GERAS {psychTools}

R Documentation

Data from Gruber et al, 2020, Study 2: Gender Related Attributes Survey

Description

Gruber et al. (2020) report on the psychometric properties of a multifaceted Gender Related Attributes Survey. Here are the data from their 3 domains (Personality, Cognition and Activities and Interests from their study 2. Eagly and Revelle (2022) include these data in their review of the power of aggregation. The data are included here as demonstrations of the cohen.d and scatterHist functions in the psych package and may be used to show the power of aggregation.

Usage

data("GERAS")
#These other objects are included in the file
# data("GERAS.scales")
# data("GERAS.dictionary")
# data("GERAS.items")
# data("GERAS.keys")
    

Format

A data frame with 471 observations on the following 51 variables (selected from the original 93) The code numbers are item numbers from the bigger set.

V15

reckless

V22

willing to take risks

V11

courageous

V6

a adventurous

V19

dominant

V14

controlling

V20

boastful

V21

rational

V23

analytical

V9

pragmatic

V44

to find an address for the first time

V45

to find a way again

V46

to understand equations

V50

to follow directions

V51

to understand equations

V53

day-to-day calculations

V48

to write a computer program

V69

paintball

V73

driving go-cart

V71

drinking beer

V68

watching action movies

V75

playing cards (poker)

V72

watching sports on TV

V67

doing certain sports (e.g. soccer, ...)

V74

Gym (weightlifting)

V27

warm-hearted

V28

loving

V29

caring

V26

compassionate

V32

delicate

V30

tender

V24

familiy-oriented

V40

anxious

V39

thin-skinned

V41

careful

V55

to explain foreign words

V58

to find the right words to express certain content

V59

synonyms for a word in order to avoid repetitions

V60

to phrase a text

V54

remembering events from your own life

V63

to notice small changes

V57

to remember names and faces

V89

shopping

V92

gossiping

V81

watching a romantic movie

V80

talking on the phone with a friend

V90

yoga

V83

rhythmic gymnastics

V84

going for a walk

V86

dancing

gender

gender (M=1 F=2)

Details

These 50 items (+ gender) may be formed into scales using the GERAS.keys The first 10 items are Male Personality, the next 10 are Female Personality, then 7 and 7 M and F Cognition, then 8 and 8 M and F Activity items. The Pers, Cog and Act scales are formed from the M-F scales for the three domains. M and F are the composites of the Male and then the Female scales. MF.all is the composite of the M - F scales. See the GERAS.keys object for scoring directions.

"M.pers" "F.pers" "M.cog" "F.cog" "M.act" "F.act" "Pers" "Cog" "Act" "M" "F" "MF.all" "gender"

See the Athenstaedt data set for a related data set.

Source

Study 2 data downloaded from the Open Science Framework https://osf.io/42jhr/ Used by kind permission of Freya M. Gruber, Tullia Ortner, and Belinda A. Pletzer.

References

Alice H. Eagly and William Revelle (2022), Understanding the Magnitude of Psychological Differences Between Women and Men Requires Seeing the Forest and the Tree. Perspectives in Psychological Science doi:10.1177/17456916211046006

Gruber, Freya M. and Distlberger, Eva and Scherndl, Thomas and Ortner, Tuulia M. and Pletzer, Belinda (2020) Psychometric properties of the multifaceted Gender-Related Attributes Survey (GERAS) European Journal of Psychological Assessment, 36, (4) 612-623.

Examples

data(GERAS)
GERAS.keys  #show the keys
#show the items from the dictionary
psych::lookupFromKeys(GERAS.keys, GERAS.dictionary[,4,drop=FALSE])


#now, use the GERAS.scales to show a scatterHist  plot showing univariate d and bivariate 
# Mahalanobis D.

psych::scatterHist(F ~ M + gender, data=GERAS.scales, cex.point=.3,smooth=FALSE, 
xlab="Masculine Scale",ylab="Feminine Scale",correl=FALSE, 
d.arrow=TRUE,col=c("red","blue"), bg=c("red","blue"), lwd=4, 
title="Combined  M and F scales",cex.cor=2,cex.arrow=1.25, cex.main=2)

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