Digman97: Factor Correlation Matrices of Big Five Model from Digman...

Digman97R Documentation

Factor Correlation Matrices of Big Five Model from Digman (1997)

Description

The data set includes fourteen studies of the factor correlation matrices of the Five-Factor Model of personality reported by Digman (1997).

Usage

data(Digman97)

Details

A list of data with the following structure:

data

A list of 14 studies of correlation matrices. The variables are Agreeableness (A), Conscientiousness (C), Emotional Stability (ES), Extraversion (E) and Intellect (I)

n

A vector of sample sizes

cluster

Types of participants of the studies

Source

Digman, J.M. (1997). Higher-order factors of the Big Five. Journal of Personality and Social Psychology, 73, 1246-1256.

References

Cheung, M. W.-L., & Chan, W. (2005). Classifying correlation matrices into relatively homogeneous subgroups: A cluster analytic approach. Educational and Psychological Measurement, 65, 954-979.

Examples

## Not run: 
Digman97

##### Fixed-effects TSSEM
fixed1 <- tssem1(Digman97$data, Digman97$n, method="FEM")
summary(fixed1)

## Factor covariance among latent factors
Phi <- matrix(c(1,"0.3*cor","0.3*cor",1), ncol=2, nrow=2)

## Error covariance matrix
Psi <- Diag(c("0.2*e1","0.2*e2","0.2*e3","0.2*e4","0.2*e5"))

## S matrix
S1 <- bdiagMat(list(Psi, Phi))

## This step is not necessary but it is useful for inspecting the model.
dimnames(S1)[[1]] <- dimnames(S1)[[2]] <- c("A","C","ES","E","I","Alpha","Beta")

## Display S1
S1

## A matrix
Lambda <-
matrix(c(".3*Alpha_A",".3*Alpha_C",".3*Alpha_ES",rep(0,5),".3*Beta_E",".3*Beta_I"),
       ncol=2, nrow=5)
A1 <- rbind( cbind(matrix(0,ncol=5,nrow=5), Lambda),
             matrix(0, ncol=7, nrow=2) )

## This step is not necessary but it is useful for inspecting the model.
dimnames(A1)[[1]] <- dimnames(A1)[[2]] <- c("A","C","ES","E","I","Alpha","Beta")

## Display A1
A1

## F matrix to select the observed variables
F1 <- create.Fmatrix(c(1,1,1,1,1,0,0), as.mxMatrix=FALSE)

## Display F1
F1

################################################################################
## Alternative model specification in lavaan model syntax
model <- "## Factor loadings
          Alpha=~A+C+ES
          Beta=~E+I
          ## Factor correlation
          Alpha~~Beta"

## Display the model
plot(model)

RAM <- lavaan2RAM(model, obs.variables=c("A","C","ES","E","I"),
                  A.notation="on", S.notation="with")
RAM

A1 <- RAM$A
S1 <- RAM$S
F1 <- RAM$F

################################################################################
fixed2 <- tssem2(fixed1, Amatrix=A1, Smatrix=S1, Fmatrix=F1,
                 model.name="TSSEM2 Digman97")
summary(fixed2)

## Display the model with the parameter estimates
plot(fixed2)

#### Fixed-effects TSSEM with several clusters
#### Create a variable for different samples
#### Younger participants: Children and Adolescents
#### Older participants: others
cluster <- ifelse(Digman97$cluster %in% c("Children","Adolescents"),
                  yes="Younger participants", no="Older participants")

#### Show the cluster
cluster

## Example of Fixed-effects TSSEM with several clusters
fixed1.cluster <- tssem1(Digman97$data, Digman97$n, method="FEM",
                         cluster=cluster)
summary(fixed1.cluster)

fixed2.cluster <- tssem2(fixed1.cluster, Amatrix=A1, Smatrix=S1, Fmatrix=F1)
#### Please note that the estimates for the younger participants are problematic.
summary(fixed2.cluster)

## Setup two plots
layout(t(1:2))

## Plot the first group
plot(fixed2.cluster[[1]])
title("Younger participants")

## Plot the second group
plot(fixed2.cluster[[2]])
title("Older participants")

#### Random-effects TSSEM with random effects on the diagonals
random1 <- tssem1(Digman97$data, Digman97$n, method="REM",
                  RE.type="Diag")
summary(random1)

random2 <- tssem2(random1, Amatrix=A1, Smatrix=S1, Fmatrix=F1)
summary(random2)

## Display the model with the parameter estimates
plot(random2, color="green")

## End(Not run)

metaSEM documentation built on Aug. 10, 2023, 1:09 a.m.