R Dataset / Package psych / epi
On this Rdata statistics page, you will find information about the epi data set which pertains to Eysenck Personality Inventory (EPI) data for 3570 participants. The epi data set is found in the psych R package. You can load the epi data set in R by issuing the following command at the console data("epi"). This will load the data into a variable called epi. If R says the epi data set is not found, you can try installing the package by issuing this command install.packages("psych") and then attempt to reload the data with the library() command. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the epi R data set. The size of this file is about 412,059 bytes.
Eysenck Personality Inventory (EPI) data for 3570 participants
Description
The EPI is and has been a very frequently administered personality test with 57 measuring two broad dimensions, ExtraversionIntroversion and StabilityNeuroticism, with an additional Lie scale. Developed by Eysenck and Eysenck, 1964. Eventually replaced with the EPQ which measures three broad dimensions. This data set represents 3570 observations collected in the early 1990s at the Personality, Motivation and Cognition lab at Northwestern. The data are included here as demonstration of scale construction.
Usage
data(epi) data(epi.dictionary)
Format
A data frame with 3570 observations on the following 57 variables.
V1

a numeric vector
V2

a numeric vector
V3

a numeric vector
V4

a numeric vector
V5

a numeric vector
V6

a numeric vector
V7

a numeric vector
V8

a numeric vector
V9

a numeric vector
V10

a numeric vector
V11

a numeric vector
V12

a numeric vector
V13

a numeric vector
V14

a numeric vector
V15

a numeric vector
V16

a numeric vector
V17

a numeric vector
V18

a numeric vector
V19

a numeric vector
V20

a numeric vector
V21

a numeric vector
V22

a numeric vector
V23

a numeric vector
V24

a numeric vector
V25

a numeric vector
V26

a numeric vector
V27

a numeric vector
V28

a numeric vector
V29

a numeric vector
V30

a numeric vector
V31

a numeric vector
V32

a numeric vector
V33

a numeric vector
V34

a numeric vector
V35

a numeric vector
V36

a numeric vector
V37

a numeric vector
V38

a numeric vector
V39

a numeric vector
V40

a numeric vector
V41

a numeric vector
V42

a numeric vector
V43

a numeric vector
V44

a numeric vector
V45

a numeric vector
V46

a numeric vector
V47

a numeric vector
V48

a numeric vector
V49

a numeric vector
V50

a numeric vector
V51

a numeric vector
V52

a numeric vector
V53

a numeric vector
V54

a numeric vector
V55

a numeric vector
V56

a numeric vector
V57

a numeric vector
Details
The original data were collected in a group testing framework for screening participants for subsequent studies. The participants were enrolled in an introductory psychology class between Fall, 1991 and Spring, 1995.
The structure of the E scale has been shown by Rocklin and Revelle (1981) to have two subcomponents, Impulsivity and Sociability. These were subsequently used by Revelle, Humphreys, Simon and Gilliland to examine the relationship between personality, caffeine induced arousal, and cognitive performance.
Source
Data from the PMC laboratory at Northwestern.
References
Eysenck, H.J. and Eysenck, S. B.G. (1968). Manual for the Eysenck Personality Inventory.Educational and Industrial Testing Service, San Diego, CA.
Rocklin, T. and Revelle, W. (1981). The measurement of extraversion: A comparison of the Eysenck Personality Inventory and the Eysenck Personality Questionnaire. British Journal of Social Psychology, 20(4):279284.
Examples
data(epi) epi.keys < make.keys(epi,list(E = c(1, 3, 5, 8, 10, 13, 15, 17, 20, 22, 25, 27, 29, 32, 34, 37, 39, 41, 44, 46, 49, 51, 53, 56), N=c(2, 4, 7, 9, 11, 14, 16, 19, 21, 23, 26, 28, 31, 33, 35, 38, 40, 43, 45, 47, 50, 52, 55, 57), L = c(6, 12, 18, 24, 30, 36, 42, 48, 54), I =c(1, 3, 5, 8, 10, 13, 22, 39, 41), S = c(11, 15, 17, 20, 25, 27, 29, 32, 37, 44, 46, 51, 53))) scores < scoreItems(epi.keys,epi) N < epi[abs(epi.keys[,"N"]) >0] E < epi[abs(epi.keys[,"E"]) >0] fa.lookup(epi.keys[,1:3],epi.dictionary) #show the items and keying information
Dataset imported from https://www.rproject.org.