resampleT_f: resample when synthetisation created incoherent high and low...

In DanielBonnery/BigSyn: X

Description

resample when synthetisation created incoherent high and low level aggregates

Usage

resampleT_f(.data, variables, verbose = FALSE)

Arguments

.data	data frame to "reduce"
variables	list of variable names roots
verbose	(default FALSE) if verbose, the formulae to compute the new variables is printed.

Details

In the case where marginal presence indicator equals 1 but all cell presence indicators where synthetised to 0, then presence indicators and other variables are resampled from synthetic units with coherent values.

Examples

library(BigSyn)
library(reshape2)
library(data.table)
data(TtableA,package="BigSyn")
variablepct="AA.cont1"
variablespct=variablepct
variablemax="AA.present"
variablesmax=variablemax
ATtableA<-augmentT_f(TtableA,variablesmax=variablesmax,variablespct=variablespct)
set.seed(1)
SATtableA<-BigSyn::SDPSYN2(ATtableA,asis=c("id1a", "id1b"))[[1]]
problems<-SATtableA$AA.cont1_Lb_La>0&!is.na(SATtableA$AA.cont1_Lb_La)&((SATtableA$AA.cont1_Lb_La_Lrn1==0|is.na(SATtableA$AA.cont1_Lb_La_Lrn1))&(SATtableA$AA.cont1_Lb_La_Lrn2==0|is.na(SATtableA$AA.cont1_Lb_La_Lrn2))&(SATtableA$AA.cont1_Lb_La_Lrn3==0|is.na(SATtableA$AA.cont1_Lb_La_Lrn3)))
varcell=c("AA.cont1_Lb_La_Lrn1", "AA.cont1_Lb_La_Lrn2", "AA.cont1_Lb_La_Lrn3")
varcellandpresenceind<-unlist(c(varcell,get_missingind(c(varcell,"AA.cont1_Lb_La"),names(SATtableA)),get_presentind(c(varcell,"AA.cont1_Lb_La"),names(SATtableA))))
replacements<-SATtableA$AA.cont1_Lb_La>0&!is.na(SATtableA$AA.cont1_Lb_La)&!((SATtableA$AA.cont1_Lb_La_Lrn1==0|is.na(SATtableA$AA.cont1_Lb_La_Lrn1))&(SATtableA$AA.cont1_Lb_La_Lrn2==0|is.na(SATtableA$AA.cont1_Lb_La_Lrn2))&(SATtableA$AA.cont1_Lb_La_Lrn3==0|is.na(SATtableA$AA.cont1_Lb_La_Lrn3)))
SATtableA[problems,c("AA.cont1_Lb_La",varcellandpresenceind)][1:3,]
SATtableA[replacements,c("AA.cont1_Lb_La",varcellandpresenceind)][1:3,]
CSATtableA<-resampleT_f(SATtableA,variablespct)
CSATtableA[problems,c("AA.cont1_Lb_La",varcellandpresenceind)][1:3,]
problems2<-CSATtableA$AA.cont1_Lb_La>0&!is.na(CSATtableA$AA.cont1_Lb_La)&
((CSATtableA$AA.cont1_Lb_La_Lrn1==0|is.na(CSATtableA$AA.cont1_Lb_La_Lrn1))&
 (CSATtableA$AA.cont1_Lb_La_Lrn2==0|is.na(CSATtableA$AA.cont1_Lb_La_Lrn2))&
 (CSATtableA$AA.cont1_Lb_La_Lrn3==0|is.na(CSATtableA$AA.cont1_Lb_La_Lrn3)))
any(problems2);sum(problems2)
RCSATtableA<-reduceT_f(CSATtableA,variablespct)
RCSATtableA[problems,intersect(c("AA.cont1_Lb_La",varcellandpresenceind),names(RCSATtableA))][1:3,]
problems3<-RCSATtableA$AA.cont1_Lb_La>0&!is.na(RCSATtableA$AA.cont1_Lb_La)&
((RCSATtableA$AA.cont1_Lb_La_Lrn1==0|is.na(RCSATtableA$AA.cont1_Lb_La_Lrn1))&
 (RCSATtableA$AA.cont1_Lb_La_Lrn2==0|is.na(RCSATtableA$AA.cont1_Lb_La_Lrn2))&
 (RCSATtableA$AA.cont1_Lb_La_Lrn3==0|is.na(RCSATtableA$AA.cont1_Lb_La_Lrn3)))
any(problems3);sum(problems3)
AA<-rbind(RCSATtableA[problems3,intersect(c("AA.cont1_Lb_La",varcellandpresenceind),names(RCSATtableA))],
CSATtableA[problems3,intersect(c("AA.cont1_Lb_La",varcellandpresenceind),names(RCSATtableA))],
SATtableA[problems3,intersect(c("AA.cont1_Lb_La",varcellandpresenceind),names(RCSATtableA))])

AA$y=rep(c("RCSA","CSA","SA"),each=sum(problems3))
AA$x=rep(1:sum(problems3),3)
AA[order(AA$x),]
library(ggplot2);library(dplyr)
xx<-function(x){xxx<-x[sort(grep("present",names(x),value=TRUE))]
xxx[xxx==0]<-NA
StudyDataTools::ggplot_missing(xxx)}
xx(ATtableA)
xx(SATtableA)
xx(CSATtableA)
xx(RCSATtableA)

DanielBonnery/BigSyn documentation built on June 28, 2020, 7:18 p.m.