combine_data_nplcm function

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=100 Y = rep(c(1,0),times=50) # simulate two cases and two controls. out_list <- vector("list",length=N) J = 3 # number of causes cause_list = c(LETTERS[1:J]) # cause list K = 2 # number of subclasses lambda = c(.8,.2) # subclass weights for control group eta = c(.9,.1) # subclass weights for case group for (i in 1: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()

  • Maintainer: Zhenke Wu
  • License: MIT + file LICENSE
  • Last published: 2024-01-30