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