R Notebook

Note This is an R markdown document and refers to the data processing step of the manuscript titled “An Exploratory Analysis of the Internal Structure of Test Through a Multi-methods Exploratory Approach of the ASQ:SE in Brazil”, by Luis Anunciação, Jane Squires, Ajay Singh, and J. Landeira-Fernandez. Data and codes are availabe at https://osf.io/z6gwv/.
Feel free to contact me at luisfca@puc-rio.br
Last update: 21 July, 2021 Thank you.

#Packages
pacman::p_load(tidyverse, #enrironment
               psych) #classical test

1 Data processing

1.1 package versions

packageVersion("psych")

[1] ‘2.1.6’

packageVersion("EGANet")

[1] ‘0.9.8’

1.2 Get the raw data

Always load the main dataset

load("https://osf.io/e4m53/download")

cannot open compressed file 'https://osf.io/e4m53/download', probable reason 'Invalid argument'Error in readChar(con, 5L, useBytes = TRUE) : cannot open the connection

1.3 Change vector labels

Note: “dados” and “original” vectors refer to the same dataset. All items that should have been reversed were reversed already.

For this specific paper, change labels

ds_60 <- original_60
ds_48 <- original_48
ds_36 <- original_36
ds_30 <- original_30
ds_24 <- original_24
ds_18 <- original_18
ds_12 <- original_12

backup_60 <- ds_60
backup_48 <- ds_48
backup_36 <- ds_36
backup_30 <- ds_30
backup_24 <- ds_24
backup_18 <- ds_18
backup_12 <- ds_12

Than I’ll remove all the other things

to.remove <- ls()
to.remove <- c(to.remove[!grepl(pattern = "^ds|^backup", to.remove)], "to.remove")
rm(list=to.remove)
#rm(list=setdiff(ls(), c("ds")))

In this project, we are using the 2011 data only.

1.4 Data set 48 months

This ds was not used in this manuscript. However, future analyses will use it.

ds_48 <- ds_48 %>% 
  select(-c(sum_emo, sum_soc)) %>% 
  filter(year == "2011") %>% 
  mutate(score = rowSums(select(., starts_with("q")), na.rm=T))

ds_48 %>% count(year)

1.5 Data set 60 months

This manuscript was used in the manuscript.

ds_60 <- ds_60 %>% 
  select(-c(sum_emo, sum_soc)) %>% 
  filter(year == "2011") %>%
  mutate(score = rowSums(select(., starts_with("q")), na.rm=T))

ds_60 %>% count(year)

1.6 Visual check: Original data (48 months)

ds_48 %>% 
  select(starts_with("q_")) %>% 
  mutate_all(factor) %>% 
  DataExplorer::plot_bar()

1.7 Visual check: Original data (60 months)

ds_60 %>% 
  select(starts_with("q_")) %>% 
  mutate_all(factor) %>% 
  DataExplorer::plot_bar()

1.8 Tabular check (48 months)

ds_48 %>% 
  select(starts_with("q_")) %>% summarytools::freq() %>% kable()

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	11073	88.775756	88.77576	88.775756	88.77576
5	1249	10.013629	98.78939	10.013629	98.78939
10	151	1.210615	100.00000	1.210615	100.00000
	0	NA	NA	0.000000	100.00000
Total	12473	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	8386	67.23322	67.23322	67.23322	67.23322
5	2720	21.80710	89.04033	21.80710	89.04033
10	1367	10.95967	100.00000	10.95967	100.00000
	0	NA	NA	0.00000	100.00000
Total	12473	100.00000	100.00000	100.00000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	10222	81.953018	81.95302	81.953018	81.95302
5	1745	13.990219	95.94324	13.990219	95.94324
10	506	4.056763	100.00000	4.056763	100.00000
	0	NA	NA	0.000000	100.00000
Total	12473	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	10489	84.093642	84.09364	84.093642	84.09364
5	1476	11.833561	95.92720	11.833561	95.92720
10	508	4.072797	100.00000	4.072797	100.00000
	0	NA	NA	0.000000	100.00000
Total	12473	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	10441	83.708811	83.70881	83.708811	83.70881
5	1685	13.509180	97.21799	13.509180	97.21799
10	347	2.782009	100.00000	2.782009	100.00000
	0	NA	NA	0.000000	100.00000
Total	12473	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	9901	79.379460	79.37946	79.379460	79.37946
5	1653	13.252626	92.63209	13.252626	92.63209
10	919	7.367915	100.00000	7.367915	100.00000
	0	NA	NA	0.000000	100.00000
Total	12473	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	9452	75.77968	75.77968	75.77968	75.77968
5	2380	19.08122	94.86090	19.08122	94.86090
10	641	5.13910	100.00000	5.13910	100.00000
	0	NA	NA	0.00000	100.00000
Total	12473	100.00000	100.00000	100.00000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	9286	74.448809	74.44881	74.448809	74.44881
5	2180	17.477752	91.92656	17.477752	91.92656
10	1007	8.073439	100.00000	8.073439	100.00000
	0	NA	NA	0.000000	100.00000
Total	12473	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	11417	91.533713	91.53371	91.533713	91.53371
5	903	7.239638	98.77335	7.239638	98.77335
10	153	1.226650	100.00000	1.226650	100.00000
	0	NA	NA	0.000000	100.00000
Total	12473	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	11711	93.890804	93.89080	93.890804	93.89080
5	553	4.433577	98.32438	4.433577	98.32438
10	209	1.675619	100.00000	1.675619	100.00000
	0	NA	NA	0.000000	100.00000
Total	12473	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	11355	91.03664	91.03664	91.03664	91.03664
5	477	3.82426	94.86090	3.82426	94.86090
10	641	5.13910	100.00000	5.13910	100.00000
	0	NA	NA	0.00000	100.00000
Total	12473	100.00000	100.00000	100.00000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	9672	77.54349	77.54349	77.54349	77.54349
5	2391	19.16941	96.71290	19.16941	96.71290
10	410	3.28710	100.00000	3.28710	100.00000
	0	NA	NA	0.00000	100.00000
Total	12473	100.00000	100.00000	100.00000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	9613	77.070472	77.07047	77.070472	77.07047
5	2619	20.997354	98.06783	20.997354	98.06783
10	241	1.932173	100.00000	1.932173	100.00000
	0	NA	NA	0.000000	100.00000
Total	12473	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	11364	91.108795	91.10880	91.108795	91.10880
5	984	7.889040	98.99784	7.889040	98.99784
10	125	1.002165	100.00000	1.002165	100.00000
	0	NA	NA	0.000000	100.00000
Total	12473	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	11523	92.383549	92.38355	92.383549	92.38355
5	689	5.523932	97.90748	5.523932	97.90748
10	261	2.092520	100.00000	2.092520	100.00000
	0	NA	NA	0.000000	100.00000
Total	12473	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	7917	63.47310	63.47310	63.47310	63.47310
5	2394	19.19346	82.66656	19.19346	82.66656
10	2162	17.33344	100.00000	17.33344	100.00000
	0	NA	NA	0.00000	100.00000
Total	12473	100.00000	100.00000	100.00000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	11259	90.266977	90.26698	90.266977	90.26698
5	895	7.175499	97.44248	7.175499	97.44248
10	319	2.557524	100.00000	2.557524	100.00000
	0	NA	NA	0.000000	100.00000
Total	12473	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	10366	83.107512	83.10751	83.107512	83.10751
5	1707	13.685561	96.79307	13.685561	96.79307
10	400	3.206927	100.00000	3.206927	100.00000
	0	NA	NA	0.000000	100.00000
Total	12473	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	9780	78.409364	78.40936	78.409364	78.40936
5	1865	14.952297	93.36166	14.952297	93.36166
10	828	6.638339	100.00000	6.638339	100.00000
	0	NA	NA	0.000000	100.00000
Total	12473	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	10480	84.021486	84.02149	84.021486	84.02149
5	1694	13.581336	97.60282	13.581336	97.60282
10	299	2.397178	100.00000	2.397178	100.00000
	0	NA	NA	0.000000	100.00000
Total	12473	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	10162	81.471980	81.47198	81.471980	81.47198
5	1930	15.473423	96.94540	15.473423	96.94540
10	381	3.054598	100.00000	3.054598	100.00000
	0	NA	NA	0.000000	100.00000
Total	12473	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	11785	94.484086	94.48409	94.484086	94.48409
5	354	2.838130	97.32222	2.838130	97.32222
10	334	2.677784	100.00000	2.677784	100.00000
	0	NA	NA	0.000000	100.00000
Total	12473	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	12086	96.897298	96.8973	96.897298	96.8973
5	214	1.715706	98.6130	1.715706	98.6130
10	173	1.386996	100.0000	1.386996	100.0000
	0	NA	NA	0.000000	100.0000
Total	12473	100.000000	100.0000	100.000000	100.0000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	8781	70.400064	70.40006	70.400064	70.40006
5	3110	24.933857	95.33392	24.933857	95.33392
10	582	4.666079	100.00000	4.666079	100.00000
	0	NA	NA	0.000000	100.00000
Total	12473	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	10713	85.889521	85.88952	85.889521	85.88952
5	1282	10.278201	96.16772	10.278201	96.16772
10	478	3.832278	100.00000	3.832278	100.00000
	0	NA	NA	0.000000	100.00000
Total	12473	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	9669	77.519442	77.51944	77.519442	77.51944
5	1732	13.885994	91.40544	13.885994	91.40544
10	1072	8.594564	100.00000	8.594564	100.00000
	0	NA	NA	0.000000	100.00000
Total	12473	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	11938	95.710735	95.71074	95.710735	95.71074
5	345	2.765975	98.47671	2.765975	98.47671
10	190	1.523290	100.00000	1.523290	100.00000
	0	NA	NA	0.000000	100.00000
Total	12473	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	7964	63.849916	63.84992	63.849916	63.84992
5	3447	27.635693	91.48561	27.635693	91.48561
10	1062	8.514391	100.00000	8.514391	100.00000
	0	NA	NA	0.000000	100.00000
Total	12473	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	11694	93.7545097	93.75451	93.7545097	93.75451
5	690	5.5319490	99.28646	5.5319490	99.28646
10	89	0.7135412	100.00000	0.7135412	100.00000
	0	NA	NA	0.0000000	100.00000
Total	12473	100.0000000	100.00000	100.0000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	11734	94.075202	94.07520	94.075202	94.07520
5	579	4.642027	98.71723	4.642027	98.71723
10	160	1.282771	100.00000	1.282771	100.00000
	0	NA	NA	0.000000	100.00000
Total	12473	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	9838	78.874369	78.87437	78.874369	78.87437
5	2032	16.291189	95.16556	16.291189	95.16556
10	603	4.834442	100.00000	4.834442	100.00000
	0	NA	NA	0.000000	100.00000
Total	12473	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	10832	86.843582	86.84358	86.843582	86.84358
5	1164	9.332157	96.17574	9.332157	96.17574
10	477	3.824260	100.00000	3.824260	100.00000
	0	NA	NA	0.000000	100.00000
Total	12473	100.000000	100.00000	100.000000	100.00000

1.9 Original data (60 months)

ds_60 %>% 
  select(starts_with("q_")) %>% summarytools::freq() %>% kable()

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	19080	85.441763	85.44176	85.441763	85.44176
5	2937	13.152120	98.59388	13.152120	98.59388
10	314	1.406117	100.00000	1.406117	100.00000
	0	NA	NA	0.000000	100.00000
Total	22331	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	14230	63.72308	63.72308	63.72308	63.72308
5	5214	23.34871	87.07178	23.34871	87.07178
10	2887	12.92822	100.00000	12.92822	100.00000
	0	NA	NA	0.00000	100.00000
Total	22331	100.00000	100.00000	100.00000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	16489	73.839058	73.83906	73.839058	73.83906
5	4835	21.651516	95.49057	21.651516	95.49057
10	1007	4.509426	100.00000	4.509426	100.00000
	0	NA	NA	0.000000	100.00000
Total	22331	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	17370	77.784246	77.78425	77.784246	77.78425
5	3881	17.379428	95.16367	17.379428	95.16367
10	1080	4.836326	100.00000	4.836326	100.00000
	0	NA	NA	0.000000	100.00000
Total	22331	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	18083	80.977117	80.97712	80.977117	80.97712
5	3240	14.508978	95.48610	14.508978	95.48610
10	1008	4.513904	100.00000	4.513904	100.00000
	0	NA	NA	0.000000	100.00000
Total	22331	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	16967	75.979580	75.97958	75.979580	75.97958
5	3500	15.673279	91.65286	15.673279	91.65286
10	1864	8.347141	100.00000	8.347141	100.00000
	0	NA	NA	0.000000	100.00000
Total	22331	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	16652	74.568985	74.56898	74.568985	74.56898
5	4693	21.015628	95.58461	21.015628	95.58461
10	986	4.415387	100.00000	4.415387	100.00000
	0	NA	NA	0.000000	100.00000
Total	22331	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	19763	88.500291	88.50029	88.500291	88.50029
5	2276	10.192110	98.69240	10.192110	98.69240
10	292	1.307599	100.00000	1.307599	100.00000
	0	NA	NA	0.000000	100.00000
Total	22331	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	17211	77.072231	77.07223	77.072231	77.07223
5	3503	15.686713	92.75894	15.686713	92.75894
10	1617	7.241055	100.00000	7.241055	100.00000
	0	NA	NA	0.000000	100.00000
Total	22331	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	20337	91.070709	91.07071	91.070709	91.07071
5	1768	7.917245	98.98795	7.917245	98.98795
10	226	1.012046	100.00000	1.012046	100.00000
	0	NA	NA	0.000000	100.00000
Total	22331	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	21546	96.484707	96.48471	96.484707	96.48471
5	441	1.974833	98.45954	1.974833	98.45954
10	344	1.540460	100.00000	1.540460	100.00000
	0	NA	NA	0.000000	100.00000
Total	22331	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	20431	91.491648	91.49165	91.491648	91.49165
5	822	3.680982	95.17263	3.680982	95.17263
10	1078	4.827370	100.00000	4.827370	100.00000
	0	NA	NA	0.000000	100.00000
Total	22331	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	18227	81.621961	81.62196	81.621961	81.62196
5	3348	14.992611	96.61457	14.992611	96.61457
10	756	3.385428	100.00000	3.385428	100.00000
	0	NA	NA	0.000000	100.00000
Total	22331	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	15083	67.542878	67.54288	67.542878	67.54288
5	6124	27.423761	94.96664	27.423761	94.96664
10	1124	5.033362	100.00000	5.033362	100.00000
	0	NA	NA	0.000000	100.00000
Total	22331	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	15975	71.537325	71.53732	71.537325	71.53732
5	5675	25.413103	96.95043	25.413103	96.95043
10	681	3.049572	100.00000	3.049572	100.00000
	0	NA	NA	0.000000	100.00000
Total	22331	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	13456	60.25704	60.25704	60.25704	60.25704
5	5085	22.77104	83.02808	22.77104	83.02808
10	3790	16.97192	100.00000	16.97192	100.00000
	0	NA	NA	0.00000	100.00000
Total	22331	100.00000	100.00000	100.00000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	19557	87.577807	87.57781	87.577807	87.57781
5	2231	9.990596	97.56840	9.990596	97.56840
10	543	2.431597	100.00000	2.431597	100.00000
	0	NA	NA	0.000000	100.00000
Total	22331	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	20446	91.558820	91.55882	91.558820	91.55882
5	1540	6.896243	98.45506	6.896243	98.45506
10	345	1.544938	100.00000	1.544938	100.00000
	0	NA	NA	0.000000	100.00000
Total	22331	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	17580	78.724643	78.72464	78.724643	78.72464
5	3555	15.919574	94.64422	15.919574	94.64422
10	1196	5.355783	100.00000	5.355783	100.00000
	0	NA	NA	0.000000	100.00000
Total	22331	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	17589	78.764946	78.76495	78.764946	78.76495
5	4100	18.360127	97.12507	18.360127	97.12507
10	642	2.874927	100.00000	2.874927	100.00000
	0	NA	NA	0.000000	100.00000
Total	22331	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	16848	75.446688	75.44669	75.446688	75.44669
5	4443	19.896109	95.34280	19.896109	95.34280
10	1040	4.657203	100.00000	4.657203	100.00000
	0	NA	NA	0.000000	100.00000
Total	22331	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	20668	92.552953	92.55295	92.552953	92.55295
5	893	3.998925	96.55188	3.998925	96.55188
10	770	3.448121	100.00000	3.448121	100.00000
	0	NA	NA	0.000000	100.00000
Total	22331	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	21545	96.48023	96.48023	96.48023	96.48023
5	458	2.05096	98.53119	2.05096	98.53119
10	328	1.46881	100.00000	1.46881	100.00000
	0	NA	NA	0.00000	100.00000
Total	22331	100.00000	100.00000	100.00000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	14573	65.259057	65.25906	65.259057	65.25906
5	6580	29.465765	94.72482	29.465765	94.72482
10	1178	5.275178	100.00000	5.275178	100.00000
	0	NA	NA	0.000000	100.00000
Total	22331	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	18832	84.331199	84.33120	84.331199	84.33120
5	2467	11.047423	95.37862	11.047423	95.37862
10	1032	4.621378	100.00000	4.621378	100.00000
	0	NA	NA	0.000000	100.00000
Total	22331	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	17647	79.024674	79.02467	79.024674	79.02467
5	3206	14.356724	93.38140	14.356724	93.38140
10	1478	6.618602	100.00000	6.618602	100.00000
	0	NA	NA	0.000000	100.00000
Total	22331	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	14105	63.163316	63.16332	63.163316	63.16332
5	6691	29.962832	93.12615	29.962832	93.12615
10	1535	6.873852	100.00000	6.873852	100.00000
	0	NA	NA	0.000000	100.00000
Total	22331	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	20182	90.3766065	90.37661	90.3766065	90.37661
5	1946	8.7143433	99.09095	8.7143433	99.09095
10	203	0.9090502	100.00000	0.9090502	100.00000
	0	NA	NA	0.0000000	100.00000
Total	22331	100.0000000	100.00000	100.0000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	20720	92.785813	92.78581	92.785813	92.78581
5	1345	6.023017	98.80883	6.023017	98.80883
10	266	1.191169	100.00000	1.191169	100.00000
	0	NA	NA	0.000000	100.00000
Total	22331	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	17795	79.687430	79.68743	79.687430	79.68743
5	3425	15.337423	95.02485	15.337423	95.02485
10	1111	4.975147	100.00000	4.975147	100.00000
	0	NA	NA	0.000000	100.00000
Total	22331	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	13290	59.513680	59.51368	59.513680	59.51368
5	7825	35.040974	94.55465	35.040974	94.55465
10	1216	5.445345	100.00000	5.445345	100.00000
	0	NA	NA	0.000000	100.00000
Total	22331	100.000000	100.00000	100.000000	100.00000

	Freq	% Valid	% Valid Cum.	% Total	% Total Cum.
0	18996	85.06560	85.06560	85.06560	85.06560
5	2262	10.12942	95.19502	10.12942	95.19502
10	1073	4.80498	100.00000	4.80498	100.00000
	0	NA	NA	0.00000	100.00000
Total	22331	100.00000	100.00000	100.00000	100.00000

1.10 Reliability of the original data 48 months

ds_48 %>% 
  select(starts_with("q_")) %>% 
  alpha(.)

Reliability analysis   
Call: alpha(x = .)

 

 lower alpha upper     95% confidence boundaries
0.82 0.83 0.83 

 Reliability if an item is dropped:

 Item statistics 

Non missing response frequency for each item
        0    5   10 miss
q_1  0.89 0.10 0.01    0
q_2  0.67 0.22 0.11    0
q_3  0.82 0.14 0.04    0
q_4  0.84 0.12 0.04    0
q_5  0.84 0.14 0.03    0
q_6  0.79 0.13 0.07    0
q_7  0.76 0.19 0.05    0
q_8  0.74 0.17 0.08    0
q_9  0.92 0.07 0.01    0
q_10 0.94 0.04 0.02    0
q_11 0.91 0.04 0.05    0
q_12 0.78 0.19 0.03    0
q_13 0.77 0.21 0.02    0
q_14 0.91 0.08 0.01    0
q_15 0.92 0.06 0.02    0
q_16 0.63 0.19 0.17    0
q_17 0.90 0.07 0.03    0
q_18 0.83 0.14 0.03    0
q_19 0.78 0.15 0.07    0
q_20 0.84 0.14 0.02    0
q_21 0.81 0.15 0.03    0
q_22 0.94 0.03 0.03    0
q_23 0.97 0.02 0.01    0
q_24 0.70 0.25 0.05    0
q_25 0.86 0.10 0.04    0
q_26 0.78 0.14 0.09    0
q_27 0.96 0.03 0.02    0
q_28 0.64 0.28 0.09    0
q_29 0.94 0.06 0.01    0
q_30 0.94 0.05 0.01    0
q_31 0.79 0.16 0.05    0
q_32 0.87 0.09 0.04    0

1.11 Reliability of the original data 60 months

ds_60 %>% 
  select(starts_with("q_")) %>% 
  alpha(.)

Reliability analysis   
Call: alpha(x = .)

 

 lower alpha upper     95% confidence boundaries
0.84 0.85 0.85 

 Reliability if an item is dropped:

 Item statistics 

Non missing response frequency for each item
        0    5   10 miss
q_1  0.85 0.13 0.01    0
q_2  0.64 0.23 0.13    0
q_3  0.74 0.22 0.05    0
q_4  0.78 0.17 0.05    0
q_5  0.81 0.15 0.05    0
q_6  0.76 0.16 0.08    0
q_7  0.75 0.21 0.04    0
q_8  0.89 0.10 0.01    0
q_9  0.77 0.16 0.07    0
q_10 0.91 0.08 0.01    0
q_11 0.96 0.02 0.02    0
q_12 0.91 0.04 0.05    0
q_13 0.82 0.15 0.03    0
q_14 0.68 0.27 0.05    0
q_15 0.72 0.25 0.03    0
q_16 0.60 0.23 0.17    0
q_17 0.88 0.10 0.02    0
q_18 0.92 0.07 0.02    0
q_19 0.79 0.16 0.05    0
q_20 0.79 0.18 0.03    0
q_21 0.75 0.20 0.05    0
q_22 0.93 0.04 0.03    0
q_23 0.96 0.02 0.01    0
q_24 0.65 0.29 0.05    0
q_25 0.84 0.11 0.05    0
q_26 0.79 0.14 0.07    0
q_27 0.63 0.30 0.07    0
q_28 0.90 0.09 0.01    0
q_29 0.93 0.06 0.01    0
q_30 0.80 0.15 0.05    0
q_31 0.60 0.35 0.05    0
q_32 0.85 0.10 0.05    0

1.12 Table 1 48 months from the published paper

This is from where we are getting the data .. Check here: 10.1111/cch.12649

ds_48 %>% 
  select(sex, score) %>% 
  group_by(sex) %>% 
  summarytools::descr()

Descriptive Statistics  
score by sex  
Data Frame: ds_48  
N: 6495  

                    sex = M   sex = F
----------------- --------- ---------
             Mean     37.38     29.08
          Std.Dev     33.10     27.55
              Min      0.00      0.00
               Q1     15.00     10.00
           Median     30.00     20.00
               Q3     55.00     40.00
              Max    240.00    230.00
              MAD     29.65     22.24
              IQR     40.00     30.00
               CV      0.89      0.95
         Skewness      1.43      1.58
      SE.Skewness      0.03      0.03
         Kurtosis      2.52      3.32
          N.Valid   6495.00   5978.00
        Pct.Valid    100.00    100.00

1.13 Table 1 60 months from the published paper

This is from where we are getting the data .. Check here: 10.1111/cch.12649

ds_60 %>% 
  select(sex, score) %>% 
  group_by(sex) %>% 
  summarytools::descr()

Descriptive Statistics  
score by sex  
Data Frame: ds_60  
N: 11291  

                     sex = 1    sex = 2
----------------- ---------- ----------
             Mean      44.82      34.02
          Std.Dev      36.66      30.44
              Min       0.00       0.00
               Q1      15.00      10.00
           Median      35.00      25.00
               Q3      65.00      50.00
              Max     275.00     290.00
              MAD      29.65      22.24
              IQR      50.00      40.00
               CV       0.82       0.89
         Skewness       1.24       1.49
      SE.Skewness       0.02       0.02
         Kurtosis       1.92       2.91
          N.Valid   11291.00   11040.00
        Pct.Valid     100.00     100.00

1.14 Random 48 months

As described, I’ll get a random sample from the main data (items-only)

set.seed(123)
ds_48_random <- ds_48 %>% sample_n(.,500)

1.15 Random 60 months

60 months

set.seed(15)
ds_60_random <- ds_60 %>% sample_n(.,500)

1.16 Sampling via Fairsubset

library(fairsubset)
check_ds <- fairSubset(ds_60, subset_setting = "ks", manual_N = 500, random_subsets = 10)
ds_60_random2 <- check_ds$best_subset %>% as.data.frame

1.17 Check the randomness of the data

1.17.1 Descriptives

bind_rows(
  ds_60_random %>% mutate(base = "random") %>% select(-months),
  ds_60 %>% mutate(base = "original") %>% select(-months)) %>%
  group_by(base) %>% 
  select(score) %>% 
  summarytools::descr()

Adding missing grouping variables: `base`

Descriptive Statistics  
score by base  
N: 22331  

                    base = original   base = random
----------------- ----------------- ---------------
             Mean             39.48           41.00
          Std.Dev             34.16           36.40
              Min              0.00            0.00
               Q1             15.00           15.00
           Median             30.00           30.00
               Q3             55.00           60.00
              Max            290.00          205.00
              MAD             29.65           29.65
              IQR             40.00           45.00
               CV              0.87            0.89
         Skewness              1.38            1.20
      SE.Skewness              0.02            0.11
         Kurtosis              2.44            1.24
          N.Valid          22331.00          500.00
        Pct.Valid            100.00          100.00

1.17.2 Total scores

bind_rows(
  ds_60_random %>% mutate(base = "random") %>% select(-months),
  ds_60 %>% mutate(base = "original") %>% select(-months)) %>% 
  {t.test(score ~ base, var.equal = T,.)}

    Two Sample t-test

data:  score by base
t = -0.98204, df = 22829, p-value = 0.3261
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
 -4.551496  1.513030
sample estimates:
mean in group original   mean in group random 
              39.48077               41.00000 

bind_rows(
  ds_60_random %>% mutate(base = "random") %>% select(-months),
  ds_60 %>% mutate(base = "original") %>% select(-months)) %>% 
  {descr::crosstab(.$sex,.$base, chisq = T, plot = F)}

   Cell Contents 
|-------------------------|
|                   Count | 
|-------------------------|

==================================
         .$base
.$sex    original   random   Total
----------------------------------
1           11291      276   11567
----------------------------------
2           11040      224   11264
----------------------------------
Total       22331      500   22831
==================================

Statistics for All Table Factors

Pearson's Chi-squared test 
------------------------------------------------------------
Chi^2 = 4.208733      d.f. = 1      p = 0.0402 

Pearson's Chi-squared test with Yates' continuity correction 
------------------------------------------------------------
Chi^2 = 4.025226      d.f. = 1      p = 0.0448 
        Minimum expected frequency: 246.6821 

1.18 Cronbach’s alpha (Random)

ds_60_random %>% select(starts_with("q")) %>% 
  mutate_all(., ~case_when(. == "0" ~ 1,
                           . == "5" ~ 2,
                           . == "10" ~ 3)) %>% alpha(.)

Reliability analysis   
Call: alpha(x = .)

 

 lower alpha upper     95% confidence boundaries
0.85 0.86 0.88 

 Reliability if an item is dropped:

 Item statistics 

Non missing response frequency for each item
        1    2    3 miss
q_1  0.83 0.15 0.01    0
q_2  0.65 0.22 0.13    0
q_3  0.71 0.25 0.04    0
q_4  0.78 0.16 0.05    0
q_5  0.82 0.13 0.04    0
q_6  0.77 0.13 0.10    0
q_7  0.74 0.20 0.06    0
q_8  0.89 0.08 0.02    0
q_9  0.76 0.15 0.09    0
q_10 0.90 0.09 0.00    0
q_11 0.97 0.02 0.02    0
q_12 0.92 0.04 0.04    0
q_13 0.81 0.17 0.03    0
q_14 0.62 0.34 0.04    0
q_15 0.71 0.26 0.03    0
q_16 0.60 0.22 0.18    0
q_17 0.85 0.13 0.02    0
q_18 0.91 0.07 0.02    0
q_19 0.78 0.18 0.05    0
q_20 0.76 0.19 0.05    0
q_21 0.76 0.18 0.06    0
q_22 0.93 0.03 0.04    0
q_23 0.97 0.02 0.01    0
q_24 0.65 0.29 0.06    0
q_25 0.83 0.11 0.05    0
q_26 0.79 0.15 0.06    0
q_27 0.61 0.31 0.08    0
q_28 0.90 0.09 0.01    0
q_29 0.94 0.05 0.01    0
q_30 0.79 0.15 0.06    0
q_31 0.59 0.35 0.06    0
q_32 0.83 0.11 0.06    0

1.19 Done