Dear All:
I am conducting a Confirmatory Factor Analysis (CFA) for the attached data.
Here is what I did. please see below
I do need your help with the structure of the model. I believe that what I
used is the correlated CFA model. If I am wrong, please fix me. I need your
help with the structure of the CFA uncorrelated model.
Thank you very much for your help in advance
Abou
datacfa<-read.table("G:/data_for_R.txt", header=TRUE)
head(datacfa)
install.packages("lavaan")
library(lavaan)
install.packages("semPlot")
library(semPlot)
install.packages("parameters")
library(parameters)
#### model structure
CAF.Factors <- 'Factor1 =~ X11 + X13 + X14 + X15 + X17
Factor2 =~ X6 + X7 + X12 + X16 + X19
Factor3 =~ X9 + X18 + X21
Factor4 =~ X19 + X20 + X22'
fourfactors.model.a <- cfa(CAF.Factors, data=datacfa,std.lv=TRUE)
summary(fourfactors.model.a, fit.measures=TRUE,standardized=TRUE)
semPaths(fourfactors.model.a, ncharNodes = 0, style = "lisrel", rotation =
2)
##### model_parameters(fourfactors.model.a)
model_parameters(fourfactors.model.a, standardize = TRUE)
______________________
*AbouEl-Makarim Aboueissa, PhD*
*Professor, Statistics and Data Science*
*Graduate Coordinator*
*Department of Mathematics and Statistics*
*University of Southern Maine*
X6 X7 X8 X9 X10 X11 X12 X13 X14 X15
X16 X17 X18 X19 X20 X21 X22
5 NA 2 1 4 4 5 5 5 5
5 5 2 5 5 1 4
4 NA 3 2 4 5 5 NA 5 4
5 4 2 5 5 1 4
5 5 5 1 5 3 5 3 4 4
5 4 1 5 5 2 4
3 3 3 3 3 3 3 3 3 3
3 3 3 3 3 3 3
3 3 3 3 3 3 3 3 3 3
3 3 3 3 3 3 3
3 2 4 2 4 3 3 4 4 4
4 4 1 4 4 2 2
3 4 5 2 2 4 3 4 4 4
4 5 2 3 4 2 3
4 NA 5 2 3 5 5 3 4 3
5 3 2 5 4 3 5
4 NA 3 1 2 4 5 4 4 3
5 5 2 5 4 3 4
5 NA 5 1 1 5 5 5 5 5
5 3 3 5 3 3 5
3 NA 4 2 4 4 4 3 4 4
4 4 4 4 2 2 2
3 NA 4 2 2 4 4 2 5 2
4 4 2 4 4 3 4
3 4 4 3 3 3 3 3 3 3
4 4 NA 3 3 3 3
4 5 5 1 3 4 5 4 5 4
4 4 2 4 4 3 4
5 5 5 2 3 5 5 3 4 5
5 2 1 5 5 1 4
4 4 4 2 2 4 4 3 4 4
4 4 2 5 4 2 5
NA 5 4 1 1 3 4 3 5 NA
3 4 2 4 4 NA 4
5 4 3 1 2 3 4 4 4 3
4 3 2 4 4 2 4
4 4 4 2 1 4 4 4 4 4
4 3 1 5 4 1 5
5 5 3 1 3 5 5 3 5 4
4 4 1 5 5 1 5
4 5 5 2 3 4 5 5 5 5
5 5 1 5 5 3 5
4 5 4 2 NA 5 5 5 5 5
5 5 1 5 5 NA 5
5 5 4 1 3 4 5 5 5 5
5 5 1 5 5 1 4
5 5 4 2 4 5 5 5 5 4
5 5 1 5 5 2 5
5 5 5 1 NA 4 5 5 5 NA
5 5 1 5 5 1 5
4 4 3 2 4 4 4 4 4 3
4 4 2 4 4 1 5
4 5 5 1 2 4 5 3 5 5
4 4 1 5 4 3 4
3 4 5 1 4 5 3 3 5 4
4 5 2 5 4 1 4
3 4 4 2 1 4 NA 4 4 3
4 4 NA 4 4 2 3
4 4 3 1 3 4 5 3 5 4
4 3 4 5 5 3 5
4 4 4 2 2 4 3 3 4 4
3 3 4 3 4 3 3
5 5 5 1 1 5 5 5 5 5
5 5 1 5 5 1 5
4 4 4 1 NA 4 4 4 4 4
4 NA 1 4 4 1 4
5 5 3 1 2 4 5 5 5 5
5 5 2 5 5 1 5
4 4 4 2 4 5 4 4 5 4
4 5 2 5 5 2 5
3 5 3 1 1 1 5 5 3 3
4 3 3 4 3 1 3
5 5 NA 1 NA NA 5 NA 5 NA
5 NA 1 5 5 1 NA
5 5 5 2 2 4 5 3 4 4
5 4 2 4 4 3 3
4 4 1 1 4 3 4 3 4 3
4 5 1 3 3 2 2
5 4 3 1 5 4 5 3 3 3
4 4 1 4 5 1 4
5 5 2 1 2 4 5 5 2 4
5 4 2 4 4 2 2
4 4 5 2 4 5 4 5 5 4
5 4 4 5 4 3 5
4 4 4 1 1 5 5 5 4 4
5 4 NA 5 5 1 3
5 5 2 1 4 2 5 2 4 4
4 5 1 4 4 1 4
5 5 4 2 2 2 5 2 5 5
5 5 2 5 4 4 4
5 4 3 1 4 4 5 3 4 4
5 5 1 5 5 1 4
4 5 5 4 2 4 4 4 4 4
4 4 2 4 4 NA 4
3 5 4 2 3 4 5 5 5 5
5 5 1 5 5 2 1
3 4 4 2 2 3 4 4 5 4
5 4 2 5 5 3 4
5 5 4 1 3 4 5 3 4 2
4 4 1 5 4 1 4
4 4 4 1 5 4 4 4 4 4
3 3 2 4 4 2 4
3 5 3 4 3 3 4 3 4 3
5 4 3 5 5 3 4
2 4 4 2 4 4 4 4 4 4
4 4 2 4 4 2 4
1 3 1 1 2 4 4 2 4 5
3 5 2 3 4 1 5
1 3 3 3 3 3 3 3 3 3
3 3 3 3 3 3 3
4 5 5 2 2 4 5 4 5 5
4 5 2 4 5 1 4
4 5 4 1 3 4 5 4 4 4
4 5 1 5 4 1 3
5 4 4 2 4 3 4 4 4 3
4 4 2 4 4 1 4
4 4 4 1 4 4 4 4 4 3
4 4 3 4 4 1 3
4 2 2 1 4 4 4 4 4 4
4 4 4 4 4 4 4
4 4 4 2 2 4 4 2 4 2
4 4 2 4 4 2 4
3 5 2 2 4 4 4 3 4 2
4 4 2 4 4 2 2
4 4 5 2 3 5 5 4 4 4
4 3 4 4 NA 3 3
5 4 4 2 NA NA 5 4 4 NA
4 4 2 5 4 NA NA
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