combine multiple data_nplcm (useful when simulating data from regression models)
combine multiple data_nplcm (useful when simulating data from regression models)
combine_data_nplcm(data_nplcm_list)
Arguments
data_nplcm_list: a list of data_nplcm in nplcm()
Returns
a list with each element resulting from row binding of each corresponding element in the input data_nplcm_list.
Examples
N=100Y = rep(c(1,0),times=50)# simulate two cases and two controls.out_list <- vector("list",length=N)J =3# number of causescause_list = c(LETTERS[1:J])# cause listK =2# number of subclasseslambda = c(.8,.2)# subclass weights for control groupeta = c(.9,.1)# subclass weights for case groupfor(i in1:N){#setup parameters for the present individual: set_parameter <- list( cause_list = cause_list, etiology = c(0.5,0.2,0.3),# only meaningful for cases pathogen_BrS = LETTERS[1:J], pathogen_SS = LETTERS[1:2], meas_nm = list(MBS = c("MBS1"),MSS=c("MSS1")), Lambda = lambda,# for BrS Eta = t(replicate(J,eta)),# case subclass weight for BrS PsiBS = cbind(c(0.15,0.3,0.35), c(0.25,0.2,0.15)),# FPR PsiSS = cbind(rep(0,J),rep(0,J)), ThetaBS = cbind(c(0.95,0.9,0.85),# TPR c(0.95,0.9,0.85)), ThetaSS = cbind(c(0.25,0.10), c(0.25,0.10)), Nd =1, Nu =1) simu_out <- simulate_nplcm(set_parameter) out <- simu_out$data_nplcm
out_list[[i]]<- out
}# extract cases and controls and combine all the data into one:data_nplcm_list <- lapply(1:N,function(s) subset_data_nplcm_by_index(out_list[[s]],2-Y[s]))data_nplcm_unordered <- combine_data_nplcm(data_nplcm_list)
See Also
Other data operation functions: merge_lists(), subset_data_nplcm_by_index()