This is the script i am working from.
library(poLCA) f <-
cbind(bq70,bq72_1,bq72_2,bq72_3,bq72_4,bq72_5,bq72_6,bq72_7,bq73a_1,bq73a_2,bq73a_3,bq73a_4)~
zq88+zq89+dm_zq101_2+dm_zq101_3+dm_zq101_4+dm_zq101_5+dm_zq101_6+dm_zq101_7+dm_zq101_8+dm_zq101_9
for(i in 2:14){max_II<--1000000 min_bic<-100000 for(j in 1:1024){
res<-poLCA(f,BESDATA,nclass=i,maxiter =1000,tol =
1e-5,na.rm=FALSE,probs.start=NULL,nrep=1,verbose=TRUE,calc.se=TRUE) if(res
bic<min_bic){min_bic<-resbic LCA_best_model<-res} }}
I would like to perform a latent class analysis, and also with a
regression. However, the above code takes my pc a very long time to
complete (intel core i5 4690k, 16gb ram).
Is it typical for poLCA to take this long?
Also, is there a line of code that I can use that will stop the loops for
each class once global maximum likelihood has been reached?
N = around 2000.
Thanks!
(very new to R) I use R studio by the way, in case it matters!
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