#' First, reading in the data:
#' 
library(foreign)
setwd('C:/Users/flournoy/Downloads')

pdr2<-read.spss("PDR Wave 2.sav", to.data.frame=T)
pdr4<-read.spss("PDR Wave 4.sav", to.data.frame=T)
head(pdr2)
summary(pdr2)

#' ## Generate a time variable
#' 
#' This indexes each call for each family. This time variable
#' will be important later for widening the data for SEM.
#' 
library(dplyr)

pdr2_time <- pdr2 %>%
group_by(FAMILY) %>% #do the count by family
 arrange(YEAR,MONTH,DAY) %>% #sort by date
 mutate(callindex=1:n()) #create call index that’s 1:end for each family

head(pdr2_time)

#' ## Create composite score of kid bex
#' 
#' Scores Found in (cols 8:47).

library(car)
#?recode
## recode all of the kid behavior items into numeric variables in one go
# ignore difference between “occurred, stressed” and “occurred, not stressed”
# (if it occurred at all, it gets a 1; if it didn’t occur, it’s a 0)
# the defaults for as.XX.result are both TRUE; if you leave it that way,
# it will return character variables.

pdr2_time[,8:47]<-sapply(pdr2_time[,8:47],
 function(x)
 {x<-recode(x,"'DID NOT OCCUR'='0'; else = '1'",
 as.factor.result=F, as.numeric.result=T)})

head(pdr2_time)
str(pdr2_time)

#' Now we can create the composite (sum) variable
#' 
pdr2_time$bextot<-rowSums(pdr2_time[,8:47],na.rm=F)

summary(pdr2_time$bextot)