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subset data from the output of clean_perch_data()

Source: R/utils.R
subset_data_nplcm_by_index.Rd

It is particularly useful in simulating data from a regression model where one generates a case and control at a particular covariate value, and just choose a case or control to retain in the simulated data.

Usage

subset_data_nplcm_by_index(data_nplcm, index)

Arguments

data_nplcm

data for fitting nplcm; See nplcm()

index

a vector of indices indicating the observations you hope to subset; it will subset in all the sublists of data_nplcm

Value

a list with the requested data, in the order determined by 'index'

See also

Other data operation functions: combine_data_nplcm(), merge_lists()

Examples


J = 3                          # number of causes
cause_list = c(LETTERS[1:J])   # cause list
K = 2                          # number of subclasses
lambda = c(1,0)                # subclass weights for control group
eta = c(1,0)                   # subclass weights for case group

# 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      =     5,
 Nu      =     3 
)
simu_out   <- simulate_nplcm(set_parameter)
out <- simu_out$data_nplcm
out
#> $Mobs
#> $Mobs$MBS
#> $Mobs$MBS$MBS1
#>   A B C
#> 1 1 0 0
#> 2 1 0 0
#> 3 0 0 0
#> 4 1 1 1
#> 5 1 1 0
#> 6 1 0 1
#> 7 0 0 0
#> 8 1 0 0
#> 
#> 
#> $Mobs$MSS
#> $Mobs$MSS$MSS1
#>   A B
#> 1 0 0
#> 2 1 0
#> 3 0 0
#> 4 0 0
#> 5 0 0
#> 6 0 0
#> 7 0 0
#> 8 0 0
#> 
#> 
#> $Mobs$MGS
#> NULL
#> 
#> 
#> $Y
#> [1] 1 1 1 1 1 0 0 0
#> 
#> $X
#> NULL
#> 
subset_data_nplcm_by_index(out,c(1,4,5))
#> $Mobs
#> $Mobs$MBS
#> $Mobs$MBS$MBS1
#>   A B C
#> 1 1 0 0
#> 4 1 1 1
#> 5 1 1 0
#> 
#> 
#> $Mobs$MSS
#> $Mobs$MSS$MSS1
#>   A B
#> 1 0 0
#> 4 0 0
#> 5 0 0
#> 
#> 
#> 
#> $Y
#> [1] 1 1 1
#> 
#> $X
#> NULL
#> 
subset_data_nplcm_by_index(out,2)
#> $Mobs
#> $Mobs$MBS
#> $Mobs$MBS$MBS1
#>   A B C
#> 2 1 0 0
#> 
#> 
#> $Mobs$MSS
#> $Mobs$MSS$MSS1
#>   A B
#> 2 1 0
#> 
#> 
#> 
#> $Y
#> [1] 1
#> 
#> $X
#> NULL
#>