details

Scale diagnosis

Reliability (internal consistency) estimates

Scale structure

Information about this scale

Estimates assuming interval level