# #StackBounty: #r #random-variable #random-effects-model #factor-analysis #dimensionality-reduction Is it possible to run an EFA in R th…

### Bounty: 50

Suppose I have the following data, in which 20 participants each rated 10 items on five different dimensions. In reality I have much more of each, but I am just using this as an example.

``````set.seed(123)

library(data.table)
library(psych)

ppt <- rep(1:20, each = 10)
item <- rep(1:10, times = 20)
dim_a <- rnorm(200)
dim_b <- rnorm(200)
dim_c <- rnorm(200)
dim_d <- rnorm(200)
dim_e <- rnorm(200)

d <- as.data.table(cbind(ppt, item, dim_a, dim_b, dim_c, dim_d, dim_e))
``````

I am interested in conducting a factor analysis on the five dimensions. I could do so with something like this. (In this example it suggests no factors be extracted because of the random data, but I proceed as though it suggested two.)

``````parallel <- fa.parallel(d[, c(3:7)], fm = 'pa', fa = 'fa')
efa2 <- fa(d[, c(3:7)], nfactors =2, rotate = "oblimin", fm = 'pa', max.iter = 100000)