Participant 002 (12.28.14)
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rm(list = ls())

## Read in data
dat=read.csv('pre002.csv')

## Designate "999" as missing
dat[dat[,]==999] <- NA

## Load Psych package
library(psych)

## Read in CFA loadings
cfaload=read.table('loads.txt')

## Generate Factor Scores
fs=factor.scores(dat[,c(13:14,18:23,24:27)],cfaload[,2:4],method='components')
ts=as.data.frame(fs$scores)

## Create empty data frame "lag"
lag=data.frame(lagf1=numeric(length(latfs[,1])),lagf2=numeric(length(latfs[,1])),lagf3=numeric(length(latfs[,1])))

## Lag factors
lagpad <- function(x, k) {
     c(rep(NA, k), x)[1 : length(x)] 
 }

lag[,1]=lagpad(latfs[,1])
lag[,2]=lagpad(latfs[,2])
lag[,3]=lagpad(latfs[,3])
lag[,4]=latfs[,1]
lag[,5]=latfs[,2]
lag[,6]=latfs[,3]

colnames(lag) <- c("lagf1","lagf2","lagf3","f1","f2","f3")

lag[is.na(lag[,])]<- -999

## Export file for DFA
write.table(lag,'lag.dat',row.names=F,col.names=F)