20200318 EFA

my <- read.csv(file=”efa.csv”,header = T , sep=’,’)

head(my,20)
summary(my)
dim(my)

a <- my[ , c(2:31)]

head(a,20)
str(a)
dim(a)
summary(a)

可以在EXCEL去除編號、性別與教育程度

從原始my data取問卷量表的部分出來

a_nomiss <- na.omit(a)

delete missing data, listwise deletion

head(a_nomiss,20)
str(a_nomiss)
dim(a_nomiss)
summary(a_nomiss)

EFA= Exploratory Factor Analysis

library(psych)
library(GPArotation)

轉軸用

a_nomiss.paf6 = fa(a_nomiss, nfactors=6,rotate=”promax”,SMC=TRUE,fm=”pa”)

a_nomiss.paf6

print(a_nomiss.paf6$loadings, cutoff = 0.3)