### The syntaxes below show R markdown syntax for calculating all scales mentioned in the current version of the scales manual. To use these syntaxes, please copy the following lines into a R Markdown file (*rmd) or change the file extension to .Rmd --- title: "TwinLife Scales for Data Release v7-0-0*" output: html_notebook --- This R-script contains syntax for all scales included in the TwinLife Scales Manual (v.3.0.0). *Literature: TwinLife Scales Manual. All data collections v3.0.1 Klatzka, C. H., Baum, M. A., Paulus, L., Nikstat, A., Elena T. T. Dang, Andreas, A. , Iser, J., & Hahn, E. (2022). TwinLife Technical Report Series, 08. Project TwinLife: Genetic and social causes of life chances (Universität Bielefeld / Universität des Saarlandes), https://pub.uni-bielefeld.de/record/2939852 For further information, see https://www.twin-life.de/documentation # Table of contents 1. Skill formation and education 2. Career, labor market attainment, and welfare 3. Political and social integration and participation 4. Subjective perception of quality of life 5. Physical and psychological health 6. Psychopathology and deviant behavior 7. Environment PLEASE NOTE: This syntax refers to the data files in person-wave-format (‘long format’; ZA6701_person_wid?_v?-0-0_en), in which each surveyed person has one data row for each survey wave. As recommended in the scales manual this syntax does provide for recoding scales in which all items are coded in the same direction. In cases of dichotomous variables, the response option 2 = "no" must be recoded to 0. We provide the code only for one data collection as an example. The code should be altered for other data collections and your research purposes. ```{r setup chunk} ## Please load the following packages into the current session: library(tidyverse) library(dplyr) library(car) ## If you haven't installed these packages yet, you can use these commands: # install.package("tidyverse") # install.package("car") ``` ```{r importing datasets} ## package "haven" (part of tidyverse) for importing datasets in other formats ## SPSS files data_wid1 <- read_sav("C:/Example path.sav") data_wid2 <- read_sav("C:/Example path.sav") data_wid3 <- read_sav("C:/Example path.sav") data_wid4 <- read_sav("C:/Example path.sav") data_wid5 <- read_sav("C:/Example path.sav") data_wid6 <- read_sav("C:/Example path.sav") data_wid7 <- read_sav("C:/Example path.sav") data_wid8 <- read_sav("C:/Example path.sav") data_wid9 <- read_sav("C:/Example path.sav") ## OR ## STATA files data_wid1 <- read_dta("C:/Example path.dta") data_wid2 <- read_dta("C:/Example path.dta") data_wid3 <- read_dta("C:/Example path.dta") data_wid4 <- read_dta("C:/Example path.dta") data_wid5 <- read_dta("C:/Example path.dta") data_wid6 <- read_dta("C:/Example path.dta") data_wid7 <- read_dta("C:/Example path.dta") data_wid8 <- read_dta("C:/Example path.dta") data_wid9 <- read_dta("C:/Example path.dta") ``` ```{r setting missings} data_wid1[data_wid1 < -51] <- NA data_wid2[data_wid2 < -51] <- NA data_wid3[data_wid3 < -51] <- NA data_wid4[data_wid4 < -51] <- NA data_wid5[data_wid5 < -51] <- NA data_wid6[data_wid4 < -51] <- NA data_wid7[data_wid5 < -51] <- NA data_wid8[data_wid4 < -51] <- NA data_wid9[data_wid5 < -51] <- NA ``` =========================================== # Skill Formation and Education ## Cognitive Abilities *Please note: for cognitive abilities, the data set already contains sum scores (see TwinLife Scales manual, p. 9 ff.). ```{r Self-perceived abilities 1} ## Academic Self-Concept (Children aged 5 to 7). ## recoding the variables according to the manual ## NOTE: In the response format, option 1 and 2 were accidentally switched in the survey and therefore have to be recoded ((1=2), (2=1), (3=3), (4=4)) data_wid1$asc0100.r <- recode(data_wid1$asc0100, "1=3; 2=4; 3=2; 4=1") data_wid1$asc0101.r <- recode(data_wid1$asc0101, "1=3; 2=4; 3=2; 4=1") data_wid1$asc0102.r <- recode(data_wid1$asc0102, "1=3; 2=4; 3=2; 4=1") data_wid1$asc0103.r <- recode(data_wid1$asc0103, "1=3; 2=4; 3=2; 4=1") data_wid1$asc0104.r <- recode(data_wid1$asc0104, "1=3; 2=4; 3=2; 4=1") data_wid1$asc0105.r <- recode(data_wid1$asc0105, "1=3; 2=4; 3=2; 4=1") data_wid1$asc0106.r <- recode(data_wid1$asc0106, "1=3; 2=4; 3=2; 4=1") ## computing mean for every row for Verbal self-concept: asc0100(r), asc0101(r), asc0102(r) data_wid1$asc_verb <- rowMeans(data_wid1[c("asc0100.r", "asc0101.r", "asc0102.r")]) ## computing mean for every row for Mathematical self-concept: asc0103(r), asc0104(r), asc0105(r), asc0106(r) data_wid1$asc_math <- rowMeans(data_wid1[c("asc0103.r", "asc0104.r", "asc0105.r", "asc0106.r")]) ``` ```{r Self-perceived abilities 2} ## Self-perceived ability ## recoding the variables according to the manual data_wid1$spa0100.r <- recode(data_wid1$spa0100, "1=1; 2=0") ## Self-perceived ability in general, self-report (school attendees) ## inverted item data_wid1$spa0202.r <- recode(data_wid1$spa0202, "1=5; 2=4; 3=3; 4=2; 5=1") ## computing mean for every row data_wid1$spagen <- rowMeans(data_wid1[c("spa0200", "spa0201", "spa0202.r")]) ## Self-perceived ability in general, parental report (preschool children) ## computing mean for every row ## Scale general self-perceived ability twin1: parental report of school attendees (mean) data_wid1$spa_prt <- rowMeans(data_wid1[c("spa0100t", "spa0202t")]) ## Scale general self-perceived ability twin2: parental report of school attendees (mean) data_wid1$spa_pru <- rowMeans(data_wid1[c("spa0100u", "spa0202u")]) ## Scale general self-perceived ability sibling: parental report of school attendees (mean) data_wid1$spa_prs <- rowMeans(data_wid1[c("spa0100s", "spa0202s")]) ## Self-perceived ability math, self-report (school attendees). ## inverted item spa0302 data_wid1$spa0302.r <- recode(data_wid1$spa0302, "1=5; 2=4; 3=3; 4=2; 5=1") ## computing mean for every row data_wid1$spamath <- rowMeans(data_wid1[c("spa0300", "spa0301", "spa0302.r")]) ## Self-perceived ability German, self-report (school attendees). ## inverted item spa0402 data_wid1$spa0402.r <- recode(data_wid1$spa0402, "1=5; 2=4; 3=3; 4=2; 5=1") ## computing mean for every row data_wid1$spager <- rowMeans(data_wid1[c("spa0400", "spa0401", "spa0402.r")]) ## self-perceived job ability, self-report (aged 16 or older). ## computing mean for every row data_wid1$spajob <- rowMeans(data_wid1[c("spa0500", "spa0501", "spa0502", "spa0503", "spa0504")]) ``` ## Motivation ```{r Motivation 1} ## Intrinsic motivation ## Anticipated intrinsic motivation, self-report (preschool children) ## recoding the variables according to the manual data_wid1$imo0100.r <- recode(data_wid1$imo0100, "1=1; 2=0") data_wid1$imo0101.r <- recode(data_wid1$imo0101, "1=1; 2=0") data_wid1$imo0102.r <- recode(data_wid1$imo0102, "1=1; 2=0") ## computing mean for every row data_wid1$imoanti <- rowMeans(data_wid1[c("imo0100.r","imo0101.r","imo0102.r")]) ## Anticipated intrinsic motivation, parental report (preschool children). ## Scale general anticipated intrinsic motivation twin1: parental report of preschool children (mean) ## computing mean for every row data_wid1$imo_prt <- rowMeans(data_wid1[c("imo0100t", "imo0101t", "imo0102t")]) ## Scale general anticipated intrinsic motivation twin2: parental report of preschool children (mean) ## computing mean for every row data_wid1$imo_pru <- rowMeans(data_wid1[c("imo0100u", "imo0101u", "imo0102u")]) ## Scale general anticipated intrinsic motivation sibling: parental report of preschool children (mean) ## computing mean for every row data_wid1$imo_prs <- rowMeans(data_wid1[c("imo0100s", "imo0101s", "imo0102s")]) ## Intrinsic motivation in general, self-report (school attendees) ## computing mean for every row data_wid1$imogen <- rowMeans(data_wid1[c("imo0200","imo0201","imo0202")]) ## Intrinsic motivation math, self-report (school attendees) ## computing mean for every row data_wid1$imomath <- rowMeans(data_wid1[c("imo0300", "imo0301", "imo0302")]) ## Intrinsic motivation German, self-report (school attendees) ## computing mean for every row data_wid1$imoger <- rowMeans(data_wid1[c("imo0400", "imo0401", "imo0402")]) ``` ```{r Motivation 2} ## Learning motivation ## Anticipated learning motivation, self-report (preschool children) ## recoding the variables according to the manual data_wid1$imo0103.r <- recode(data_wid1$imo0103, "1=1; 2=0") data_wid1$imo0104.r <- recode(data_wid1$imo0104, "1=1; 2=0") data_wid1$imo0105.r <- recode(data_wid1$imo0105, "1=1; 2=0") ## computing mean for every row data_wid1$imoantilearn <- rowMeans(data_wid1[c("imo0103.r", "imo0104.r", "imo0105.r")]) ## Learning motivation in general, self-report (school attendees aged 9/10 or younger) ## computing mean for every row data_wid1$imolearn1 <- rowMeans(data_wid1[c("imo0550", "imo0551", "imo0552")]) ## Learning motivation in general, self-report (school attendees aged 10/11 or older) ## computing mean for every row data_wid1$imolearn2 <- rowMeans(data_wid1[c("imo0500", "imo0501", "imo0502")]) ## Job learning motivation in general, self-report (aged 16 or older). ## computing mean for every row data_wid1$imojob <- rowMeans(data_wid1[c("imo0600", "imo0601", "imo0602")]) ``` ```{r Motivation 3} ## Achievement motivation ## Achievement motivation, self-report report (age 7 to 15), one-item-scale: imo0701 ## Achievement motivation, self-report (aged 16 or older). ## computing mean for every row data_wid1$imoachiev <- rowMeans(data_wid1[c("imo0700", "imo0702")]) ## Achievement motivation, parental report report (school attendees), one-item-scale: imo0701(t/u/s). ``` ## School Context ```{r School Context} ## School climate / relationship to teachers ## Student teacher interaction, self-report (school attendees aged 13 or older). ## computing mean for every row data_wid3$eduint <- rowMeans(data_wid3[c("edu0700", "edu0701", "edu0800", "edu0801", "edu0802")]) ## Subjective burden at school, self-report (school attendees aged 13 or older). ## computing mean for every row data_wid3$eduburd <- rowMeans(data_wid3[c("edu0901", "edu0902", "edu0903", "edu0904", "edu0905", "edu0906", "edu0907")]) ``` # Career, Labor Market Attainment, and Welfare ## Job Autonomy ```{r Job Autonomy} ## Job autonomy (self-report, all employed participants). ## inverted item data_wid3$aut0103.r <- recode(data_wid3$aut0103, "1=5; 2=4; 3=3; 4=2; 5=1") ## computing mean for every row data_wid3$jobaut <- rowMeans(data_wid3[c("aut0101", "aut0102", "aut0103.r")]) ``` # Political and Social Integration and Participation ## Cultural Capital ```{r Cultural Capital} ## Embodied cultural capital (self-report, aged 10 or older). ## recoding the variables according to the manual data_wid3$cul0201.r <- recode(data_wid3$cul0201, "1=1; 2=0") data_wid3$cul0202.r <- recode(data_wid3$cul0202, "1=1; 2=0") data_wid3$cul0203.r <- recode(data_wid3$cul0203, "1=1; 2=0") data_wid3$cul0204.r <- recode(data_wid3$cul0204, "1=1; 2=0") data_wid3$cul0205.r <- recode(data_wid3$cul0205, "1=1; 2=0") ## computing mean for every row data_wid3$culcap <- rowMeans(data_wid3[c("cul0201.r", "cul0202.r", "cul0203.r", "cul0204.r", "cul0205.r")]) ## cultural involvement (self-report, aged 10 or older). ## recoding the variables acCording to the manual data_wid3$cul0401.r <- recode(data_wid3$cul0401, "1=5; 2=4; 3=3; 4=2; 5=1") data_wid3$cul0402.r <- recode(data_wid3$cul0402, "1=5; 2=4; 3=3; 4=2; 5=1") data_wid3$cul0403.r <- recode(data_wid3$cul0403, "1=5; 2=4; 3=3; 4=2; 5=1") data_wid3$cul0404.r <- recode(data_wid3$cul0404, "1=5; 2=4; 3=3; 4=2; 5=1") ## computing mean for every row data_wid3$culinv <- rowMeans(data_wid3[c("cul0401.r", "cul0402.r", "cul0403.r", "cul0404.r")]) ## participation in high culture (self-report, aged 10 or older) ## acctional items cul0502, cul0505 not included ## computing mean for every row data_wid3$culhigh <- rowMeans(data_wid3[c("cul0501", "cul0503", "cul0504")]) ## participation in high culture (parental report, aged 5 to 9). ## Scale participation in high culture: parental report for twin 1 (mean) ## computing mean for every row data_wid3$culhigh_prt <- rowMeans(data_wid3[c("cul0501t", "cul0503t", "cul0504t")]) ## Scale participation in high culture: parental report for twin 2 (mean) ## computing mean for every row data_wid3$culhigh_pru <- rowMeans(data_wid3[c("cul0501u", "cul0503u", "cul0504u")]) ## Scale participation in high culture: parental report for sibling (mean) ## computing mean for every row data_wid3$culhigh_prs <- rowMeans(data_wid3[c("cul0501s", "cul0503s", "cul0504s")]) ``` ## Social Trust ```{r Social Trust} ## Social Trust: self-report ## inverted items data_wid1$net0101.r <- recode(data_wid1$net0101, "1=4; 2=3; 3=2; 4=1") data_wid1$net0102.r <- recode(data_wid1$net0102, "1=4; 2=3; 3=2; 4=1") ## computing mean for every row data_wid1$net <- rowMeans(data_wid1[c("net0100", "net0101.r", "net0102.r")]) ``` ## Insitutional Trust ```{r Insitutional Trust} ## Insitutional Trust: self-report ## computing mean for every row data_wid9$inst <- rowMeans(data_wid9[c("tru0100", "tru0101", "tru0102", "tru0103", "tru0104", "tru0105")]) ``` ## Right-Wing Authoritarianism ```{r Right-Wing Authoritarianism } ## Right-Wing Authoritarianism scale: self-report ## inverted item data_wid5$rwa0101.r <- recode(data_wid5$rwa0101, "1=5; 2=4; 3=3; 4=2; 5=1") data_wid5$rwa0102.r <- recode(data_wid5$rwa0102, "1=5; 2=4; 3=3; 4=2; 5=1") ## computing mean for every row data_wid5$rwa <- rowMeans(data_wid5[c("rwa0100", "rwa0101.r", "rwa0102.r", "rwa0103")]) ``` ## Social Dominance Orientation ```{r Social Dominance Orientation} ## Social Dominance Orientation: self-report ## inverted item data_wid5$sdo0102.r <- recode(data_wid5$sdo0102, "1=5; 2=4; 3=3; 4=2; 5=1") ## computing mean for every row data_wid5$sdo <- rowMeans(data_wid5[c("sdo0100", "sdo0101", "sdo0102.r", "sdo0103")]) ``` #Personality and Individual Characteristics ## Personality ```{r Personality 1 } ## personality self-report (aged 10 or older). ## Scale personality openness: self-report (mean) ## addtional item per0116 not included ## computing mean for every row data_wid1$peropen <- rowMeans(data_wid1[c("per0103", "per0108", "per0113", "per0115")]) ## Scale personality conscientiousness: self-report (mean) ## inverted item data_wid1$per0106.r <- recode(data_wid1$per0106, "1=7; 2=6; 3=5; 4=4; 5=3; 6=2; 7=1") ## computing mean for every row data_wid1$percons <- rowMeans(data_wid1[c("per0100", "per0106.r", "per0110")]) ## Scale personality extraversion: self-report (mean) ## inverted item data_wid1$per0111.r <- recode(data_wid1$per0111, "1=7; 2=6; 3=5; 4=4; 5=3; 6=2; 7=1") ## computing mean for every row data_wid1$perextr <- rowMeans(data_wid1[c("per0101", "per0111.r", "per0107")]) ## Scale personality agreeableness: self-report (mean) ## inverted item data_wid1$per0102.r <- recode(data_wid1$per0102, "1=7; 2=6; 3=5; 4=4; 5=3; 6=2; 7=1") ## computing mean for every row data_wid1$peragre <- rowMeans(data_wid1[c("per0102.r", "per0105", "per0112")]) ## Scale personality neuroticism: self-report (mean) ## inverted item data_wid1$per0114.r <- recode(data_wid1$per0114, "1=7; 2=6; 3=5; 4=4; 5=3; 6=2; 7=1") ## computing mean for every row data_wid1$perneur <- rowMeans(data_wid1[c("per0114.r", "per0109", "per0104")]) ``` ```{r Personality 2} ## personality, parental report (children aged 5 to 9). ## Scale personality openness twin1: parental report (mean) ## inverted item data_wid1$per0408t.r <- recode(data_wid1$per0408t, "0=10; 1=9; 2=8; 3=7; 4=6; 5=5; 6=4; 7=3; 8=2; 9=1; 10=0") ## computing mean for every row data_wid1$peropen_prt <- rowMeans(data_wid1[c("per0403t", "per0408t.r")]) ## Scale personality conscientiousness twin1: parental report (mean) ## inverted item data_wid1$per0406t.r <- recode(data_wid1$per0406t, "0=10; 1=9; 2=8; 3=7; 4=6; 5=5; 6=4; 7=3; 8=2; 9=1; 10=0") ## computing mean for every row data_wid1$percons_prt <- rowMeans(data_wid1[c("per0401t", "per0406t.r")]) ## Scale personality extraversion twin1: parental report (mean) ## inverted item data_wid1$per0400t.r <- recode(data_wid1$per0400t, "0=10; 1=9; 2=8; 3=7; 4=6; 5=5; 6=4; 7=3; 8=2; 9=1; 10=0") ## computing mean for every row data_wid1$perextr_prt <- rowMeans(data_wid1[c("per0400t.r", "per0405t")]) ## Scale personality agreeableness twin1: parental report (mean) ## inverted item data_wid1$per0402t.r <- recode(data_wid1$per0402t, "0=10; 1=9; 2=8; 3=7; 4=6; 5=5; 6=4; 7=3; 8=2; 9=1; 10=0") ## computing mean for every row data_wid1$peragre_prt <- rowMeans(data_wid1[c("per0402t.r", "per0407t")]) ## Scale personality neuroticism twin1: parental report (mean) ## inverted item data_wid1$per0409t.r <- recode(data_wid1$per0409t, "0=10; 1=9; 2=8; 3=7; 4=6; 5=5; 6=4; 7=3; 8=2; 9=1; 10=0") ## computing mean for every row data_wid1$perneur_prt <- rowMeans(data_wid1[c("per0404t", "per0409t.r")]) ## Scale personality openness twin2: parental report (mean) ## inverted item data_wid1$per0408u.r <- recode(data_wid1$per0408u, "0=10; 1=9; 2=8; 3=7; 4=6; 5=5; 6=4; 7=3; 8=2; 9=1; 10=0") ## computing mean for every row data_wid1$peropen_pru <- rowMeans(data_wid1[c("per0403u", "per0408u.r")]) ## Scale personality conscientiousness twin2: parental report (mean) ## inverted item data_wid1$per0406u.r <- recode(data_wid1$per0406u, "0=10; 1=9; 2=8; 3=7; 4=6; 5=5; 6=4; 7=3; 8=2; 9=1; 10=0") ## computing mean for every row data_wid1$percons_pru <- rowMeans(data_wid1[c("per0401u", "per0406u.r")]) ## Scale personality extraversion twin2: parental report (mean) ## inverted item data_wid1$per0400u.r <- recode(data_wid1$per0400u, "0=10; 1=9; 2=8; 3=7; 4=6; 5=5; 6=4; 7=3; 8=2; 9=1; 10=0") ## computing mean for every row data_wid1$perextr_pru <- rowMeans(data_wid1[c("per0400u.r", "per0405u")]) ## Scale personality agreeableness twin2: parental report (mean) ## inverted item data_wid1$per0402u.r <- recode(data_wid1$per0402u, "0=10; 1=9; 2=8; 3=7; 4=6; 5=5; 6=4; 7=3; 8=2; 9=1; 10=0") ## computing mean for every row data_wid1$peragre_pru <- rowMeans(data_wid1[c("per0402u.r", "per0407u")]) ## Scale personality neuroticism twin2: parental report (mean) ## inverted item data_wid1$per0409u.r <- recode(data_wid1$per0409u, "0=10; 1=9; 2=8; 3=7; 4=6; 5=5; 6=4; 7=3; 8=2; 9=1; 10=0") ## computing mean for every row data_wid1$perneur_pru <- rowMeans(data_wid1[c("per0404u", "per0409u.r")]) ## Scale personality openness sibling: parental report (mean) ## inverted item data_wid1$per0408s.r <- recode(data_wid1$per0408s, "0=10; 1=9; 2=8; 3=7; 4=6; 5=5; 6=4; 7=3; 8=2; 9=1; 10=0") ## computing mean for every row data_wid1$peropen_prs <- rowMeans(data_wid1[c("per0403s", "per0408s.r")]) ## Scale personality conscientiousness sibling: parental report (mean) ## inverted item data_wid1$per0406s.r <- recode(data_wid1$per0406s, "0=10; 1=9; 2=8; 3=7; 4=6; 5=5; 6=4; 7=3; 8=2; 9=1; 10=0") ## computing mean for every row data_wid1$percons_prs <- rowMeans(data_wid1[c("per0401s", "per0406s.r")]) ## Scale personality extraversion sibling: parental report (mean) ## inverted item data_wid1$per0400s.r <- recode(data_wid1$per0400s, "0=10; 1=9; 2=8; 3=7; 4=6; 5=5; 6=4; 7=3; 8=2; 9=1; 10=0") ## computing mean for every row data_wid1$perextr_prs <- rowMeans(data_wid1[c("per0400s.r", "per0405s")]) ## Scale personality agreeableness sibling: parental report (mean) ## inverted item data_wid1$per0402s.r <- recode(data_wid1$per0402s, "0=10; 1=9; 2=8; 3=7; 4=6; 5=5; 6=4; 7=3; 8=2; 9=1; 10=0") ## computing mean for every row data_wid1$peragre_prs <- rowMeans(data_wid1[c("per0402s.r", "per0407s")]) ## Scale personality neuroticism sibling: parental report (mean) ## inverted item data_wid1$per0409s.r <- recode(data_wid1$per0409s, "0=10; 1=9; 2=8; 3=7; 4=6; 5=5; 6=4; 7=3; 8=2; 9=1; 10=0") ## computing mean for every row data_wid1$perneur_prs <- rowMeans(data_wid1[c("per0404s", "per0409s.r")]) ``` ## Narcissism ```{r Narcissism } ## Self-report – Naughty Nine ## computing mean for every row data_wid5$nine <- rowMeans(data_wid5[c("nar0100", "nar0101", "nar0102")]) ## Self-report – NPQC-R: Superiority ## computing mean for every row data_wid5$narsup <- rowMeans(data_wid5[c("nar0200", "nar0201")]) ## Self-report – NPQC-R: Exploitativeness ## computing mean for every row data_wid5$narexp <- rowMeans(data_wid5[c("nar0202", "nar0203")]) ``` ## Self-Esteem ```{r Self-Esteem} ## self-esteem, self-report ## inverted item data_wid1$ses0100.r <- recode(data_wid1$ses0100, "1=5; 2=4; 3=3; 4=2; 5=1") ## computing mean for every row data_wid1$ses <- rowMeans(data_wid1[c("ses0100.r", "ses0101", "ses0102")]) ## self-esteem parental report (children aged 5 to 12). ## Scale self-esteem twin1: parental report (mean) ## computing mean for every row data_wid1$ses_prt <- rowMeans(data_wid1[c("ses0200t", "ses0102t")]) ## Scale self-esteem twin2: parental report (mean) ## computing mean for every row data_wid1$ses_pru <- rowMeans(data_wid1[c("ses0200u", "ses0102u")]) ## Scale self-esteem sibling: parental report (mean) ## computing mean for every row data_wid1$ses_prs <- rowMeans(data_wid1[c("ses0200s", "ses0102s")]) ``` ## Self-Regulation ```{r Self-Regulation} ## Caution: In this case, higher values mean a lower trait manifestation. ## consistency of interest self-report (aged 10 or older). ## computing mean for every row data_wid3$srgcoi <- rowMeans(data_wid3[c("srg0100", "srg0200", "srg0300")]) ## Self-control self-report (aged 10 or older). ## computing mean for every row data_wid3$srgsc <- rowMeans(data_wid3[c("srg0400", "srg0500", "srg0600")]) ## Self-control parental report (children aged 5 to 9). ## Scale self-control twin1: parental report (mean) ## computing mean for every row data_wid3$srg_prt <- rowMeans(data_wid3[c("srg0400t", "srg0500t", "srg0600t")]) ## Scale self-control twin2: parental report (mean) ## computing mean for every row data_wid3$srg_pru <- rowMeans(data_wid3[c("srg0400u", "srg0500u", "srg0600u")]) ## Scale self-control sibling: parental report (mean) ## computing mean for every row data_wid3$srg_prs <- rowMeans(data_wid3[c("srg0400s", "srg0500s", "srg0600s")]) ``` ## Optimism ```{r Optimism} ## Optimism, self-report (aged 10 or older). ## computing mean for every row data_wid3$lot <- rowMeans(data_wid3[c("lot0100", "lot0101", "lot0102")]) ``` ## Fear of Failure ```{r Fear of Failure } ## performance failure appraisal inventory - short form: self-report ## computing mean for every row data_wid5$fof <- rowMeans(data_wid5[c("fof0100", "fof0101", "fof0102", "fof0103", "fof0104")]) ``` ## Self-Efficacy ```{r Self-Efficacy} ## Self-efficacy (self-report, aged 10 or older). ## computing mean for every row data_wid1$sef <- rowMeans(data_wid1[c("sef0100", "sef0101", "sef0102")]) ``` ## Sensory Processing Sensitivity ```{r Sensory Processing Sensitivity} ## Sensory processing sensitivity, self-report (between 10 and 15 years of age). ## scale ease of excitation: self-report (between 10y and 15y, mean) ## computing mean for every row data_wid3$spseas_1 <- rowMeans(data_wid3[c("sps0102", "sps0104")]) ##scale aesthetic sensitivity: self-report (between 10y and 15y, mean) ## computing mean for every row data_wid3$spsaes_1 <- rowMeans(data_wid3[c("sps0101", "sps0103")]) ## scale low sensory threshold: self-report (between 10y and 15y, mean ## computing mean for every row data_wid3$spssen_1 <- rowMeans(data_wid3[c("sps0100", "sps0105")]) ## Sensory processing sensitivity, self-report (aged 16 or older). ## scale ease of excitation: self-report (aged 16 or older, mean) ## computing mean for every row data_wid3$spseas_2 <- rowMeans(data_wid3[c("sps0202", "sps0204")]) ## scale aesthetic sensitivity: self-report (aged 16 or older, mean) ## computing mean for every row data_wid3$spsaes_1 <- rowMeans(data_wid3[c("sps0201", "sps0203")]) ## scale low sensory threshold: self-report (aged 16 or older, mean) ## computing mean for every row data_wid3$spssen_1 <- rowMeans(data_wid3[c("sps0200", "sps0205")]) ``` ## Locus of control ```{r Locus of control} ## scale internal locus of control: self-report (aged 15 or younger, mean) ## computing mean for every row data_wid3$locint_1 <- rowMeans(data_wid3[c("loc0100", "loc0102")]) ##scale external locus of control: self-report (aged 15 or younger, mean) ## computing mean for every row data_wid3$locext_1 <- rowMeans(data_wid3[c("loc0101", "loc0103")]) ## Locus of control, self-report (aged 16 or older). ## scale internal locus of control: self-report (aged 16 or older, mean) ## computing mean for every row data_wid3$locint_2 <- rowMeans(data_wid3[c("loc0200", "loc0202")]) ## scale external locus of control: self-report (aged 16 or older, mean) ## computing mean for every row data_wid3$locext_2 <- rowMeans(data_wid3[c("loc0201", "loc0203")]) ``` ## Stress regulation and coping, self-report (aged 5 to 15). ## scale stress task orientation: self-report (aged 15 or younger, mean) ## computing mean for every row data_wid3$svktas <- rowMeans(data_wid3[c("svk0100", "svk0103", "svk0106")]) ## scale stress emotional coping: self-report (aged 15 or younger, mean) ## computing mean for every row data_wid3$svkemo <- rowMeans(data_wid3[c("svk0101", "svk0104", "svk0107")]) ## scale stress distraction: self-report (aged 15 or younger, mean) ## computing mean for every row data_wid3$svkdis <- rowMeans(data_wid3[c("svk0102", "svk0105", "svk0108")]) ## Stress regulation and coping, self-report (aged 16 or older). ## scale stress task orientation: self-report (aged 16 or older, mean) ## computing mean for every row data_wid3$cistas <- rowMeans(data_wid3[c("cis0100", "cis0103", "cis0106")]) # scale stress emotional coping: self-report (aged 16 or older, mean) ## computing mean for every row data_wid3$cisemo <- rowMeans(data_wid3[c("cis0101", "cis0104", "cis0107")]) ## scale stress distraction: self-report (aged 16 or older, mean) ## computing mean for every row data_wid3$cisdis <- rowMeans(data_wid3[c("cis0102", "cis0105", "cis0108")]) # Subjective Perception of Quality of Life ## Global Life Satisfaction ```{r Global Life Satisfaction} ## global life satisfaction, self-report (aged 10 to 15). ## computing mean for every row data_wid1$gls_1 <- rowMeans(data_wid1[c("gls0600", "gls0700", "gls0800", "gls0900", "gls1000")]) ## global life satisfaction, self-report (aged 16 and older). ## computing mean for every row data_wid1$gls_2 <- rowMeans(data_wid1[c("gls0100", "gls0200", "gls0300", "gls0400", "gls0500")]) ``` ## Burden and Stress ```{r Burden and Stress } ### Burden and stress related to parenthood, self-report (aged 16 or older and having a child) ## computing mean for every row data_wid3$ebi <- rowMeans(data_wid3[c("ebi0100", "ebi0101", "ebi0102", "ebi0103", "ebi0104", "ebi0105")]) ``` ## Life Goals ```{r Life Goals} ## Life Goals, self-report (aged 16 or older) ## scale life goals success: self-report (mean) ## computing mean for every row data_wid3$lgdsuc <- rowMeans(data_wid3[c("lgd0101", "lgd0102", "lgd0105")]) ## scale life goals family life: self-report (mean) ## computing mean for every row data_wid3$lgdfam <- rowMeans(data_wid3[c("lgd0103", "lgd0104")]) ``` ## Emotional impairment ```{r Emotional impairment} ## Worrying – Generalized Anxiety Disorder: self report (Participants aged 11 or older) ## computing mean for every row data_wid5$gad <- rowMeans(data_wid5[c("emi0102", "emi0103")]) ``` ## Injustice Sensitivity ```{r Injustice Sensitivity} ## Victim sensitivity – Self report ## computing mean for every row data_wid5$vicsen <- rowMeans(data_wid5[c("ugs0100", "ugs0101")]) ## Social structure – Self report: one-item scale: ugs0200 ``` # Physical and Psychological Health ## Depression ```{r Depression} ## Depression, self-report (aged 10 or older). ## computing mean for every row data_wid3$bdi <- rowMeans(data_wid3[c("bdi0100", "bdi0101", "bdi0102", "bdi0103", "bdi0104", "bdi0105", "bdi0106")]) ``` # Psychopathology and Deviant Behavior ## Internalizing Problem Behavior ```{r Internalizing Problem Behavior 1} ## Internalizing problem behavior ## Internalizing problem behavior, self-report (aged 10 or older). ## please note: int0108 & int0109 were only asked if participant was aged 17 or younger, whereas int0110 and int0111 were asked for participants aged 18 or older; ## these items correspond in content: int0108 corresponds to int0111; int0109 corresponds to int0110. ## scale internalizing emotional symptoms: self-report (mean) ## computing mean for every row data_wid1$intemo <- rowMeans(data_wid1[c("int0100", "int0101", "int0102", "int0103", "int0104")]) ## scale internalizing peer problems: self-report (mean) ## inverted item data_wid1$int0106.r <- recode(data_wid1$int0106, "1=3; 2=2; 3=1") data_wid1$int0107.r <- recode(data_wid1$int0107, "1=3; 2=2; 3=1") ## computing mean for every row data_wid1$intpeer <- rowMeans(data_wid1[c("int0105", "int0106.r", "int0107.r", "int0108", "int0109", "int0110", "int0111")]) ``` ```{r Internalizing Problem Behavior 2} ## Internalizing problem behavior, parental report (children aged 5 to 9). ## twin1: parental report ## scale Internalizing emotional symptoms twin1: parental report (mean) ## computing mean for every row data_wid1$intemo_t <- rowMeans(data_wid1[c("int0100t", "int0101t", "int0102t", "int0103t", "int0104t")]) ## scale internalizing peer problems twin1: parental report (mean) ## inverted item data_wid1$int0106t.r <- recode(data_wid1$int0106t, "1=3; 2=2; 3=1") data_wid1$int0107t.r <- recode(data_wid1$int0107t, "1=3; 2=2; 3=1") ## computing mean for every row data_wid1$intpeer_t <- rowMeans(data_wid1[c("int0105t", "int0106t.r", "int0107t.r", "int0108t", "int0109t")]) ## twin2: parental report ## scale Internalizing emotional symptoms twin2: parental report (mean) ## computing mean for every row data_wid1$intemo_u <- rowMeans(data_wid1[c("int0100u", "int0101u", "int0102u", "int0103u", "int0104u")]) ## scale internalizing peer problems twin2: parental report (mean) ## inverted item data_wid1$int0106u.r <- recode(data_wid1$int0106u, "1=3; 2=2; 3=1") data_wid1$int0107u.r <- recode(data_wid1$int0107u, "1=3; 2=2; 3=1") ## computing mean for every row data_wid1$intpeer_u <- rowMeans(data_wid1[c("int0105u", "int0106u.r", "int0107u.r", "int0108u", "int0109u")]) ## sibling: parental report ## scale Internalizing emotional symptoms sibling: parental report (mean) ## scale internalizing emotional symptoms: self-report (mean) ## computing mean for every row data_wid1$intemo_s <- rowMeans(data_wid1[c("int0100s", "int0101s", "int0102s", "int0103s", "int0104s")]) ## scale internalizing peer problems sibling: parental report (mean) ## inverted item data_wid1$int0106s.r <- recode(data_wid1$int0106s, "1=3; 2=2; 3=1") data_wid1$int0107s.r <- recode(data_wid1$int0107s, "1=3; 2=2; 3=1") ## computing mean for every row data_wid1$intpeer_s <- rowMeans(data_wid1[c("int0105s", "int0106s.r", "int0107s.r", "int0108s", "int0109s")]) ``` ## Externalizing Problem Behavior ```{r Externalizing Problem Behavior 1} ## Externalizing problem behavior, self-report (aged 10 or older). ## please note: ext0101 was not assessed for participants aged 18 or older. ## scale externalizing hyperactivity: self-report (mean) ## inverted item data_wid1$ext0103.r <- recode(data_wid1$ext0103, "1=3; 2=2; 3=1") data_wid1$ext0104.r <- recode(data_wid1$ext0104, "1=3; 2=2; 3=1") ## computing mean for every row data_wid1$exthyp <- rowMeans(data_wid1[c("ext0100", "ext0101", "ext0102", "ext0103.r", "ext0104.r")]) ## scale externalizing conduct problems: self-report (mean) ## inverted item data_wid1$ext0106.r <- recode(data_wid1$ext0106, "1=3; 2=2; 3=1") ## computing mean for every row data_wid1$extcon <- rowMeans(data_wid1[c("ext0105", "ext0106.r", "ext0107", "ext0108", "ext0109")]) ``` ```{r Externalizing Problem Behavior 2} ## Externalizing problem behavior, parental report (children aged 5 to 9). ## twin1: parental report ## scale externalizing hyperactivity twin1: parental report (mean) ## inverted item data_wid1$ext0102t.r <- recode(data_wid1$ext0102t, "1=3; 2=2; 3=1") data_wid1$ext0103t.r <- recode(data_wid1$ext0103t, "1=3; 2=2; 3=1") ## computing mean for every row data_wid1$exthyp_prt <- rowMeans(data_wid1[c("ext0100t", "ext0109t", "ext0101t", "ext0102t.r", "ext0103t.r")]) ## scale externalizing conduct problems twin1: parental report (mean) ## inverted item data_wid1$ext0105t.r <- recode(data_wid1$ext0105t, "1=3; 2=2; 3=1") ## computing mean for every row data_wid1$extcond_prt <- rowMeans(data_wid1[c("ext0104t", "ext0105t.r", "ext0106t", "ext0107t", "ext0108t")]) ## twin2:parental report ## scale externalizing hyperactivity twin2:parental report (mean) ## inverted item data_wid1$ext0102u.r <- recode(data_wid1$ext0102u, "1=3; 2=2; 3=1") data_wid1$ext0103u.r <- recode(data_wid1$ext0103u, "1=3; 2=2; 3=1") ## computing mean for every row data_wid1$exthyp_pru <- rowMeans(data_wid1[c("ext0100u", "ext0109u", "ext0101u", "ext0102u.r", "ext0103u.r")]) ## scale externalizing conduct problems twin2:parental report (mean) ## inverted item data_wid1$ext0105u.r <- recode(data_wid1$ext0105u, "1=3; 2=2; 3=1") ## computing mean for every row data_wid1$extcond_pru <- rowMeans(data_wid1[c("ext0104u", "ext0105u.r", "ext0106u", "ext0107u", "ext0108u")]) ## sibling: parental report ## scale externalizing hyperactivity sibling: parental report (mean) ## inverted item data_wid1$ext0102s.r <- recode(data_wid1$ext0102s, "1=3; 2=2; 3=1") data_wid1$ext0103s.r <- recode(data_wid1$ext0103s, "1=3; 2=2; 3=1") ## computing mean for every row data_wid1$exthyp_prs <- rowMeans(data_wid1[c("ext0100s", "ext0109s", "ext0101s", "ext0102s.r", "ext0103s.r")]) ## scale externalizing conduct problems sibling: parental report (mean) ## inverted item data_wid1$ext0105s.r <- recode(data_wid1$ext0105s, "1=3; 2=2; 3=1") ## computing mean for every row data_wid1$extcond_prs <- rowMeans(data_wid1[c("ext0104s", "ext0105s.r", "ext0106s", "ext0107s", "ext0108s")]) ``` ## Deviant and Delinquent Behavior ```{r Deviant and Delinquent Behavior} ## Deviant and delinquent behavior, self-report (aged 5 to 9). ## scale deviant behavior conduct problems: self-report (mean) ## inverted item data_wid1$dev0101.r <- recode(data_wid1$dev0101, "1=3; 2=2; 3=1") ## computing mean for every row data_wid1$devcond <- rowMeans(data_wid1[c("dev0100", "dev0101.r", "dev0102", "dev0103")]) ``` # Environment ## Parental Behavior and Involvement ```{r Parental Behavior and Involvement 1} ## Parental involvement, self-report (F2F1: school attendees aged 9 or older; F2F2: school attendees aged 10 to 20). ## scale parental involvement structure: self-report (mean) ## computing mean for every row data_wid1$invstru <- rowMeans(data_wid1[c("inv0100", "inv0101", "inv0102")]) ## scale parental involvement emotional support: self-report (mean) ## computing mean for every row data_wid1$invemo <- rowMeans(data_wid1[c("inv0103", "inv0104", "inv0105")]) ## scale parental involvement autonomy: self-report (mean) ## computing mean for every row data_wid1$invaut <- rowMeans(data_wid1[c("inv0106", "inv0107", "inv0108")]) ## scale parental involvement control: self-report (mean) ## computing mean for every row data_wid1$invcon <- rowMeans(data_wid1[c("inv0109", "inv0110", "inv0111")]) ## Parenting Style, parental report (F2F1 only). ## parents on twin1 ## parents on twin1: parenting scale warmth (mean) ## computing mean for every row data_wid1$parwarm_prt <- rowMeans(data_wid1[c("par0100t", "par0101t", "par0102t", "par0103t")]) ## parents on twin1: parenting scale psych. control (mean) ## computing mean for every row data_wid1$parcont_prt <- rowMeans(data_wid1[c("par0104t", "par0105t", "par0106t")]) ## parents on twin1: parenting scale negative communication (mean) ## computing mean for every row data_wid1$parnegc_prt <- rowMeans(data_wid1[c("par0107t", "par0108t")]) ## parents on twin1: parenting scale monitoring (mean) ## computing mean for every row data_wid1$parmoni_prt <- rowMeans(data_wid1[c("par0109t", "par0110t")]) ## parents on twin1: parenting scale inconsistent parenting (mean) ## computing mean for every row data_wid1$parinco_prt <- rowMeans(data_wid1[c("par0111t", "par0112t")]) ## Parenting Style, parental report (F2F1 only). ## parents on twin2 ## parents on twin2: parenting scale warmth (mean) ## computing mean for every row data_wid1$parwarm_pru <- rowMeans(data_wid1[c("par0100u", "par0101u", "par0102u", "par0103u")]) ## parents on twin2: parenting scale psych. control (mean) ## computing mean for every row data_wid1$parcont_pru <- rowMeans(data_wid1[c("par0104u", "par0105u", "par0106u")]) ## parents on twin2: parenting scale negative communication (mean) ## computing mean for every row data_wid1$parnegc_pru <- rowMeans(data_wid1[c("par0107u", "par0108u")]) ## parents on twin2: parenting scale monitoring (mean) ## computing mean for every row data_wid1$parmoni_pru <- rowMeans(data_wid1[c("par0109u", "par0110u")]) ## parents on twin2: parenting scale inconsistent parenting (mean) ## computing mean for every row data_wid1$parinco_pru <- rowMeans(data_wid1[c("par0111u", "par0112u")]) ## Parenting Style, parental report (F2F1 only). ## parents on siblings: ## parents on siblings: parenting scale warmth (mean) ## computing mean for every row data_wid1$parwarm_prs <- rowMeans(data_wid1[c("par0100s", "par0101s", "par0102s", "par0103s")]) ## parents on siblings: parenting scale psych. control (mean) ## computing mean for every row data_wid1$parcont_prs <- rowMeans(data_wid1[c("par0104s", "par0105s", "par0106s")]) ## parents on siblings: parenting scale negative communication (mean) ## computing mean for every row data_wid1$parnegc_prs <- rowMeans(data_wid1[c("par0107s", "par0108s")]) ## parents on siblings: parenting scale monitoring (mean) ## computing mean for every row data_wid1$parmoni_prs <- rowMeans(data_wid1[c("par0109s", "par0110s")]) ## parents on siblings: parenting scale inconsistent parenting (mean) ## computing mean for every row data_wid1$parinco_prs <- rowMeans(data_wid1[c("par0111s", "par0112s")]) ``` ```{r Parental Behavior and Involvement 2} ## Parenting Style, child report (children aged 5 to 9, F2F1 only). ## child on mother ## child on mother: parenting scale warmth (age 5-9, mean)' ## computing mean for every row data_wid1$paswarm_2m <- rowMeans(data_wid1[c("pas0200m", "pas0201m", "pas0202m", "pas0203m")]) ## child on mother: parenting scale psych. control (age 5-9, mean)' ## computing mean for every row data_wid1$pascont_2m <- rowMeans(data_wid1[c("pas0204m", "pas0205m", "pas0206m")]) ## child on mother: parenting scale negative communication (age 5-9, mean)' ## computing mean for every row data_wid1$pasnegc_2m <- rowMeans(data_wid1[c("pas0207m", "pas0208m")]) ## child on mother: parenting scale monitoring (age 5-9, mean)' ## computing mean for every row data_wid1$pasmoni_2m <- rowMeans(data_wid1[c("pas0209m", "pas0210m")]) ## child on mother: parenting scale inconsistent parenting (age 5-9, mean)' ## computing mean for every row data_wid1$pasinco_2m <- rowMeans(data_wid1[c("pas0211m", "pas0212m")]) ## Parenting Style, child report (children aged 5 to 9, F2F1 only). ## child on father ## child on father: parenting scale warmth (age 5-9, mean)' ## computing mean for every row data_wid1$paswarm_2f <- rowMeans(data_wid1[c("pas0200f", "pas0201f", "pas0202f", "pas0203f")]) ## child on father: parenting scale psych. control (age 5-9, mean)' ## computing mean for every row data_wid1$pascont_2f <- rowMeans(data_wid1[c("pas0204f", "pas0205f", "pas0206f")]) ## child on father: parenting scale negative communication (age 5-9, mean)' ## computing mean for every row data_wid1$pasnegc_2f <- rowMeans(data_wid1[c("pas0207f", "pas0208f")]) ## child on father: parenting scale monitoring (age 5-9, mean)' ## computing mean for every row data_wid1$pasmoni_2f <- rowMeans(data_wid1[c("pas0209f", "pas0210f")]) ## child on father: parenting scale inconsistent parenting (age 5-9, mean)' ## computing mean for every row data_wid1$pasinco_2f <- rowMeans(data_wid1[c("pas0211f", "pas0212f")]) ## Parenting Style, child report (children aged 5 to 9, F2F1 only). ## child on stepmother ## child on stepmother: parenting scale warmth (age 5-9, mean)' ## computing mean for every row data_wid1$paswarm_2n <- rowMeans(data_wid1[c("pas0200n", "pas0201n", "pas0202n", "pas0203n")]) ## child on stepmother: parenting scale psych. control (age 5-9, mean)' ## computing mean for every row data_wid1$pascont_2n <- rowMeans(data_wid1[c("pas0204n", "pas0205n", "pas0206n")]) ## child on stepmother: parenting scale negative communication (age 5-9, mean)' ## computing mean for every row data_wid1$pasnegc_2n <- rowMeans(data_wid1[c("pas0207n", "pas0208n")]) ## child on stepmother: parenting scale monitoring (age 5-9, mean)' ## computing mean for every row data_wid1$pasmoni_2n <- rowMeans(data_wid1[c("pas0209n", "pas0210n")]) ## child on stepmother: parenting scale inconsistent parenting (age 5-9, mean)' ## computing mean for every row data_wid1$pasinco_2n <- rowMeans(data_wid1[c("pas0211n", "pas0212n")]) ## Parenting Style, child report (children aged 5 to 9, F2F1 only). ## child on stepfather ## child on stepfather: parenting scale warmth (age 5-9, mean)' ## computing mean for every row data_wid1$paswarm_2g <- rowMeans(data_wid1[c("pas0200g", "pas0201g", "pas0202g", "pas0203g")]) ## child on stepfather: parenting scale psych. control (age 5-9, mean)' ## computing mean for every row data_wid1$pascont_2g <- rowMeans(data_wid1[c("pas0204g", "pas0205g", "pas0206g")]) ## child on stepfather: parenting scale negative communication (age 5-9, mean)' ## computing mean for every row data_wid1$pasnegc_2g <- rowMeans(data_wid1[c("pas0207g", "pas0208g")]) ## child on stepfather: parenting scale monitoring (age 5-9, mean)' ## computing mean for every row data_wid1$pasmoni_2g <- rowMeans(data_wid1[c("pas0209g", "pas0210g")]) ## child on stepfather: parenting scale inconsistent parenting (age 5-9, mean)' ## computing mean for every row data_wid1$pasinco_2g <- rowMeans(data_wid1[c("pas0211g", "pas0212g")]) ``` ```{r Parental Behavior and Involvement 3} ## Parenting Style, child report (children aged 10 or older, F2F1 and F2F2). ## child on mother ## child on mother: parenting scale warmth (age >=10, mean) ## computing mean for every row data_wid1$paswarm_1m <- rowMeans(data_wid1[c("pas0100m", "pas0101m", "pas0102m", "pas0103m")]) ## child on mother: parenting scale psych. control (age >=10, mean) ## computing mean for every row data_wid1$pascont_1m <- rowMeans(data_wid1[c("pas0104m", "pas0105m", "pas0106m")]) ## child on mother: parenting scale negative communication (age >=10, mean) ## computing mean for every row data_wid1$pasnegc_1m <- rowMeans(data_wid1[c("pas0107m", "pas0108m")]) ## child on mother: parenting scale monitoring (age >=10, mean) ## computing mean for every row data_wid1$pasmoni_1m <- rowMeans(data_wid1[c("pas0109m", "pas0110m")]) ## child on mother: parenting scale inconsistent parenting (age >=10, mean) ## computing mean for every row data_wid1$pasinco_1m <- rowMeans(data_wid1[c("pas0111m", "pas0112m")]) ## Parenting Style, child report (children aged 10 or older, F2F1 and F2F2). ## child on father ## child on father: parenting scale warmth (age >=10, mean) ## computing mean for every row data_wid1$paswarm_1f <- rowMeans(data_wid1[c("pas0100f", "pas0101f", "pas0102f", "pas0103f")]) ## child on father: parenting scale psych. control (age >=10, mean) ## computing mean for every row data_wid1$pascont_1f <- rowMeans(data_wid1[c("pas0104f", "pas0105f", "pas0106f")]) ## child on father: parenting scale negative communication (age >=10, mean) ## computing mean for every row data_wid1$pasnegc_1f <- rowMeans(data_wid1[c("pas0107f", "pas0108f")]) ## child on father: parenting scale monitoring (age >=10, mean) ## computing mean for every row data_wid1$pasmoni_1f <- rowMeans(data_wid1[c("pas0109f", "pas0110f")]) ## child on father: parenting scale inconsistent parenting (age >=10, mean) ## computing mean for every row data_wid1$pasinco_1f <- rowMeans(data_wid1[c("pas0111f", "pas0112f")]) ## Parenting Style, child report (children aged 10 or older, F2F1 and F2F2). ## child on stepmother ## child on stepmother: parenting scale warmth (age >=10, mean) ## computing mean for every row data_wid1$paswarm_1n <- rowMeans(data_wid1[c("pas0100n", "pas0101n", "pas0102n", "pas0103n")]) ## child on stepmother: parenting scale psych. control (age >=10, mean) ## computing mean for every row data_wid1$pascont_1n <- rowMeans(data_wid1[c("pas0104n", "pas0105n", "pas0106n")]) ## child on stepmother: parenting scale negative communication (age >=10, mean) ## computing mean for every row data_wid1$pasnegc_1n <- rowMeans(data_wid1[c("pas0107n", "pas0108n")]) ## child on stepmother: parenting scale monitoring (age >=10, mean) ## computing mean for every row data_wid1$pasmoni_1n <- rowMeans(data_wid1[c("pas0109n", "pas0110n")]) ## child on stepmother: parenting scale inconsistent parenting (age >=10, mean) ## computing mean for every row data_wid1$pasinco_1n <- rowMeans(data_wid1[c("pas0111n", "pas0112n")]) ## Parenting Style, child report (children aged 10 or older, F2F1 and F2F2). ## child on stepfather: ## child on stepfather: parenting scale warmth (age >=10, mean) ## computing mean for every row data_wid1$paswarm_1g <- rowMeans(data_wid1[c("pas0100g", "pas0101g", "pas0102g", "pas0103g")]) ## child on stepfather: parenting scale psych. control (age >=10, mean) ## computing mean for every row data_wid1$pascont_1g <- rowMeans(data_wid1[c("pas0104g", "pas0105g", "pas0106g")]) ## child on stepfather: parenting scale negative communication (age >=10, mean) ## computing mean for every row data_wid1$pasnegc_1g <- rowMeans(data_wid1[c("pas0107g", "pas0108g")]) ## child on stepfather: parenting scale monitoring (age >=10, mean) ## computing mean for every row data_wid1$pasmoni_1g <- rowMeans(data_wid1[c("pas0109g", "pas0110g")]) ## child on stepfather: parenting scale inconsistent parenting (age >=10, mean) ## computing mean for every row data_wid1$pasinco_1g <- rowMeans(data_wid1[c("pas0111g", "pas0112g")]) ``` ## Sibling Relationship Quality ```{r Sibling Relationship Quality 1} ## SRI- Version 1 – Early childhood ## sibling relationship quality, self-report (aged 5 to 9, F2F1 only) ## twin on co-twin ## twin on co-twin: scale sibling relationship affection (age 5-9, mean) ## computing mean for every row data_wid1$sreaff_1 <- rowMeans(data_wid1[c("sre0500", "sre0501", "sre0502", "sre0503")]) ## twin on co-twin: scale sibling relationship hostility (age 5-9, mean ## computing mean for every row data_wid1$srehos_1 <- rowMeans(data_wid1[c("sre0504", "sre0505", "sre0506", "sre0507")]) ## twin on co-twin: scale sibling relationship rivalry (age 5-9, mean) ## computing mean for every row data_wid1$sreriv_1 <- rowMeans(data_wid1[c("sre0508", "sre0509", "sre0510", "sre0511")]) ## sibling relationship quality, self-report (aged 5 to 9, F2F1 only) ## twin on sibling ## twin on sibling: scale sibling relationship affection (age 5-9, mean) ## computing mean for every row data_wid1$sreaff_1s <- rowMeans(data_wid1[c("sre0500s", "sre0501s", "sre0502s", "sre0503s")]) ## twin on sibling: scale sibling relationship hostility (age 5-9, mean ## computing mean for every row data_wid1$srehos_1s <- rowMeans(data_wid1[c("sre0504s", "sre0505s", "sre0506s", "sre0507s")]) ## twin on sibling: scale sibling relationship rivalry (age 5-9, mean) ## computing mean for every row data_wid1$sreriv_1s <- rowMeans(data_wid1[c("sre0508s", "sre0509s", "sre0510s", "sre0511s")]) ## sibling relationship quality, self-report (aged 5 to 9, F2F1 only) ## sibling on twin1 ## sibling on twin1: scale sibling relationship affection (age 5-9, mean) ## computing mean for every row data_wid1$sreaff_1t <- rowMeans(data_wid1[c("sre0500t", "sre0501t", "sre0502t", "sre0503t")]) ## sibling on twin1: scale sibling relationship hostility (age 5-9, mean ## computing mean for every row data_wid1$srehos_1t <- rowMeans(data_wid1[c("sre0504t", "sre0505t", "sre0506t", "sre0507t")]) ## sibling on twin1: scale sibling relationship rivalry (age 5-9, mean) ## computing mean for every row data_wid1$sreriv_1t <- rowMeans(data_wid1[c("sre0508t", "sre0509t", "sre0510t", "sre0511t")]) ## sibling relationship quality, self-report (aged 5 to 9, F2F1 only) ## sibling on twin2 ## sibling on twin2: scale sibling relationship affection (age 5-9, mean) ## computing mean for every row data_wid1$sreaff_1u <- rowMeans(data_wid1[c("sre0500u", "sre0501u", "sre0502u", "sre0503u")]) ## sibling on twin2: scale sibling relationship hostility (age 5-9, mean ## computing mean for every row data_wid1$srehos_1u <- rowMeans(data_wid1[c("sre0504u", "sre0505u", "sre0506u", "sre0507u")]) ## sibling on twin2: scale sibling relationship rivalry (age 5-9, mean) ## computing mean for every row data_wid1$sreriv_1u <- rowMeans(data_wid1[c("sre0508u", "sre0509u", "sre0510u", "sre0511u")]) ``` ```{r Sibling Relationship Quality 2} ## SRI - Version 2 – Late childhood ## sibling relationship quality, self-report (aged 10 to 14) ## twin on co-twin ## twin on co-twin: scale sibling relationship affection (aged 10 to 14, mean) ## computing mean for every row data_wid1$sreaff_2 <- rowMeans(data_wid1[c("sre0100", "sre0101", "sre0102", "sre0103")]) ## twin on co-twin: scale sibling relationship hostility (aged 10 to 14, mean ## computing mean for every row data_wid1$srehos_2 <- rowMeans(data_wid1[c("sre0104", "sre0105", "sre0106", "sre0107")]) ## twin on co-twin: scale sibling relationship rivalry (aged 10 to 14, mean) ## computing mean for every row data_wid1$sreriv_2 <- rowMeans(data_wid1[c("sre0108", "sre0109", "sre0110", "sre0111")]) ## sibling relationship quality, self-report (aged 10 to 14) ## twin on sibling ## twin on sibling: scale sibling relationship affection (aged 10 to 14, mean) ## computing mean for every row data_wid1$sreaff_2s <- rowMeans(data_wid1[c("sre0100s", "sre0101s", "sre0102s", "sre0103s")]) ## twin on sibling: scale sibling relationship hostility (aged 10 to 14, mean ## computing mean for every row data_wid1$srehos_2s <- rowMeans(data_wid1[c("sre0104s", "sre0105s", "sre0106s", "sre0107s")]) ## twin on sibling: scale sibling relationship rivalry (aged 10 to 14, mean) ## computing mean for every row data_wid1$sreriv_2s <- rowMeans(data_wid1[c("sre0108s", "sre0109s", "sre0110s", "sre0111s")]) ## sibling relationship quality, self-report (aged 10 to 14) ## sibling on twin1 ## sibling on twin1: scale sibling relationship affection (aged 10 to 14, mean) ## computing mean for every row data_wid1$sreaff_2t <- rowMeans(data_wid1[c("sre0100t", "sre0101t", "sre0102t", "sre0103t")]) ## sibling on twin1: scale sibling relationship hostility (aged 10 to 14, mean ## computing mean for every row data_wid1$srehos_2t <- rowMeans(data_wid1[c("sre0104t", "sre0105t", "sre0106t", "sre0107t")]) ## sibling on twin1: scale sibling relationship rivalry (aged 10 to 14, mean) ## computing mean for every row data_wid1$sreriv_2t <- rowMeans(data_wid1[c("sre0108t", "sre0109t", "sre0110t", "sre0111t")]) ## sibling relationship quality, self-report (aged 10 to 14). ## sibling on twin2 ## sibling on twin2: scale sibling relationship affection (aged 10 to 14, mean) ## computing mean for every row data_wid1$sreaff_2u <- rowMeans(data_wid1[c("sre0100u", "sre0101u", "sre0102u", "sre0103u")]) ## sibling on twin2: scale sibling relationship hostility (aged 10 to 14, mean ## computing mean for every row data_wid1$srehos_2u <- rowMeans(data_wid1[c("sre0104u", "sre0105u", "sre0106u", "sre0107u")]) ## sibling on twin2: scale sibling relationship rivalry (aged 10 to 14, mean) ## computing mean for every row data_wid1$sreriv_2u <- rowMeans(data_wid1[c("sre0108u", "sre0109u", "sre0110u", "sre0111u")]) ``` ```{r Sibling Relationship Quality 3} ## ASRQ ## sibling relationship quality, self-report (aged 15 or older) ## twin on co-twin ## twin on co-twin: scale sibling relationship warmth (age >=15, mean) ## computing mean for every row data_wid1$srewarm <- rowMeans(data_wid1[c("sre0200", "sre0300", "sre0302")]) ## twin on co-twin: scale sibling relationship conflict (age >=15, mean) ## computing mean for every row data_wid1$sreconf <- rowMeans(data_wid1[c("sre0201", "sre0202", "sre0301")]) ## twin on co-twin: scale sibling relationship rivalry (age >=15, mean) ## recoding the variables acCording to the manual data_wid1$sre0400.r <- recode(data_wid1$sre0400, "1=2; 2=1; 3=0; 4=1; 5=2") data_wid1$sre0401.r <- recode(data_wid1$sre0401, "1=2; 2=1; 3=0; 4=1; 5=2") data_wid1$sre0402.r <- recode(data_wid1$sre0402, "1=2; 2=1; 3=0; 4=1; 5=2") data_wid1$sre0403.r <- recode(data_wid1$sre0403, "1=2; 2=1; 3=0; 4=1; 5=2") ## computing mean for every row data_wid1$sreriva <- rowMeans(data_wid1[c("sre0400.r", "sre0401.r", "sre0402.r", "sre0403.r")]) ## sibling relationship quality, self-report (aged 15 or older) ## sibling on twin1 ## sibling on twin1: scale sibling relationship warmth (age >=15, mean) ## computing mean for every row data_wid1$srewarm_t <- rowMeans(data_wid1[c("sre0200t", "sre0300t", "sre0302t")]) ## sibling on twin1: scale sibling relationship conflict (age >=15, mean) ## computing mean for every row data_wid1$sreconf_t <- rowMeans(data_wid1[c("sre0201t", "sre0202t", "sre0301t")]) ## sibling on twin1: scale sibling relationship rivalry (age >=15, mean) ## recoding the variables acCording to the manual data_wid1$sre0400t.r <- recode(data_wid1$sre0400t, "1=2; 2=1; 3=0; 4=1; 5=2") data_wid1$sre0401t.r <- recode(data_wid1$sre0401t, "1=2; 2=1; 3=0; 4=1; 5=2") data_wid1$sre0402t.r <- recode(data_wid1$sre0402t, "1=2; 2=1; 3=0; 4=1; 5=2") data_wid1$sre0403t.r <- recode(data_wid1$sre0403t, "1=2; 2=1; 3=0; 4=1; 5=2") ## computing mean for every row data_wid1$sreriva_t <- rowMeans(data_wid1[c("sre0400t.r", "sre0401t.r", "sre0402t.r", "sre0403t.r")]) ## sibling relationship quality, self-report (aged 15 or older) # sibling on twin2 ## sibling on twin2: scale sibling relationship warmth (age >=15, mean) ## computing mean for every row data_wid1$srewarm_u <- rowMeans(data_wid1[c("sre0200u", "sre0300u", "sre0302u")]) ## sibling on twin2: scale sibling relationship conflict (age >=15, mean) ## computing mean for every row data_wid1$sreconf_u <- rowMeans(data_wid1[c("sre0201u", "sre0202u", "sre0301u")]) ## sibling on twin2: scale sibling relationship rivalry (age >=15, mean) ## recoding the variables acCording to the manual data_wid1$sre0400u.r <- recode(data_wid1$sre0400u, "1=2; 2=1; 3=0; 4=1; 5=2") data_wid1$sre0401u.r <- recode(data_wid1$sre0401u, "1=2; 2=1; 3=0; 4=1; 5=2") data_wid1$sre0402u.r <- recode(data_wid1$sre0402u, "1=2; 2=1; 3=0; 4=1; 5=2") data_wid1$sre0403u.r <- recode(data_wid1$sre0403u, "1=2; 2=1; 3=0; 4=1; 5=2") ## computing mean for every row data_wid1$sreriva_u <- rowMeans(data_wid1[c("sre0400u.r", "sre0401u.r", "sre0402u.r", "sre0403u.r")]) ## sibling relationship quality, self-report (aged 15 or older) ## twin on sibling ## twin on sibling: scale sibling relationship warmth (age >=15, mean) ## computing mean for every row data_wid1$srewarm_s <- rowMeans(data_wid1[c("sre0200s", "sre0300s", "sre0302s")]) ## twin on sibling: scale sibling relationship conflict (age >=15, mean) ## computing mean for every row data_wid1$sreconf_s <- rowMeans(data_wid1[c("sre0201s", "sre0202s", "sre0301s")]) ## twin on sibling: scale sibling relationship rivalry (age >=15, mean) ## recoding the variables acCording to the manual data_wid1$sre0400s.r <- recode(data_wid1$sre0400s, "1=2; 2=1; 3=0; 4=1; 5=2") data_wid1$sre0401s.r <- recode(data_wid1$sre0401s, "1=2; 2=1; 3=0; 4=1; 5=2") data_wid1$sre0402s.r <- recode(data_wid1$sre0402s, "1=2; 2=1; 3=0; 4=1; 5=2") data_wid1$sre0403s.r <- recode(data_wid1$sre0403s, "1=2; 2=1; 3=0; 4=1; 5=2") ## computing mean for every row data_wid1$sreriva_s <- rowMeans(data_wid1[c("sre0400s.r", "sre0401s.r", "sre0402s.r", "sre0403s.r")]) ``` ## Quality of Home Environment ```{r Quality of Home Environment} ## self-report (aged 10 or older, F2F1: parental report and child's report of children who are currently living in the household of the parents; F2F2: only child’s report of children who are currently living in the household of the parents). ## please note: hoe0102 corresponds to hoe0100 and is only assessed for parents, whereas hoe0100 is only assessed for children between 10 and 13 years of age. ## scale quality of home environment: self-report (mean) ## inverted item data_wid1$hoe0100.r <- recode(data_wid1$hoe0100, "1=5; 2=4; 3=3; 4=2; 5=1") data_wid1$hoe0102.r <- recode(data_wid1$hoe0102, "1=5; 2=4; 3=3; 4=2; 5=1") data_wid1$hoe0400.r <- recode(data_wid1$hoe0400, "1=5; 2=4; 3=3; 4=2; 5=1") data_wid1$hoe0600.r <- recode(data_wid1$hoe0600, "1=5; 2=4; 3=3; 4=2; 5=1") ## computing mean for every row data_wid1$hoe1 <- rowMeans(data_wid1[c("hoe0102.r", "hoe0200", "hoe0300", "hoe0400.r", "hoe0500", "hoe0600.r")]) data_wid1$hoe2 <- rowMeans(data_wid1[c("hoe0100.r", "hoe0200", "hoe0300", "hoe0400.r", "hoe0500", "hoe0600.r")]) ## scale quality of home environment: self-report (aged 9 or younger, only in F2F2) ## inverted item data_wid3$hoe0110.r <- recode(data_wid3$hoe0110, "1=5; 2=4; 3=3; 4=2; 5=1") data_wid3$hoe0410.r <- recode(data_wid3$hoe0410, "1=5; 2=4; 3=3; 4=2; 5=1") data_wid3$hoe0610.r <- recode(data_wid3$hoe0610, "1=5; 2=4; 3=3; 4=2; 5=1") ## computing mean for every row data_wid3$hoechild <- rowMeans(data_wid3[c("hoe0110.r", "hoe0210", "hoe0310", "hoe0410.r", "hoe0510", "hoe0610.r")]) ## scale quality of home environment: retrospective self-report (children aged 16 or older outside of parental household, F2F1 and F2F2) ## inverted item data_wid1$hoe0101.r <- recode(data_wid1$hoe0101, "1=5; 2=4; 3=3; 4=2; 5=1") data_wid1$hoe0401.r <- recode(data_wid1$hoe0401, "1=5; 2=4; 3=3; 4=2; 5=1") data_wid1$hoe0601.r <- recode(data_wid1$hoe0601, "1=5; 2=4; 3=3; 4=2; 5=1") ## computing mean for every row data_wid1$hoeretro <- rowMeans(data_wid1[c("hoe0101.r", "hoe0201", "hoe0301", "hoe0401.r", "hoe0501", "hoe0601.r")]) ``` ## Media use ```{r Media use} ## Problematic Smartphone use: self-report ## computing mean for every row data_wid5$med <- rowMeans(data_wid5[c("med1200", "med1201", "med1202", "med1203")]) ``` ## Bullying ```{r Bullying} ## Frequency of bullying, self-report (age 10 or older). ## computing mean for every row data_wid3$bulfreq_1 <- rowMeans(data_wid3[c("bul0100", "bul0200", "bul0300", "bul0400")]) ## Burden of bullying, self-report (age 10 or older). ## computing mean for every row data_wid3$bulburd_1 <- rowMeans(data_wid3[c("bul0101", "bul0201", "bul0301", "bul0401")]) ## Frequency of bullying, self-report (age 5 to 9). ## computing mean for every row data_wid3$bulfreq_2 <- rowMeans(data_wid3[c("bul0500", "bul0600", "bul0700", "bul0800")]) ## Burden of bullying, self-report (age 5 to 9). ## computing mean for every row data_wid3$bulburd_1 <- rowMeans(data_wid3[c("bul0501", "bul0601", "bul0701", "bul0801")]) ``` - End of the Script -