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14_create_table_3.R
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1650 lines (1564 loc) · 80.5 KB
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sink("D:\\projects\\nhood_mediation_lead\\programs\\_LOGS\\14_create_table_3_log.txt")
print(Sys.time())
################################################
################################################
## ##
## PROGRAM NAME: 14_create_table_3 ##
## AUTHOR: GW ##
## DATE: 8/7/2020 ##
## DESCRIPTION: ##
## ##
## creates table of nh effect estimates ##
## ##
################################################
################################################
rm(list=ls())
library(haven)
library(foreign)
library(ebal)
library(dplyr)
library(tidyr)
library(CBPS)
library(IDPmisc)
library(ggplot2)
library(survey)
library(mgcv)
library(geeM)
##### LOAD PHDCN #####
phdcnmi<-read.dta("D:\\projects\\nhood_mediation_lead\\data\\v02_phdcn_merged_mi.dta")
phdcnmi<-phdcnmi[which((phdcnmi$"_mj"!=0)),]
##### COMPUTE RWR EFFECT ESTIMATES #####
set.seed(8675309)
nmi<-50
nboot<-500
astar<-0.70
a<-(-0.90)
mstar<-0.65
m<-0.30
miest.rwr<-mivar.rwr<-matrix(data=NA,nrow=nmi,ncol=5)
miest.rwr.gen<-mivar.rwr.gen<-matrix(data=NA,nrow=nmi,ncol=5)
miest.rwr.race<-mivar.rwr.race<-matrix(data=NA,nrow=nmi,ncol=5)
miest.rwr.inc<-mivar.rwr.inc<-matrix(data=NA,nrow=nmi,ncol=5)
for (i in 1:nmi) {
# LOAD MI DATA #
phdcn<-phdcnmi[which(phdcnmi$"_mj"==i),]
# RESIDUALIZE CONFOUNDERS #
resid_l1<-function(y) { residuals(lm(y~1,data=phdcn)) }
resid_l2<-function(y) { residuals(lm(y~npcage_b+npchsgrad_b+npcsomcol_b+npccolgrd_b+nownhome_b+nfemale_b+nblack_b+nhispan_b+nothrace_b+nfamsize_b+
nlninc_1+npcemply_1+npcwelf_1+npcmarr_1+npcengl_1+ncondadvg_1+nbl5ug_1,data=phdcn)) }
resid_l3<-function(y) { residuals(lm(y~npcage_b+npchsgrad_b+npcsomcol_b+npccolgrd_b+nownhome_b+nfemale_b+nblack_b+nhispan_b+nothrace_b+nfamsize_b+
nlninc_1+npcemply_1+npcwelf_1+npcmarr_1+npcengl_1+ncondadvg_1+nbl5ug_1+
nlninc_2+npcemply_2+npcwelf_2+npcmarr_2+npcengl_2+ncondadvg_2+nbl5ug_2,data=phdcn)) }
phdcn<-phdcn %>% mutate_at(vars(npcage_b,npchsgrad_b,npcsomcol_b,npccolgrd_b,nownhome_b,nfemale_b,nblack_b,nhispan_b,nothrace_b,nfamsize_b), funs(r=resid_l1))
phdcn<-phdcn %>% mutate_at(vars(nlninc_1,npcemply_1,npcwelf_1,npcmarr_1,npcengl_1), funs(r=resid_l1))
phdcn<-phdcn %>% mutate_at(vars(nlninc_2,npcemply_2,npcwelf_2,npcmarr_2,npcengl_2), funs(r=resid_l2))
phdcn<-phdcn %>% mutate_at(vars(nlninc_3,npcemply_3,npcwelf_3,npcmarr_3,npcengl_3), funs(r=resid_l3))
phdcn$nbl5ug_1_r<-residuals(lm(nbl5ug_1~npcage_b+npchsgrad_b+npcsomcol_b+npccolgrd_b+nownhome_b+nfemale_b+nblack_b+nhispan_b+nothrace_b+nfamsize_b+
nlninc_1+npcemply_1+npcwelf_1+npcmarr_1+npcengl_1+ncondadvg_1,data=phdcn))
phdcn$nbl5ug_2_r<-residuals(lm(nbl5ug_2~npcage_b+npchsgrad_b+npcsomcol_b+npccolgrd_b+nownhome_b+nfemale_b+nblack_b+nhispan_b+nothrace_b+nfamsize_b+
nlninc_1+npcemply_1+npcwelf_1+npcmarr_1+npcengl_1+ncondadvg_1+nbl5ug_1+
nlninc_2+npcemply_2+npcwelf_2+npcmarr_2+npcengl_2+ncondadvg_2,data=phdcn))
phdcn$nbl5ug_3_r<-residuals(lm(nbl5ug_3~npcage_b+npchsgrad_b+npcsomcol_b+npccolgrd_b+nownhome_b+nfemale_b+nblack_b+nhispan_b+nothrace_b+nfamsize_b+
nlninc_1+npcemply_1+npcwelf_1+npcmarr_1+npcengl_1+ncondadvg_1+nbl5ug_1+
nlninc_2+npcemply_2+npcwelf_2+npcmarr_2+npcengl_2+ncondadvg_2+nbl5ug_2+
nlninc_3+npcemply_3+npcwelf_3+npcmarr_3+npcengl_3+ncondadvg_3,data=phdcn))
phdcn$nsubage_3_r<-residuals(lm(nsubage_3~npcage_b+npchsgrad_b+npcsomcol_b+npccolgrd_b+nownhome_b+nfemale_b+nblack_b+nhispan_b+nothrace_b+nfamsize_b+
nlninc_1+npcemply_1+npcwelf_1+npcmarr_1+npcengl_1+ncondadvg_1+nbl5ug_1+
nlninc_2+npcemply_2+npcwelf_2+npcmarr_2+npcengl_2+ncondadvg_2+nbl5ug_2+
nlninc_3+npcemply_3+npcwelf_3+npcmarr_3+npcengl_3+ncondadvg_3+nbl5ug_3,data=phdcn))
# COMPUTE NEW VARIABLES #
phdcn$nlninc_s_r<-phdcn$nlninc_1_r+phdcn$nlninc_2_r+phdcn$nlninc_3_r
phdcn$npcemply_s_r<-phdcn$npcemply_1_r+phdcn$npcemply_2_r+phdcn$npcemply_3_r
phdcn$npcwelf_s_r<-phdcn$npcwelf_1_r+phdcn$npcwelf_2_r+phdcn$npcwelf_3_r
phdcn$npcmarr_s_r<-phdcn$npcmarr_1_r+phdcn$npcmarr_2_r+phdcn$npcmarr_3_r
phdcn$npcengl_s_r<-phdcn$npcengl_1_r+phdcn$npcengl_2_r+phdcn$npcengl_3_r
phdcn$nbl5ug_s_r<-phdcn$nbl5ug_1_r+phdcn$nbl5ug_2_r+phdcn$nbl5ug_3_r
phdcn$cumndadvg<-(phdcn$ncondadvg_1+phdcn$ncondadvg_2+phdcn$ncondadvg_3)/3
phdcn$cumnbl5ug<-(phdcn$nbl5ug_1+phdcn$nbl5ug_2+phdcn$nbl5ug_3)/3
phdcn$nppvt_3<-(phdcn$nppvt_3-mean(phdcn$nppvt_3))/sd(phdcn$nppvt_3)
# FIT MODELS #
# BASE MODEL #
m1<-lm(nppvt_3~npcage_b_r+npchsgrad_b_r+npcsomcol_b_r+npccolgrd_b_r+nownhome_b_r+nfemale_b_r+nblack_b_r+nhispan_b_r+nothrace_b_r+nfamsize_b_r+
nsubage_3_r+nbl5ug_s_r+nlninc_s_r+npcemply_s_r+npcwelf_s_r+npcmarr_s_r+npcengl_s_r+cumndadvg,data=phdcn)
m2<-lm(nppvt_3~npcage_b_r+npchsgrad_b_r+npcsomcol_b_r+npccolgrd_b_r+nownhome_b_r+nfemale_b_r+nblack_b_r+nhispan_b_r+nothrace_b_r+nfamsize_b_r+
nsubage_3_r+nlninc_s_r+npcemply_s_r+npcwelf_s_r+npcmarr_s_r+npcengl_s_r+cumndadvg+cumnbl5ug,data=phdcn)
# BASE + GENDER MODERATION #
m1.gen<-lm(nppvt_3~npcage_b_r+npchsgrad_b_r+npcsomcol_b_r+npccolgrd_b_r+nownhome_b_r+nfemale_b_r+nblack_b_r+nhispan_b_r+nothrace_b_r+nfamsize_b_r+
nsubage_3_r+nbl5ug_s_r+nlninc_s_r+npcemply_s_r+npcwelf_s_r+npcmarr_s_r+npcengl_s_r+cumndadvg+
(cumndadvg*nfemale_b_r),data=phdcn)
m2.gen<-lm(nppvt_3~npcage_b_r+npchsgrad_b_r+npcsomcol_b_r+npccolgrd_b_r+nownhome_b_r+nfemale_b_r+nblack_b_r+nhispan_b_r+nothrace_b_r+nfamsize_b_r+
nsubage_3_r+nlninc_s_r+npcemply_s_r+npcwelf_s_r+npcmarr_s_r+npcengl_s_r+cumndadvg+cumnbl5ug+
(cumndadvg*nfemale_b_r)+(cumnbl5ug*nfemale_b_r),data=phdcn)
# BASE + RACE MODERATION #
m1.race<-lm(nppvt_3~npcage_b_r+npchsgrad_b_r+npcsomcol_b_r+npccolgrd_b_r+nownhome_b_r+nfemale_b_r+nblack_b_r+nhispan_b_r+nothrace_b_r+nfamsize_b_r+
nsubage_3_r+nbl5ug_s_r+nlninc_s_r+npcemply_s_r+npcwelf_s_r+npcmarr_s_r+npcengl_s_r+cumndadvg+
(cumndadvg*nblack_b_r)+(cumndadvg*nhispan_b_r),data=phdcn)
m2.race<-lm(nppvt_3~npcage_b_r+npchsgrad_b_r+npcsomcol_b_r+npccolgrd_b_r+nownhome_b_r+nfemale_b_r+nblack_b_r+nhispan_b_r+nothrace_b_r+nfamsize_b_r+
nsubage_3_r+nlninc_s_r+npcemply_s_r+npcwelf_s_r+npcmarr_s_r+npcengl_s_r+cumndadvg+cumnbl5ug+
(cumndadvg*nblack_b_r)+(cumndadvg*nhispan_b_r)+(cumnbl5ug*nblack_b_r)+(cumnbl5ug*nhispan_b_r),data=phdcn)
# BASE + INCOME MODERATION #
m1.inc<-lm(nppvt_3~npcage_b_r+npchsgrad_b_r+npcsomcol_b_r+npccolgrd_b_r+nownhome_b_r+nfemale_b_r+nblack_b_r+nhispan_b_r+nothrace_b_r+nfamsize_b_r+
nsubage_3_r+nbl5ug_s_r+nlninc_s_r+npcemply_s_r+npcwelf_s_r+npcmarr_s_r+npcengl_s_r+cumndadvg+
(cumndadvg*nlninc_s_r),data=phdcn)
m2.inc<-lm(nppvt_3~npcage_b_r+npchsgrad_b_r+npcsomcol_b_r+npccolgrd_b_r+nownhome_b_r+nfemale_b_r+nblack_b_r+nhispan_b_r+nothrace_b_r+nfamsize_b_r+
nsubage_3_r+nlninc_s_r+npcemply_s_r+npcwelf_s_r+npcmarr_s_r+npcengl_s_r+cumndadvg+cumnbl5ug+
(cumndadvg*nlninc_s_r)+(cumnbl5ug*nlninc_s_r),data=phdcn)
# TOTAL EFFECT OF NHOOD POVERTY #
miest.rwr[i,1]<-m1$coefficients["cumndadvg"]*(astar-a)
miest.rwr.gen[i,1]<-m1.gen$coefficients["cumndadvg"]*(astar-a)
miest.rwr.race[i,1]<-m1.race$coefficients["cumndadvg"]*(astar-a)
miest.rwr.inc[i,1]<-m1.inc$coefficients["cumndadvg"]*(astar-a)
# JOINT EFFECT OF NHOOD POVERTY AND ENVIRONMENTAL LEAD CONTAMINATION #
miest.rwr[i,2]<-m2$coefficients["cumndadvg"]*(astar-a)+m2$coefficients["cumnbl5ug"]*(mstar-m)
miest.rwr.gen[i,2]<-m2.gen$coefficients["cumndadvg"]*(astar-a)+m2.gen$coefficients["cumnbl5ug"]*(mstar-m)
miest.rwr.race[i,2]<-m2.race$coefficients["cumndadvg"]*(astar-a)+m2.race$coefficients["cumnbl5ug"]*(mstar-m)
miest.rwr.inc[i,2]<-m2.inc$coefficients["cumndadvg"]*(astar-a)+m2.inc$coefficients["cumnbl5ug"]*(mstar-m)
# CONTROLLED DIRECT EFFECT OF NHOOD POVERTY #
miest.rwr[i,3]<-m2$coefficients["cumndadvg"]*(astar-a)
miest.rwr.gen[i,3]<-m2.gen$coefficients["cumndadvg"]*(astar-a)
miest.rwr.race[i,3]<-m2.race$coefficients["cumndadvg"]*(astar-a)
miest.rwr.inc[i,3]<-m2.inc$coefficients["cumndadvg"]*(astar-a)
# CONTROLLED MEDIATOR EFFECT OF ENVIRONMENTAL LEAD CONTAMINATION #
miest.rwr[i,4]<-m2$coefficients["cumnbl5ug"]*(mstar-m)
miest.rwr.gen[i,4]<-m2.gen$coefficients["cumnbl5ug"]*(mstar-m)
miest.rwr.race[i,4]<-m2.race$coefficients["cumnbl5ug"]*(mstar-m)
miest.rwr.inc[i,4]<-m2.inc$coefficients["cumnbl5ug"]*(mstar-m)
# DIFFERENCE BETWEEN ATE AND CDE #
miest.rwr[i,5]<-miest.rwr[i,1]-miest.rwr[i,3]
miest.rwr.gen[i,5]<-miest.rwr.gen[i,1]-miest.rwr.gen[i,3]
miest.rwr.race[i,5]<-miest.rwr.race[i,1]-miest.rwr.race[i,3]
miest.rwr.inc[i,5]<-miest.rwr.inc[i,1]-miest.rwr.inc[i,3]
# COMPUTE BOOTSTRAP SEs #
boot.ate.rwr<-boot.aje.rwr<-boot.cde.rwr<-boot.cme.rwr<-boot.dif1.rwr<-matrix(data=NA,nrow=nboot,ncol=1)
boot.ate.rwr.gen<-boot.aje.rwr.gen<-boot.cde.rwr.gen<-boot.cme.rwr.gen<-boot.dif1.rwr.gen<-matrix(data=NA,nrow=nboot,ncol=1)
boot.ate.rwr.race<-boot.aje.rwr.race<-boot.cde.rwr.race<-boot.cme.rwr.race<-boot.dif1.rwr.race<-matrix(data=NA,nrow=nboot,ncol=1)
boot.ate.rwr.inc<-boot.aje.rwr.inc<-boot.cde.rwr.inc<-boot.cme.rwr.inc<-boot.dif1.rwr.inc<-matrix(data=NA,nrow=nboot,ncol=1)
for (j in 1:nboot) {
boot.phdcn<-NULL
for (s in 1:16) {
phdcn.strata<-phdcn[which(phdcn$nstrata==s),]
idboot.1<-sample(unique(phdcn.strata$nlinknc_1),length(unique(phdcn.strata$nlinknc_1))-1,replace=T)
idboot.2<-table(idboot.1)
boot.phdcn.strata<-NULL
for (k in 1:max(idboot.2)) {
boot.data<-phdcn.strata[phdcn.strata$nlinknc_1 %in% names(idboot.2[idboot.2 %in% k]),]
for (l in 1:k) { boot.phdcn.strata<-rbind(boot.phdcn.strata,boot.data) }
}
boot.phdcn<-rbind(boot.phdcn,boot.phdcn.strata)
}
boot.resid_l1<-function(y) { residuals(lm(y~1,data=boot.phdcn)) }
boot.resid_l2<-function(y) { residuals(lm(y~npcage_b+npchsgrad_b+npcsomcol_b+npccolgrd_b+nownhome_b+nfemale_b+nblack_b+nhispan_b+nothrace_b+nfamsize_b+
nlninc_1+npcemply_1+npcwelf_1+npcmarr_1+npcengl_1+ncondadvg_1+nbl5ug_1,data=boot.phdcn)) }
boot.resid_l3<-function(y) { residuals(lm(y~npcage_b+npchsgrad_b+npcsomcol_b+npccolgrd_b+nownhome_b+nfemale_b+nblack_b+nhispan_b+nothrace_b+nfamsize_b+
nlninc_1+npcemply_1+npcwelf_1+npcmarr_1+npcengl_1+ncondadvg_1+nbl5ug_1+
nlninc_2+npcemply_2+npcwelf_2+npcmarr_2+npcengl_2+ncondadvg_2+nbl5ug_2,data=boot.phdcn)) }
boot.phdcn<-boot.phdcn %>% mutate_at(vars(npcage_b,npchsgrad_b,npcsomcol_b,npccolgrd_b,nownhome_b,nfemale_b,nblack_b,nhispan_b,nothrace_b,nfamsize_b), funs(r=boot.resid_l1))
boot.phdcn<-boot.phdcn %>% mutate_at(vars(nlninc_1,npcemply_1,npcwelf_1,npcmarr_1,npcengl_1), funs(r=boot.resid_l1))
boot.phdcn<-boot.phdcn %>% mutate_at(vars(nlninc_2,npcemply_2,npcwelf_2,npcmarr_2,npcengl_2), funs(r=boot.resid_l2))
boot.phdcn<-boot.phdcn %>% mutate_at(vars(nlninc_3,npcemply_3,npcwelf_3,npcmarr_3,npcengl_3), funs(r=boot.resid_l3))
boot.phdcn$nbl5ug_1_r<-residuals(lm(nbl5ug_1~npcage_b+npchsgrad_b+npcsomcol_b+npccolgrd_b+nownhome_b+nfemale_b+nblack_b+nhispan_b+nothrace_b+nfamsize_b+
nlninc_1+npcemply_1+npcwelf_1+npcmarr_1+npcengl_1+ncondadvg_1,data=boot.phdcn))
boot.phdcn$nbl5ug_2_r<-residuals(lm(nbl5ug_2~npcage_b+npchsgrad_b+npcsomcol_b+npccolgrd_b+nownhome_b+nfemale_b+nblack_b+nhispan_b+nothrace_b+nfamsize_b+
nlninc_1+npcemply_1+npcwelf_1+npcmarr_1+npcengl_1+ncondadvg_1+nbl5ug_1+
nlninc_2+npcemply_2+npcwelf_2+npcmarr_2+npcengl_2+ncondadvg_2,data=boot.phdcn))
boot.phdcn$nbl5ug_3_r<-residuals(lm(nbl5ug_3~npcage_b+npchsgrad_b+npcsomcol_b+npccolgrd_b+nownhome_b+nfemale_b+nblack_b+nhispan_b+nothrace_b+nfamsize_b+
nlninc_1+npcemply_1+npcwelf_1+npcmarr_1+npcengl_1+ncondadvg_1+nbl5ug_1+
nlninc_2+npcemply_2+npcwelf_2+npcmarr_2+npcengl_2+ncondadvg_2+nbl5ug_2+
nlninc_3+npcemply_3+npcwelf_3+npcmarr_3+npcengl_3+ncondadvg_3,data=boot.phdcn))
boot.phdcn$nsubage_3_r<-residuals(lm(nsubage_3~npcage_b+npchsgrad_b+npcsomcol_b+npccolgrd_b+nownhome_b+nfemale_b+nblack_b+nhispan_b+nothrace_b+nfamsize_b+
nlninc_1+npcemply_1+npcwelf_1+npcmarr_1+npcengl_1+ncondadvg_1+nbl5ug_1+
nlninc_2+npcemply_2+npcwelf_2+npcmarr_2+npcengl_2+ncondadvg_2+nbl5ug_2+
nlninc_3+npcemply_3+npcwelf_3+npcmarr_3+npcengl_3+ncondadvg_3+nbl5ug_3,data=boot.phdcn))
boot.phdcn$nlninc_s_r<-boot.phdcn$nlninc_1_r+boot.phdcn$nlninc_2_r+boot.phdcn$nlninc_3_r
boot.phdcn$npcemply_s_r<-boot.phdcn$npcemply_1_r+boot.phdcn$npcemply_2_r+boot.phdcn$npcemply_3_r
boot.phdcn$npcwelf_s_r<-boot.phdcn$npcwelf_1_r+boot.phdcn$npcwelf_2_r+boot.phdcn$npcwelf_3_r
boot.phdcn$npcmarr_s_r<-boot.phdcn$npcmarr_1_r+boot.phdcn$npcmarr_2_r+boot.phdcn$npcmarr_3_r
boot.phdcn$npcengl_s_r<-boot.phdcn$npcengl_1_r+boot.phdcn$npcengl_2_r+boot.phdcn$npcengl_3_r
boot.phdcn$nbl5ug_s_r<-boot.phdcn$nbl5ug_1_r+boot.phdcn$nbl5ug_2_r+boot.phdcn$nbl5ug_3_r
boot.m1<-lm(nppvt_3~npcage_b_r+npchsgrad_b_r+npcsomcol_b_r+npccolgrd_b_r+nownhome_b_r+nfemale_b_r+nblack_b_r+nhispan_b_r+nothrace_b_r+nfamsize_b_r+
nsubage_3_r+nbl5ug_s_r+nlninc_s_r+npcemply_s_r+npcwelf_s_r+npcmarr_s_r+npcengl_s_r+cumndadvg,data=boot.phdcn)
boot.m2<-lm(nppvt_3~npcage_b_r+npchsgrad_b_r+npcsomcol_b_r+npccolgrd_b_r+nownhome_b_r+nfemale_b_r+nblack_b_r+nhispan_b_r+nothrace_b_r+nfamsize_b_r+
nsubage_3_r+nlninc_s_r+npcemply_s_r+npcwelf_s_r+npcmarr_s_r+npcengl_s_r+cumndadvg+cumnbl5ug,data=boot.phdcn)
boot.m1.gen<-lm(nppvt_3~npcage_b_r+npchsgrad_b_r+npcsomcol_b_r+npccolgrd_b_r+nownhome_b_r+nfemale_b_r+nblack_b_r+nhispan_b_r+nothrace_b_r+nfamsize_b_r+
nsubage_3_r+nbl5ug_s_r+nlninc_s_r+npcemply_s_r+npcwelf_s_r+npcmarr_s_r+npcengl_s_r+cumndadvg+
(cumndadvg*nfemale_b_r),data=boot.phdcn)
boot.m2.gen<-lm(nppvt_3~npcage_b_r+npchsgrad_b_r+npcsomcol_b_r+npccolgrd_b_r+nownhome_b_r+nfemale_b_r+nblack_b_r+nhispan_b_r+nothrace_b_r+nfamsize_b_r+
nsubage_3_r+nlninc_s_r+npcemply_s_r+npcwelf_s_r+npcmarr_s_r+npcengl_s_r+cumndadvg+cumnbl5ug+
(cumndadvg*nfemale_b_r)+(cumnbl5ug*nfemale_b_r),data=boot.phdcn)
boot.m1.race<-lm(nppvt_3~npcage_b_r+npchsgrad_b_r+npcsomcol_b_r+npccolgrd_b_r+nownhome_b_r+nfemale_b_r+nblack_b_r+nhispan_b_r+nothrace_b_r+nfamsize_b_r+
nsubage_3_r+nbl5ug_s_r+nlninc_s_r+npcemply_s_r+npcwelf_s_r+npcmarr_s_r+npcengl_s_r+cumndadvg+
(cumndadvg*nblack_b_r)+(cumndadvg*nhispan_b_r),data=boot.phdcn)
boot.m2.race<-lm(nppvt_3~npcage_b_r+npchsgrad_b_r+npcsomcol_b_r+npccolgrd_b_r+nownhome_b_r+nfemale_b_r+nblack_b_r+nhispan_b_r+nothrace_b_r+nfamsize_b_r+
nsubage_3_r+nlninc_s_r+npcemply_s_r+npcwelf_s_r+npcmarr_s_r+npcengl_s_r+cumndadvg+cumnbl5ug+
(cumndadvg*nblack_b_r)+(cumndadvg*nhispan_b_r)+(cumnbl5ug*nblack_b_r)+(cumnbl5ug*nhispan_b_r),data=boot.phdcn)
boot.m1.inc<-lm(nppvt_3~npcage_b_r+npchsgrad_b_r+npcsomcol_b_r+npccolgrd_b_r+nownhome_b_r+nfemale_b_r+nblack_b_r+nhispan_b_r+nothrace_b_r+nfamsize_b_r+
nsubage_3_r+nbl5ug_s_r+nlninc_s_r+npcemply_s_r+npcwelf_s_r+npcmarr_s_r+npcengl_s_r+cumndadvg+
(cumndadvg*nlninc_s_r),data=boot.phdcn)
boot.m2.inc<-lm(nppvt_3~npcage_b_r+npchsgrad_b_r+npcsomcol_b_r+npccolgrd_b_r+nownhome_b_r+nfemale_b_r+nblack_b_r+nhispan_b_r+nothrace_b_r+nfamsize_b_r+
nsubage_3_r+nlninc_s_r+npcemply_s_r+npcwelf_s_r+npcmarr_s_r+npcengl_s_r+cumndadvg+cumnbl5ug+
(cumndadvg*nlninc_s_r)+(cumnbl5ug*nlninc_s_r),data=boot.phdcn)
boot.ate.rwr[j,1]<-boot.m1$coefficients["cumndadvg"]*(astar-a)
boot.ate.rwr.gen[j,1]<-boot.m1.gen$coefficients["cumndadvg"]*(astar-a)
boot.ate.rwr.race[j,1]<-boot.m1.race$coefficients["cumndadvg"]*(astar-a)
boot.ate.rwr.inc[j,1]<-boot.m1.inc$coefficients["cumndadvg"]*(astar-a)
boot.aje.rwr[j,1]<-boot.m2$coefficients["cumndadvg"]*(astar-a)+boot.m2$coefficients["cumnbl5ug"]*(mstar-m)
boot.aje.rwr.gen[j,1]<-boot.m2.gen$coefficients["cumndadvg"]*(astar-a)+boot.m2.gen$coefficients["cumnbl5ug"]*(mstar-m)
boot.aje.rwr.race[j,1]<-boot.m2.race$coefficients["cumndadvg"]*(astar-a)+boot.m2.race$coefficients["cumnbl5ug"]*(mstar-m)
boot.aje.rwr.inc[j,1]<-boot.m2.inc$coefficients["cumndadvg"]*(astar-a)+boot.m2.inc$coefficients["cumnbl5ug"]*(mstar-m)
boot.cde.rwr[j,1]<-boot.m2$coefficients["cumndadvg"]*(astar-a)
boot.cde.rwr.gen[j,1]<-boot.m2.gen$coefficients["cumndadvg"]*(astar-a)
boot.cde.rwr.race[j,1]<-boot.m2.race$coefficients["cumndadvg"]*(astar-a)
boot.cde.rwr.inc[j,1]<-boot.m2.inc$coefficients["cumndadvg"]*(astar-a)
boot.cme.rwr[j,1]<-boot.m2$coefficients["cumnbl5ug"]*(mstar-m)
boot.cme.rwr.gen[j,1]<-boot.m2.gen$coefficients["cumnbl5ug"]*(mstar-m)
boot.cme.rwr.race[j,1]<-boot.m2.race$coefficients["cumnbl5ug"]*(mstar-m)
boot.cme.rwr.inc[j,1]<-boot.m2.inc$coefficients["cumnbl5ug"]*(mstar-m)
boot.dif1.rwr[j,1]<-boot.ate.rwr[j,1]-boot.cde.rwr[j,1]
boot.dif1.rwr.gen[j,1]<-boot.ate.rwr.gen[j,1]-boot.cde.rwr.gen[j,1]
boot.dif1.rwr.race[j,1]<-boot.ate.rwr.race[j,1]-boot.cde.rwr.race[j,1]
boot.dif1.rwr.inc[j,1]<-boot.ate.rwr.inc[j,1]-boot.cde.rwr.inc[j,1]
}
mivar.rwr[i,1]<-var(boot.ate.rwr)
mivar.rwr[i,2]<-var(boot.aje.rwr)
mivar.rwr[i,3]<-var(boot.cde.rwr)
mivar.rwr[i,4]<-var(boot.cme.rwr)
mivar.rwr[i,5]<-var(boot.dif1.rwr)
mivar.rwr.gen[i,1]<-var(boot.ate.rwr.gen)
mivar.rwr.gen[i,2]<-var(boot.aje.rwr.gen)
mivar.rwr.gen[i,3]<-var(boot.cde.rwr.gen)
mivar.rwr.gen[i,4]<-var(boot.cme.rwr.gen)
mivar.rwr.gen[i,5]<-var(boot.dif1.rwr.gen)
mivar.rwr.race[i,1]<-var(boot.ate.rwr.race)
mivar.rwr.race[i,2]<-var(boot.aje.rwr.race)
mivar.rwr.race[i,3]<-var(boot.cde.rwr.race)
mivar.rwr.race[i,4]<-var(boot.cme.rwr.race)
mivar.rwr.race[i,5]<-var(boot.dif1.rwr.race)
mivar.rwr.inc[i,1]<-var(boot.ate.rwr.inc)
mivar.rwr.inc[i,2]<-var(boot.aje.rwr.inc)
mivar.rwr.inc[i,3]<-var(boot.cde.rwr.inc)
mivar.rwr.inc[i,4]<-var(boot.cme.rwr.inc)
mivar.rwr.inc[i,5]<-var(boot.dif1.rwr.inc)
}
##### COMPUTE RESIDUAL BALANCING ESTIMATES #####
### DEFINE RESIDUAL BALANCING FUNCTION ###
resbal<-function(M,C,Q,Z=rep(0,ncol(C)),max_iter=300,tol=1,print.level=0) {
converged <- FALSE
for (iter in 1:max_iter) {
if (print.level >= 1) cat("iteration",iter,"\n")
W<-c(Q * exp(C %*% Z))
sumC<-t(C) %*% W
gradient<-sumC-M
if (max(abs(gradient)) < tol) {
converged<-TRUE
break
}
if (print.level >= 2) { cat("Iteration",iter,"maximum deviation is =",format(max(abs(gradient)),digits=4),"\n") }
hessian=t(C) %*% (W*C)
Coefs<-Z
newton<-solve(hessian,gradient)
Z<-Z-newton
loss.new<-line.searcher(Base.weight=Q,Co.x=C,Tr.total=M,coefs=Z,Newton=newton,ss=1)
loss.old<-line.searcher(Base.weight=Q,Co.x=C,Tr.total=M,coefs=Coefs,Newton=newton,ss=0)
if (print.level>=3) { cat("new loss=",loss.new,"old loss=",loss.old,"\n") }
if (loss.old <= loss.new) {
ss.out<-optimize(line.searcher,lower=.00001,upper=1,maximum=FALSE,Base.weight=Q,Co.x=C,Tr.total=M,coefs=Coefs,Newton=newton)
if (print.level >= 3) { cat("LS Step Length is ",ss.out$minimum,"\n") }
if (print.level >= 3) { cat("Loss is",ss.out$objective,"\n") }
Z <- Coefs-ss.out$minimum*solve(hessian, gradient)
}
}
list(W=W,sumC=sumC,converged=converged,maxdiff=max(abs(gradient)))
}
miest.rbal<-mivar.rbal<-matrix(data=NA,nrow=nmi,ncol=5)
### COMPUTE ESTIMATES ###
for (i in 1:nmi) {
# LOAD DATA #
phdcn<-phdcnmi[which(phdcnmi$"_mj"==i),]
# RESIDUALIZE POST-TREATMENT CONFOUNDERS #
resid_l1<-function(y) { residuals(lm(y~1,data=phdcn)) }
resid_l2<-function(y) { residuals(lm(y~npcage_b+npchsgrad_b+npcsomcol_b+npccolgrd_b+nownhome_b+nfemale_b+nblack_b+nhispan_b+nothrace_b+nfamsize_b+
nlninc_1+npcemply_1+npcwelf_1+npcmarr_1+npcengl_1+ncondadvg_1+nbl5ug_1,data=phdcn)) }
resid_l3<-function(y) { residuals(lm(y~npcage_b+npchsgrad_b+npcsomcol_b+npccolgrd_b+nownhome_b+nfemale_b+nblack_b+nhispan_b+nothrace_b+nfamsize_b+
nlninc_1+npcemply_1+npcwelf_1+npcmarr_1+npcengl_1+ncondadvg_1+nbl5ug_1+
nlninc_2+npcemply_2+npcwelf_2+npcmarr_2+npcengl_2+ncondadvg_2+nbl5ug_2,data=phdcn)) }
phdcn<-phdcn %>% mutate_at(vars(npcage_b,npchsgrad_b,npcsomcol_b,npccolgrd_b,nownhome_b,nfemale_b,nblack_b,nhispan_b,nothrace_b,nfamsize_b), funs(r=resid_l1))
phdcn<-phdcn %>% mutate_at(vars(nlninc_1,npcemply_1,npcwelf_1,npcmarr_1,npcengl_1), funs(r=resid_l1))
phdcn<-phdcn %>% mutate_at(vars(nlninc_2,npcemply_2,npcwelf_2,npcmarr_2,npcengl_2), funs(r=resid_l2))
phdcn<-phdcn %>% mutate_at(vars(nlninc_3,npcemply_3,npcwelf_3,npcmarr_3,npcengl_3), funs(r=resid_l3))
phdcn$nbl5ug_1_r<-residuals(lm(nbl5ug_1~npcage_b+npchsgrad_b+npcsomcol_b+npccolgrd_b+nownhome_b+nfemale_b+nblack_b+nhispan_b+nothrace_b+nfamsize_b+
nlninc_1+npcemply_1+npcwelf_1+npcmarr_1+npcengl_1+ncondadvg_1,data=phdcn))
phdcn$nbl5ug_2_r<-residuals(lm(nbl5ug_2~npcage_b+npchsgrad_b+npcsomcol_b+npccolgrd_b+nownhome_b+nfemale_b+nblack_b+nhispan_b+nothrace_b+nfamsize_b+
nlninc_1+npcemply_1+npcwelf_1+npcmarr_1+npcengl_1+ncondadvg_1+nbl5ug_1+
nlninc_2+npcemply_2+npcwelf_2+npcmarr_2+npcengl_2+ncondadvg_2,data=phdcn))
phdcn$nbl5ug_3_r<-residuals(lm(nbl5ug_3~npcage_b+npchsgrad_b+npcsomcol_b+npccolgrd_b+nownhome_b+nfemale_b+nblack_b+nhispan_b+nothrace_b+nfamsize_b+
nlninc_1+npcemply_1+npcwelf_1+npcmarr_1+npcengl_1+ncondadvg_1+nbl5ug_1+
nlninc_2+npcemply_2+npcwelf_2+npcmarr_2+npcengl_2+ncondadvg_2+nbl5ug_2+
nlninc_3+npcemply_3+npcwelf_3+npcmarr_3+npcengl_3+ncondadvg_3,data=phdcn))
phdcn$nsubage_3_r<-residuals(lm(nsubage_3~npcage_b+npchsgrad_b+npcsomcol_b+npccolgrd_b+nownhome_b+nfemale_b+nblack_b+nhispan_b+nothrace_b+nfamsize_b+
nlninc_1+npcemply_1+npcwelf_1+npcmarr_1+npcengl_1+ncondadvg_1+nbl5ug_1+
nlninc_2+npcemply_2+npcwelf_2+npcmarr_2+npcengl_2+ncondadvg_2+nbl5ug_2+
nlninc_3+npcemply_3+npcwelf_3+npcmarr_3+npcengl_3+ncondadvg_3+nbl5ug_3,data=phdcn))
# DEFINE CONSTRAINT MATRICES #
Cm<-cbind(1,
phdcn$nbl5ug_1_r,
phdcn$nbl5ug_1_r*phdcn$ncondadvg_2,
phdcn$nbl5ug_1_r*phdcn$ncondadvg_3,
phdcn$nbl5ug_1_r*phdcn$npcage_b,
phdcn$nbl5ug_1_r*phdcn$npchsgrad_b,
phdcn$nbl5ug_1_r*phdcn$npcsomcol_b,
phdcn$nbl5ug_1_r*phdcn$npccolgrd_b,
phdcn$nbl5ug_1_r*phdcn$nownhome_b,
phdcn$nbl5ug_1_r*phdcn$nfemale_b,
phdcn$nbl5ug_1_r*phdcn$nblack_b,
phdcn$nbl5ug_1_r*phdcn$nhispan_b,
phdcn$nbl5ug_1_r*phdcn$nothrace_b,
phdcn$nbl5ug_1_r*phdcn$nfamsize_b,
phdcn$nbl5ug_1_r*phdcn$nlninc_1,
phdcn$nbl5ug_1_r*phdcn$npcemply_1,
phdcn$nbl5ug_1_r*phdcn$npcwelf_1,
phdcn$nbl5ug_1_r*phdcn$npcmarr_1,
phdcn$nbl5ug_1_r*phdcn$npcengl_1,
phdcn$nbl5ug_1_r*phdcn$ncondadvg_1,
phdcn$nlninc_2_r,
phdcn$nlninc_2_r*phdcn$ncondadvg_2,
phdcn$nlninc_2_r*phdcn$ncondadvg_3,
phdcn$nlninc_2_r*phdcn$npcage_b,
phdcn$nlninc_2_r*phdcn$npchsgrad_b,
phdcn$nlninc_2_r*phdcn$npcsomcol_b,
phdcn$nlninc_2_r*phdcn$npccolgrd_b,
phdcn$nlninc_2_r*phdcn$nownhome_b,
phdcn$nlninc_2_r*phdcn$nfemale_b,
phdcn$nlninc_2_r*phdcn$nblack_b,
phdcn$nlninc_2_r*phdcn$nhispan_b,
phdcn$nlninc_2_r*phdcn$nothrace_b,
phdcn$nlninc_2_r*phdcn$nfamsize_b,
phdcn$nlninc_2_r*phdcn$nlninc_1,
phdcn$nlninc_2_r*phdcn$npcemply_1,
phdcn$nlninc_2_r*phdcn$npcwelf_1,
phdcn$nlninc_2_r*phdcn$npcmarr_1,
phdcn$nlninc_2_r*phdcn$npcengl_1,
phdcn$nlninc_2_r*phdcn$ncondadvg_1,
phdcn$nlninc_2_r*phdcn$nbl5ug_1,
phdcn$npcemply_2_r,
phdcn$npcemply_2_r*phdcn$ncondadvg_2,
phdcn$npcemply_2_r*phdcn$ncondadvg_3,
phdcn$npcemply_2_r*phdcn$npcage_b,
phdcn$npcemply_2_r*phdcn$npchsgrad_b,
phdcn$npcemply_2_r*phdcn$npcsomcol_b,
phdcn$npcemply_2_r*phdcn$npccolgrd_b,
phdcn$npcemply_2_r*phdcn$nownhome_b,
phdcn$npcemply_2_r*phdcn$nfemale_b,
phdcn$npcemply_2_r*phdcn$nblack_b,
phdcn$npcemply_2_r*phdcn$nhispan_b,
phdcn$npcemply_2_r*phdcn$nothrace_b,
phdcn$npcemply_2_r*phdcn$nfamsize_b,
phdcn$npcemply_2_r*phdcn$nlninc_1,
phdcn$npcemply_2_r*phdcn$npcemply_1,
phdcn$npcemply_2_r*phdcn$npcwelf_1,
phdcn$npcemply_2_r*phdcn$npcmarr_1,
phdcn$npcemply_2_r*phdcn$npcengl_1,
phdcn$npcemply_2_r*phdcn$ncondadvg_1,
phdcn$npcemply_2_r*phdcn$nbl5ug_1,
phdcn$npcwelf_2_r,
phdcn$npcwelf_2_r*phdcn$ncondadvg_2,
phdcn$npcwelf_2_r*phdcn$ncondadvg_3,
phdcn$npcwelf_2_r*phdcn$npcage_b,
phdcn$npcwelf_2_r*phdcn$npchsgrad_b,
phdcn$npcwelf_2_r*phdcn$npcsomcol_b,
phdcn$npcwelf_2_r*phdcn$npccolgrd_b,
phdcn$npcwelf_2_r*phdcn$nownhome_b,
phdcn$npcwelf_2_r*phdcn$nfemale_b,
phdcn$npcwelf_2_r*phdcn$nblack_b,
phdcn$npcwelf_2_r*phdcn$nhispan_b,
phdcn$npcwelf_2_r*phdcn$nothrace_b,
phdcn$npcwelf_2_r*phdcn$nfamsize_b,
phdcn$npcwelf_2_r*phdcn$nlninc_1,
phdcn$npcwelf_2_r*phdcn$npcemply_1,
phdcn$npcwelf_2_r*phdcn$npcwelf_1,
phdcn$npcwelf_2_r*phdcn$npcmarr_1,
phdcn$npcwelf_2_r*phdcn$npcengl_1,
phdcn$npcwelf_2_r*phdcn$ncondadvg_1,
phdcn$npcwelf_2_r*phdcn$nbl5ug_1,
phdcn$npcmarr_2_r,
phdcn$npcmarr_2_r*phdcn$ncondadvg_2,
phdcn$npcmarr_2_r*phdcn$ncondadvg_3,
phdcn$npcmarr_2_r*phdcn$npcage_b,
phdcn$npcmarr_2_r*phdcn$npchsgrad_b,
phdcn$npcmarr_2_r*phdcn$npcsomcol_b,
phdcn$npcmarr_2_r*phdcn$npccolgrd_b,
phdcn$npcmarr_2_r*phdcn$nownhome_b,
phdcn$npcmarr_2_r*phdcn$nfemale_b,
phdcn$npcmarr_2_r*phdcn$nblack_b,
phdcn$npcmarr_2_r*phdcn$nhispan_b,
phdcn$npcmarr_2_r*phdcn$nothrace_b,
phdcn$npcmarr_2_r*phdcn$nfamsize_b,
phdcn$npcmarr_2_r*phdcn$nlninc_1,
phdcn$npcmarr_2_r*phdcn$npcemply_1,
phdcn$npcmarr_2_r*phdcn$npcwelf_1,
phdcn$npcmarr_2_r*phdcn$npcmarr_1,
phdcn$npcmarr_2_r*phdcn$npcengl_1,
phdcn$npcmarr_2_r*phdcn$ncondadvg_1,
phdcn$npcmarr_2_r*phdcn$nbl5ug_1,
phdcn$npcengl_2_r,
phdcn$npcengl_2_r*phdcn$ncondadvg_2,
phdcn$npcengl_2_r*phdcn$ncondadvg_3,
phdcn$npcengl_2_r*phdcn$npcage_b,
phdcn$npcengl_2_r*phdcn$npchsgrad_b,
phdcn$npcengl_2_r*phdcn$npcsomcol_b,
phdcn$npcengl_2_r*phdcn$npccolgrd_b,
phdcn$npcengl_2_r*phdcn$nownhome_b,
phdcn$npcengl_2_r*phdcn$nfemale_b,
phdcn$npcengl_2_r*phdcn$nblack_b,
phdcn$npcengl_2_r*phdcn$nhispan_b,
phdcn$npcengl_2_r*phdcn$nothrace_b,
phdcn$npcengl_2_r*phdcn$nfamsize_b,
phdcn$npcengl_2_r*phdcn$nlninc_1,
phdcn$npcengl_2_r*phdcn$npcemply_1,
phdcn$npcengl_2_r*phdcn$npcwelf_1,
phdcn$npcengl_2_r*phdcn$npcmarr_1,
phdcn$npcengl_2_r*phdcn$npcengl_1,
phdcn$npcengl_2_r*phdcn$ncondadvg_1,
phdcn$npcengl_2_r*phdcn$nbl5ug_1,
phdcn$nbl5ug_2_r,
phdcn$nbl5ug_2_r*phdcn$ncondadvg_3,
phdcn$nbl5ug_2_r*phdcn$npcage_b,
phdcn$nbl5ug_2_r*phdcn$npchsgrad_b,
phdcn$nbl5ug_2_r*phdcn$npcsomcol_b,
phdcn$nbl5ug_2_r*phdcn$npccolgrd_b,
phdcn$nbl5ug_2_r*phdcn$nownhome_b,
phdcn$nbl5ug_2_r*phdcn$nfemale_b,
phdcn$nbl5ug_2_r*phdcn$nblack_b,
phdcn$nbl5ug_2_r*phdcn$nhispan_b,
phdcn$nbl5ug_2_r*phdcn$nothrace_b,
phdcn$nbl5ug_2_r*phdcn$nfamsize_b,
phdcn$nbl5ug_2_r*phdcn$nlninc_1,
phdcn$nbl5ug_2_r*phdcn$npcemply_1,
phdcn$nbl5ug_2_r*phdcn$npcwelf_1,
phdcn$nbl5ug_2_r*phdcn$npcmarr_1,
phdcn$nbl5ug_2_r*phdcn$npcengl_1,
phdcn$nbl5ug_2_r*phdcn$ncondadvg_1,
phdcn$nbl5ug_2_r*phdcn$nbl5ug_1,
phdcn$nbl5ug_2_r*phdcn$nlninc_2,
phdcn$nbl5ug_2_r*phdcn$npcemply_2,
phdcn$nbl5ug_2_r*phdcn$npcwelf_2,
phdcn$nbl5ug_2_r*phdcn$npcmarr_2,
phdcn$nbl5ug_2_r*phdcn$npcengl_2,
phdcn$nbl5ug_2_r*phdcn$ncondadvg_2,
phdcn$nlninc_3_r,
phdcn$nlninc_3_r*phdcn$ncondadvg_3,
phdcn$nlninc_3_r*phdcn$npcage_b,
phdcn$nlninc_3_r*phdcn$npchsgrad_b,
phdcn$nlninc_3_r*phdcn$npcsomcol_b,
phdcn$nlninc_3_r*phdcn$npccolgrd_b,
phdcn$nlninc_3_r*phdcn$nownhome_b,
phdcn$nlninc_3_r*phdcn$nfemale_b,
phdcn$nlninc_3_r*phdcn$nblack_b,
phdcn$nlninc_3_r*phdcn$nhispan_b,
phdcn$nlninc_3_r*phdcn$nothrace_b,
phdcn$nlninc_3_r*phdcn$nfamsize_b,
phdcn$nlninc_3_r*phdcn$nlninc_1,
phdcn$nlninc_3_r*phdcn$npcemply_1,
phdcn$nlninc_3_r*phdcn$npcwelf_1,
phdcn$nlninc_3_r*phdcn$npcmarr_1,
phdcn$nlninc_3_r*phdcn$npcengl_1,
phdcn$nlninc_3_r*phdcn$ncondadvg_1,
phdcn$nlninc_3_r*phdcn$nbl5ug_1,
phdcn$nlninc_3_r*phdcn$nlninc_2,
phdcn$nlninc_3_r*phdcn$npcemply_2,
phdcn$nlninc_3_r*phdcn$npcwelf_2,
phdcn$nlninc_3_r*phdcn$npcmarr_2,
phdcn$nlninc_3_r*phdcn$npcengl_2,
phdcn$nlninc_3_r*phdcn$ncondadvg_2,
phdcn$nlninc_3_r*phdcn$nbl5ug_2,
phdcn$npcemply_3_r,
phdcn$npcemply_3_r*phdcn$ncondadvg_3,
phdcn$npcemply_3_r*phdcn$npcage_b,
phdcn$npcemply_3_r*phdcn$npchsgrad_b,
phdcn$npcemply_3_r*phdcn$npcsomcol_b,
phdcn$npcemply_3_r*phdcn$npccolgrd_b,
phdcn$npcemply_3_r*phdcn$nownhome_b,
phdcn$npcemply_3_r*phdcn$nfemale_b,
phdcn$npcemply_3_r*phdcn$nblack_b,
phdcn$npcemply_3_r*phdcn$nhispan_b,
phdcn$npcemply_3_r*phdcn$nothrace_b,
phdcn$npcemply_3_r*phdcn$nfamsize_b,
phdcn$npcemply_3_r*phdcn$nlninc_1,
phdcn$npcemply_3_r*phdcn$npcemply_1,
phdcn$npcemply_3_r*phdcn$npcwelf_1,
phdcn$npcemply_3_r*phdcn$npcmarr_1,
phdcn$npcemply_3_r*phdcn$npcengl_1,
phdcn$npcemply_3_r*phdcn$ncondadvg_1,
phdcn$npcemply_3_r*phdcn$nbl5ug_1,
phdcn$npcemply_3_r*phdcn$nlninc_2,
phdcn$npcemply_3_r*phdcn$npcemply_2,
phdcn$npcemply_3_r*phdcn$npcwelf_2,
phdcn$npcemply_3_r*phdcn$npcmarr_2,
phdcn$npcemply_3_r*phdcn$npcengl_2,
phdcn$npcemply_3_r*phdcn$ncondadvg_2,
phdcn$npcemply_3_r*phdcn$nbl5ug_2,
phdcn$npcwelf_3_r,
phdcn$npcwelf_3_r*phdcn$ncondadvg_3,
phdcn$npcwelf_3_r*phdcn$npcage_b,
phdcn$npcwelf_3_r*phdcn$npchsgrad_b,
phdcn$npcwelf_3_r*phdcn$npcsomcol_b,
phdcn$npcwelf_3_r*phdcn$npccolgrd_b,
phdcn$npcwelf_3_r*phdcn$nownhome_b,
phdcn$npcwelf_3_r*phdcn$nfemale_b,
phdcn$npcwelf_3_r*phdcn$nblack_b,
phdcn$npcwelf_3_r*phdcn$nhispan_b,
phdcn$npcwelf_3_r*phdcn$nothrace_b,
phdcn$npcwelf_3_r*phdcn$nfamsize_b,
phdcn$npcwelf_3_r*phdcn$nlninc_1,
phdcn$npcwelf_3_r*phdcn$npcemply_1,
phdcn$npcwelf_3_r*phdcn$npcwelf_1,
phdcn$npcwelf_3_r*phdcn$npcmarr_1,
phdcn$npcwelf_3_r*phdcn$npcengl_1,
phdcn$npcwelf_3_r*phdcn$ncondadvg_1,
phdcn$npcwelf_3_r*phdcn$nbl5ug_1,
phdcn$npcwelf_3_r*phdcn$nlninc_2,
phdcn$npcwelf_3_r*phdcn$npcemply_2,
phdcn$npcwelf_3_r*phdcn$npcwelf_2,
phdcn$npcwelf_3_r*phdcn$npcmarr_2,
phdcn$npcwelf_3_r*phdcn$npcengl_2,
phdcn$npcwelf_3_r*phdcn$ncondadvg_2,
phdcn$npcwelf_3_r*phdcn$nbl5ug_2,
phdcn$npcmarr_3_r,
phdcn$npcmarr_3_r*phdcn$ncondadvg_3,
phdcn$npcmarr_3_r*phdcn$npcage_b,
phdcn$npcmarr_3_r*phdcn$npchsgrad_b,
phdcn$npcmarr_3_r*phdcn$npcsomcol_b,
phdcn$npcmarr_3_r*phdcn$npccolgrd_b,
phdcn$npcmarr_3_r*phdcn$nownhome_b,
phdcn$npcmarr_3_r*phdcn$nfemale_b,
phdcn$npcmarr_3_r*phdcn$nblack_b,
phdcn$npcmarr_3_r*phdcn$nhispan_b,
phdcn$npcmarr_3_r*phdcn$nothrace_b,
phdcn$npcmarr_3_r*phdcn$nfamsize_b,
phdcn$npcmarr_3_r*phdcn$nlninc_1,
phdcn$npcmarr_3_r*phdcn$npcemply_1,
phdcn$npcmarr_3_r*phdcn$npcwelf_1,
phdcn$npcmarr_3_r*phdcn$npcmarr_1,
phdcn$npcmarr_3_r*phdcn$npcengl_1,
phdcn$npcmarr_3_r*phdcn$ncondadvg_1,
phdcn$npcmarr_3_r*phdcn$nbl5ug_1,
phdcn$npcmarr_3_r*phdcn$nlninc_2,
phdcn$npcmarr_3_r*phdcn$npcemply_2,
phdcn$npcmarr_3_r*phdcn$npcwelf_2,
phdcn$npcmarr_3_r*phdcn$npcmarr_2,
phdcn$npcmarr_3_r*phdcn$npcengl_2,
phdcn$npcmarr_3_r*phdcn$ncondadvg_2,
phdcn$npcmarr_3_r*phdcn$nbl5ug_2,
phdcn$npcengl_3_r,
phdcn$npcengl_3_r*phdcn$ncondadvg_3,
phdcn$npcengl_3_r*phdcn$npcage_b,
phdcn$npcengl_3_r*phdcn$npchsgrad_b,
phdcn$npcengl_3_r*phdcn$npcsomcol_b,
phdcn$npcengl_3_r*phdcn$npccolgrd_b,
phdcn$npcengl_3_r*phdcn$nownhome_b,
phdcn$npcengl_3_r*phdcn$nfemale_b,
phdcn$npcengl_3_r*phdcn$nblack_b,
phdcn$npcengl_3_r*phdcn$nhispan_b,
phdcn$npcengl_3_r*phdcn$nothrace_b,
phdcn$npcengl_3_r*phdcn$nfamsize_b,
phdcn$npcengl_3_r*phdcn$nlninc_1,
phdcn$npcengl_3_r*phdcn$npcemply_1,
phdcn$npcengl_3_r*phdcn$npcwelf_1,
phdcn$npcengl_3_r*phdcn$npcmarr_1,
phdcn$npcengl_3_r*phdcn$npcengl_1,
phdcn$npcengl_3_r*phdcn$ncondadvg_1,
phdcn$npcengl_3_r*phdcn$nbl5ug_1,
phdcn$npcengl_3_r*phdcn$nlninc_2,
phdcn$npcengl_3_r*phdcn$npcemply_2,
phdcn$npcengl_3_r*phdcn$npcwelf_2,
phdcn$npcengl_3_r*phdcn$npcmarr_2,
phdcn$npcengl_3_r*phdcn$npcengl_2,
phdcn$npcengl_3_r*phdcn$ncondadvg_2,
phdcn$npcengl_3_r*phdcn$nbl5ug_2,
phdcn$nbl5ug_3_r,
phdcn$nbl5ug_3_r*phdcn$ncondadvg_3,
phdcn$nbl5ug_3_r*phdcn$npcage_b,
phdcn$nbl5ug_3_r*phdcn$npchsgrad_b,
phdcn$nbl5ug_3_r*phdcn$npcsomcol_b,
phdcn$nbl5ug_3_r*phdcn$npccolgrd_b,
phdcn$nbl5ug_3_r*phdcn$nownhome_b,
phdcn$nbl5ug_3_r*phdcn$nfemale_b,
phdcn$nbl5ug_3_r*phdcn$nblack_b,
phdcn$nbl5ug_3_r*phdcn$nhispan_b,
phdcn$nbl5ug_3_r*phdcn$nothrace_b,
phdcn$nbl5ug_3_r*phdcn$nfamsize_b,
phdcn$nbl5ug_3_r*phdcn$nlninc_1,
phdcn$nbl5ug_3_r*phdcn$npcemply_1,
phdcn$nbl5ug_3_r*phdcn$npcwelf_1,
phdcn$nbl5ug_3_r*phdcn$npcmarr_1,
phdcn$nbl5ug_3_r*phdcn$npcengl_1,
phdcn$nbl5ug_3_r*phdcn$ncondadvg_1,
phdcn$nbl5ug_3_r*phdcn$nbl5ug_1,
phdcn$nbl5ug_3_r*phdcn$nlninc_2,
phdcn$nbl5ug_3_r*phdcn$npcemply_2,
phdcn$nbl5ug_3_r*phdcn$npcwelf_2,
phdcn$nbl5ug_3_r*phdcn$npcmarr_2,
phdcn$nbl5ug_3_r*phdcn$npcengl_2,
phdcn$nbl5ug_3_r*phdcn$ncondadvg_2,
phdcn$nbl5ug_3_r*phdcn$nbl5ug_2)
Cj<-cbind(1,
phdcn$nlninc_2_r,
phdcn$nlninc_2_r*phdcn$ncondadvg_2,
phdcn$nlninc_2_r*phdcn$nbl5ug_2,
phdcn$nlninc_2_r*phdcn$ncondadvg_3,
phdcn$nlninc_2_r*phdcn$nbl5ug_3,
phdcn$nlninc_2_r*phdcn$npcage_b,
phdcn$nlninc_2_r*phdcn$npchsgrad_b,
phdcn$nlninc_2_r*phdcn$npcsomcol_b,
phdcn$nlninc_2_r*phdcn$npccolgrd_b,
phdcn$nlninc_2_r*phdcn$nownhome_b,
phdcn$nlninc_2_r*phdcn$nfemale_b,
phdcn$nlninc_2_r*phdcn$nblack_b,
phdcn$nlninc_2_r*phdcn$nhispan_b,
phdcn$nlninc_2_r*phdcn$nothrace_b,
phdcn$nlninc_2_r*phdcn$nfamsize_b,
phdcn$nlninc_2_r*phdcn$nlninc_1,
phdcn$nlninc_2_r*phdcn$npcemply_1,
phdcn$nlninc_2_r*phdcn$npcwelf_1,
phdcn$nlninc_2_r*phdcn$npcmarr_1,
phdcn$nlninc_2_r*phdcn$npcengl_1,
phdcn$nlninc_2_r*phdcn$ncondadvg_1,
phdcn$nlninc_2_r*phdcn$nbl5ug_1,
phdcn$npcemply_2_r,
phdcn$npcemply_2_r*phdcn$ncondadvg_2,
phdcn$npcemply_2_r*phdcn$nbl5ug_2,
phdcn$npcemply_2_r*phdcn$ncondadvg_3,
phdcn$npcemply_2_r*phdcn$nbl5ug_3,
phdcn$npcemply_2_r*phdcn$npcage_b,
phdcn$npcemply_2_r*phdcn$npchsgrad_b,
phdcn$npcemply_2_r*phdcn$npcsomcol_b,
phdcn$npcemply_2_r*phdcn$npccolgrd_b,
phdcn$npcemply_2_r*phdcn$nownhome_b,
phdcn$npcemply_2_r*phdcn$nfemale_b,
phdcn$npcemply_2_r*phdcn$nblack_b,
phdcn$npcemply_2_r*phdcn$nhispan_b,
phdcn$npcemply_2_r*phdcn$nothrace_b,
phdcn$npcemply_2_r*phdcn$nfamsize_b,
phdcn$npcemply_2_r*phdcn$nlninc_1,
phdcn$npcemply_2_r*phdcn$npcemply_1,
phdcn$npcemply_2_r*phdcn$npcwelf_1,
phdcn$npcemply_2_r*phdcn$npcmarr_1,
phdcn$npcemply_2_r*phdcn$npcengl_1,
phdcn$npcemply_2_r*phdcn$ncondadvg_1,
phdcn$npcemply_2_r*phdcn$nbl5ug_1,
phdcn$npcwelf_2_r,
phdcn$npcwelf_2_r*phdcn$ncondadvg_2,
phdcn$npcwelf_2_r*phdcn$nbl5ug_2,
phdcn$npcwelf_2_r*phdcn$ncondadvg_3,
phdcn$npcwelf_2_r*phdcn$nbl5ug_3,
phdcn$npcwelf_2_r*phdcn$npcage_b,
phdcn$npcwelf_2_r*phdcn$npchsgrad_b,
phdcn$npcwelf_2_r*phdcn$npcsomcol_b,
phdcn$npcwelf_2_r*phdcn$npccolgrd_b,
phdcn$npcwelf_2_r*phdcn$nownhome_b,
phdcn$npcwelf_2_r*phdcn$nfemale_b,
phdcn$npcwelf_2_r*phdcn$nblack_b,
phdcn$npcwelf_2_r*phdcn$nhispan_b,
phdcn$npcwelf_2_r*phdcn$nothrace_b,
phdcn$npcwelf_2_r*phdcn$nfamsize_b,
phdcn$npcwelf_2_r*phdcn$nlninc_1,
phdcn$npcwelf_2_r*phdcn$npcemply_1,
phdcn$npcwelf_2_r*phdcn$npcwelf_1,
phdcn$npcwelf_2_r*phdcn$npcmarr_1,
phdcn$npcwelf_2_r*phdcn$npcengl_1,
phdcn$npcwelf_2_r*phdcn$ncondadvg_1,
phdcn$npcwelf_2_r*phdcn$nbl5ug_1,
phdcn$npcmarr_2_r,
phdcn$npcmarr_2_r*phdcn$ncondadvg_2,
phdcn$npcmarr_2_r*phdcn$nbl5ug_2,
phdcn$npcmarr_2_r*phdcn$ncondadvg_3,
phdcn$npcmarr_2_r*phdcn$nbl5ug_3,
phdcn$npcmarr_2_r*phdcn$npcage_b,
phdcn$npcmarr_2_r*phdcn$npchsgrad_b,
phdcn$npcmarr_2_r*phdcn$npcsomcol_b,
phdcn$npcmarr_2_r*phdcn$npccolgrd_b,
phdcn$npcmarr_2_r*phdcn$nownhome_b,
phdcn$npcmarr_2_r*phdcn$nfemale_b,
phdcn$npcmarr_2_r*phdcn$nblack_b,
phdcn$npcmarr_2_r*phdcn$nhispan_b,
phdcn$npcmarr_2_r*phdcn$nothrace_b,
phdcn$npcmarr_2_r*phdcn$nfamsize_b,
phdcn$npcmarr_2_r*phdcn$nlninc_1,
phdcn$npcmarr_2_r*phdcn$npcemply_1,
phdcn$npcmarr_2_r*phdcn$npcwelf_1,
phdcn$npcmarr_2_r*phdcn$npcmarr_1,
phdcn$npcmarr_2_r*phdcn$npcengl_1,
phdcn$npcmarr_2_r*phdcn$ncondadvg_1,
phdcn$npcmarr_2_r*phdcn$nbl5ug_1,
phdcn$npcengl_2_r,
phdcn$npcengl_2_r*phdcn$ncondadvg_2,
phdcn$npcengl_2_r*phdcn$nbl5ug_2,
phdcn$npcengl_2_r*phdcn$ncondadvg_3,
phdcn$npcengl_2_r*phdcn$nbl5ug_3,
phdcn$npcengl_2_r*phdcn$npcage_b,
phdcn$npcengl_2_r*phdcn$npchsgrad_b,
phdcn$npcengl_2_r*phdcn$npcsomcol_b,
phdcn$npcengl_2_r*phdcn$npccolgrd_b,
phdcn$npcengl_2_r*phdcn$nownhome_b,
phdcn$npcengl_2_r*phdcn$nfemale_b,
phdcn$npcengl_2_r*phdcn$nblack_b,
phdcn$npcengl_2_r*phdcn$nhispan_b,
phdcn$npcengl_2_r*phdcn$nothrace_b,
phdcn$npcengl_2_r*phdcn$nfamsize_b,
phdcn$npcengl_2_r*phdcn$nlninc_1,
phdcn$npcengl_2_r*phdcn$npcemply_1,
phdcn$npcengl_2_r*phdcn$npcwelf_1,
phdcn$npcengl_2_r*phdcn$npcmarr_1,
phdcn$npcengl_2_r*phdcn$npcengl_1,
phdcn$npcengl_2_r*phdcn$ncondadvg_1,
phdcn$npcengl_2_r*phdcn$nbl5ug_1,
phdcn$nlninc_3_r,
phdcn$nlninc_3_r*phdcn$ncondadvg_3,
phdcn$nlninc_3_r*phdcn$nbl5ug_3,
phdcn$nlninc_3_r*phdcn$npcage_b,
phdcn$nlninc_3_r*phdcn$npchsgrad_b,
phdcn$nlninc_3_r*phdcn$npcsomcol_b,
phdcn$nlninc_3_r*phdcn$npccolgrd_b,
phdcn$nlninc_3_r*phdcn$nownhome_b,
phdcn$nlninc_3_r*phdcn$nfemale_b,
phdcn$nlninc_3_r*phdcn$nblack_b,
phdcn$nlninc_3_r*phdcn$nhispan_b,
phdcn$nlninc_3_r*phdcn$nothrace_b,
phdcn$nlninc_3_r*phdcn$nfamsize_b,
phdcn$nlninc_3_r*phdcn$nlninc_1,
phdcn$nlninc_3_r*phdcn$npcemply_1,
phdcn$nlninc_3_r*phdcn$npcwelf_1,
phdcn$nlninc_3_r*phdcn$npcmarr_1,
phdcn$nlninc_3_r*phdcn$npcengl_1,
phdcn$nlninc_3_r*phdcn$ncondadvg_1,
phdcn$nlninc_3_r*phdcn$nbl5ug_1,
phdcn$nlninc_3_r*phdcn$nlninc_2,
phdcn$nlninc_3_r*phdcn$npcemply_2,
phdcn$nlninc_3_r*phdcn$npcwelf_2,
phdcn$nlninc_3_r*phdcn$npcmarr_2,
phdcn$nlninc_3_r*phdcn$npcengl_2,
phdcn$nlninc_3_r*phdcn$ncondadvg_2,
phdcn$nlninc_3_r*phdcn$nbl5ug_2,
phdcn$npcemply_3_r,
phdcn$npcemply_3_r*phdcn$ncondadvg_3,
phdcn$npcemply_3_r*phdcn$nbl5ug_3,
phdcn$npcemply_3_r*phdcn$npcage_b,
phdcn$npcemply_3_r*phdcn$npchsgrad_b,
phdcn$npcemply_3_r*phdcn$npcsomcol_b,
phdcn$npcemply_3_r*phdcn$npccolgrd_b,
phdcn$npcemply_3_r*phdcn$nownhome_b,
phdcn$npcemply_3_r*phdcn$nfemale_b,
phdcn$npcemply_3_r*phdcn$nblack_b,
phdcn$npcemply_3_r*phdcn$nhispan_b,
phdcn$npcemply_3_r*phdcn$nothrace_b,
phdcn$npcemply_3_r*phdcn$nfamsize_b,
phdcn$npcemply_3_r*phdcn$nlninc_1,
phdcn$npcemply_3_r*phdcn$npcemply_1,
phdcn$npcemply_3_r*phdcn$npcwelf_1,
phdcn$npcemply_3_r*phdcn$npcmarr_1,
phdcn$npcemply_3_r*phdcn$npcengl_1,
phdcn$npcemply_3_r*phdcn$ncondadvg_1,
phdcn$npcemply_3_r*phdcn$nbl5ug_1,
phdcn$npcemply_3_r*phdcn$nlninc_2,
phdcn$npcemply_3_r*phdcn$npcemply_2,
phdcn$npcemply_3_r*phdcn$npcwelf_2,
phdcn$npcemply_3_r*phdcn$npcmarr_2,
phdcn$npcemply_3_r*phdcn$npcengl_2,
phdcn$npcemply_3_r*phdcn$ncondadvg_2,
phdcn$npcemply_3_r*phdcn$nbl5ug_2,
phdcn$npcwelf_3_r,
phdcn$npcwelf_3_r*phdcn$ncondadvg_3,
phdcn$npcwelf_3_r*phdcn$nbl5ug_3,
phdcn$npcwelf_3_r*phdcn$npcage_b,
phdcn$npcwelf_3_r*phdcn$npchsgrad_b,
phdcn$npcwelf_3_r*phdcn$npcsomcol_b,
phdcn$npcwelf_3_r*phdcn$npccolgrd_b,
phdcn$npcwelf_3_r*phdcn$nownhome_b,
phdcn$npcwelf_3_r*phdcn$nfemale_b,
phdcn$npcwelf_3_r*phdcn$nblack_b,
phdcn$npcwelf_3_r*phdcn$nhispan_b,
phdcn$npcwelf_3_r*phdcn$nothrace_b,
phdcn$npcwelf_3_r*phdcn$nfamsize_b,
phdcn$npcwelf_3_r*phdcn$nlninc_1,
phdcn$npcwelf_3_r*phdcn$npcemply_1,
phdcn$npcwelf_3_r*phdcn$npcwelf_1,
phdcn$npcwelf_3_r*phdcn$npcmarr_1,
phdcn$npcwelf_3_r*phdcn$npcengl_1,
phdcn$npcwelf_3_r*phdcn$ncondadvg_1,
phdcn$npcwelf_3_r*phdcn$nbl5ug_1,
phdcn$npcwelf_3_r*phdcn$nlninc_2,
phdcn$npcwelf_3_r*phdcn$npcemply_2,
phdcn$npcwelf_3_r*phdcn$npcwelf_2,
phdcn$npcwelf_3_r*phdcn$npcmarr_2,
phdcn$npcwelf_3_r*phdcn$npcengl_2,
phdcn$npcwelf_3_r*phdcn$ncondadvg_2,
phdcn$npcwelf_3_r*phdcn$nbl5ug_2,
phdcn$npcmarr_3_r,
phdcn$npcmarr_3_r*phdcn$ncondadvg_3,
phdcn$npcmarr_3_r*phdcn$nbl5ug_3,
phdcn$npcmarr_3_r*phdcn$npcage_b,
phdcn$npcmarr_3_r*phdcn$npchsgrad_b,
phdcn$npcmarr_3_r*phdcn$npcsomcol_b,
phdcn$npcmarr_3_r*phdcn$npccolgrd_b,
phdcn$npcmarr_3_r*phdcn$nownhome_b,
phdcn$npcmarr_3_r*phdcn$nfemale_b,
phdcn$npcmarr_3_r*phdcn$nblack_b,
phdcn$npcmarr_3_r*phdcn$nhispan_b,
phdcn$npcmarr_3_r*phdcn$nothrace_b,
phdcn$npcmarr_3_r*phdcn$nfamsize_b,
phdcn$npcmarr_3_r*phdcn$nlninc_1,
phdcn$npcmarr_3_r*phdcn$npcemply_1,
phdcn$npcmarr_3_r*phdcn$npcwelf_1,
phdcn$npcmarr_3_r*phdcn$npcmarr_1,
phdcn$npcmarr_3_r*phdcn$npcengl_1,
phdcn$npcmarr_3_r*phdcn$ncondadvg_1,
phdcn$npcmarr_3_r*phdcn$nbl5ug_1,
phdcn$npcmarr_3_r*phdcn$nlninc_2,
phdcn$npcmarr_3_r*phdcn$npcemply_2,
phdcn$npcmarr_3_r*phdcn$npcwelf_2,
phdcn$npcmarr_3_r*phdcn$npcmarr_2,
phdcn$npcmarr_3_r*phdcn$npcengl_2,
phdcn$npcmarr_3_r*phdcn$ncondadvg_2,
phdcn$npcmarr_3_r*phdcn$nbl5ug_2,
phdcn$npcengl_3_r,
phdcn$npcengl_3_r*phdcn$ncondadvg_3,
phdcn$npcengl_3_r*phdcn$nbl5ug_3,
phdcn$npcengl_3_r*phdcn$npcage_b,
phdcn$npcengl_3_r*phdcn$npchsgrad_b,
phdcn$npcengl_3_r*phdcn$npcsomcol_b,
phdcn$npcengl_3_r*phdcn$npccolgrd_b,
phdcn$npcengl_3_r*phdcn$nownhome_b,
phdcn$npcengl_3_r*phdcn$nfemale_b,
phdcn$npcengl_3_r*phdcn$nblack_b,
phdcn$npcengl_3_r*phdcn$nhispan_b,
phdcn$npcengl_3_r*phdcn$nothrace_b,
phdcn$npcengl_3_r*phdcn$nfamsize_b,
phdcn$npcengl_3_r*phdcn$nlninc_1,
phdcn$npcengl_3_r*phdcn$npcemply_1,
phdcn$npcengl_3_r*phdcn$npcwelf_1,
phdcn$npcengl_3_r*phdcn$npcmarr_1,
phdcn$npcengl_3_r*phdcn$npcengl_1,
phdcn$npcengl_3_r*phdcn$ncondadvg_1,
phdcn$npcengl_3_r*phdcn$nbl5ug_1,
phdcn$npcengl_3_r*phdcn$nlninc_2,
phdcn$npcengl_3_r*phdcn$npcemply_2,
phdcn$npcengl_3_r*phdcn$npcwelf_2,
phdcn$npcengl_3_r*phdcn$npcmarr_2,
phdcn$npcengl_3_r*phdcn$npcengl_2,
phdcn$npcengl_3_r*phdcn$ncondadvg_2,
phdcn$npcengl_3_r*phdcn$nbl5ug_2)
# DEFINE BASE WEIGHTS #
Q<-rep(1,length(phdcn$nsubid))
# DEFINE COLUMN MEANS OF CONSTRAINT MATRIX #
Mm<-c(sum(Q),rep(0,ncol(Cm)-1))
Mj<-c(sum(Q),rep(0,ncol(Cj)-1))
# COMPUTE BALANCING WEIGHTS #
rbalwtm<-resbal(Mm,Cm,Q,tol=0.01)$W
rbalwtj<-resbal(Mj,Cj,Q,tol=0.01)$W
# COMPUTE NEW VARIABLES #
phdcn$cumndadvg<-(phdcn$ncondadvg_1+phdcn$ncondadvg_2+phdcn$ncondadvg_3)/3
phdcn$cumnbl5ug<-(phdcn$nbl5ug_1+phdcn$nbl5ug_2+phdcn$nbl5ug_3)/3
phdcn$nppvt_3<-(phdcn$nppvt_3-mean(phdcn$nppvt_3))/sd(phdcn$nppvt_3)
# FIT MODELS #
m1<-lm(nppvt_3~npcage_b_r+npchsgrad_b_r+npcsomcol_b_r+npccolgrd_b_r+nownhome_b_r+nfemale_b_r+nblack_b_r+nhispan_b_r+nothrace_b_r+nfamsize_b_r+
nlninc_1_r+npcemply_1_r+npcwelf_1_r+npcmarr_1_r+npcengl_1_r+nsubage_3_r+cumndadvg,data=phdcn,weights=rbalwtm)
m2<-lm(nppvt_3~npcage_b_r+npchsgrad_b_r+npcsomcol_b_r+npccolgrd_b_r+nownhome_b_r+nfemale_b_r+nblack_b_r+nhispan_b_r+nothrace_b_r+nfamsize_b_r+
nlninc_1_r+npcemply_1_r+npcwelf_1_r+npcmarr_1_r+npcengl_1_r+nsubage_3_r+cumndadvg+cumnbl5ug,data=phdcn,weights=rbalwtj)
# TOTAL EFFECT OF NHOOD POVERTY #
miest.rbal[i,1]<-m1$coefficients["cumndadvg"]*(astar-a)
# JOINT EFFECT OF NHOOD POVERTY AND ENVIRONMENTAL LEAD CONTAMINATION #
miest.rbal[i,2]<-m2$coefficients["cumndadvg"]*(astar-a)+m2$coefficients["cumnbl5ug"]*(mstar-m)
# CONTROLLED DIRECT EFFECT OF NHOOD POVERTY #
miest.rbal[i,3]<-m2$coefficients["cumndadvg"]*(astar-a)
# CONTROLLED MEDIATOR EFFECT OF ENVIRONMENTAL LEAD CONTAMINATION #
miest.rbal[i,4]<-m2$coefficients["cumnbl5ug"]*(mstar-m)
# DIFFERENCE BETWEEN ATE AND CDE #
miest.rbal[i,5]<-miest.rbal[i,1]-miest.rbal[i,3]
# COMPUTE BOOTSTRAP SEs #
boot.ate.rbal<-boot.aje.rbal<-boot.cde.rbal<-boot.cme.rbal<-boot.dif1.rbal<-matrix(data=NA,nrow=nboot,ncol=1)
for (j in 1:nboot) {
boot.phdcn<-NULL
for (s in 1:16) {
phdcn.strata<-phdcn[which(phdcn$nstrata==s),]
idboot.1<-sample(unique(phdcn.strata$nlinknc_1),length(unique(phdcn.strata$nlinknc_1))-1,replace=T)
idboot.2<-table(idboot.1)
boot.phdcn.strata<-NULL
for (k in 1:max(idboot.2)) {
boot.data<-phdcn.strata[phdcn.strata$nlinknc_1 %in% names(idboot.2[idboot.2 %in% k]),]
for (l in 1:k) { boot.phdcn.strata<-rbind(boot.phdcn.strata,boot.data) }
}
boot.phdcn<-rbind(boot.phdcn,boot.phdcn.strata)
}
boot.resid_l1<-function(y) { residuals(lm(y~1,data=boot.phdcn)) }
boot.resid_l2<-function(y) { residuals(lm(y~npcage_b+npchsgrad_b+npcsomcol_b+npccolgrd_b+nownhome_b+nfemale_b+nblack_b+nhispan_b+nothrace_b+nfamsize_b+
nlninc_1+npcemply_1+npcwelf_1+npcmarr_1+npcengl_1+ncondadvg_1+nbl5ug_1,data=boot.phdcn)) }
boot.resid_l3<-function(y) { residuals(lm(y~npcage_b+npchsgrad_b+npcsomcol_b+npccolgrd_b+nownhome_b+nfemale_b+nblack_b+nhispan_b+nothrace_b+nfamsize_b+
nlninc_1+npcemply_1+npcwelf_1+npcmarr_1+npcengl_1+ncondadvg_1+nbl5ug_1+
nlninc_2+npcemply_2+npcwelf_2+npcmarr_2+npcengl_2+ncondadvg_2+nbl5ug_2,data=boot.phdcn)) }
boot.phdcn<-boot.phdcn %>% mutate_at(vars(npcage_b,npchsgrad_b,npcsomcol_b,npccolgrd_b,nownhome_b,nfemale_b,nblack_b,nhispan_b,nothrace_b,nfamsize_b), funs(r=boot.resid_l1))
boot.phdcn<-boot.phdcn %>% mutate_at(vars(nlninc_1,npcemply_1,npcwelf_1,npcmarr_1,npcengl_1), funs(r=boot.resid_l1))
boot.phdcn<-boot.phdcn %>% mutate_at(vars(nlninc_2,npcemply_2,npcwelf_2,npcmarr_2,npcengl_2), funs(r=boot.resid_l2))
boot.phdcn<-boot.phdcn %>% mutate_at(vars(nlninc_3,npcemply_3,npcwelf_3,npcmarr_3,npcengl_3), funs(r=boot.resid_l3))
boot.phdcn$nbl5ug_1_r<-residuals(lm(nbl5ug_1~npcage_b+npchsgrad_b+npcsomcol_b+npccolgrd_b+nownhome_b+nfemale_b+nblack_b+nhispan_b+nothrace_b+nfamsize_b+
nlninc_1+npcemply_1+npcwelf_1+npcmarr_1+npcengl_1+ncondadvg_1,data=boot.phdcn))
boot.phdcn$nbl5ug_2_r<-residuals(lm(nbl5ug_2~npcage_b+npchsgrad_b+npcsomcol_b+npccolgrd_b+nownhome_b+nfemale_b+nblack_b+nhispan_b+nothrace_b+nfamsize_b+
nlninc_1+npcemply_1+npcwelf_1+npcmarr_1+npcengl_1+ncondadvg_1+nbl5ug_1+
nlninc_2+npcemply_2+npcwelf_2+npcmarr_2+npcengl_2+ncondadvg_2,data=boot.phdcn))
boot.phdcn$nbl5ug_3_r<-residuals(lm(nbl5ug_3~npcage_b+npchsgrad_b+npcsomcol_b+npccolgrd_b+nownhome_b+nfemale_b+nblack_b+nhispan_b+nothrace_b+nfamsize_b+
nlninc_1+npcemply_1+npcwelf_1+npcmarr_1+npcengl_1+ncondadvg_1+nbl5ug_1+
nlninc_2+npcemply_2+npcwelf_2+npcmarr_2+npcengl_2+ncondadvg_2+nbl5ug_2+
nlninc_3+npcemply_3+npcwelf_3+npcmarr_3+npcengl_3+ncondadvg_3,data=boot.phdcn))
boot.phdcn$nsubage_3_r<-residuals(lm(nsubage_3~npcage_b+npchsgrad_b+npcsomcol_b+npccolgrd_b+nownhome_b+nfemale_b+nblack_b+nhispan_b+nothrace_b+nfamsize_b+
nlninc_1+npcemply_1+npcwelf_1+npcmarr_1+npcengl_1+ncondadvg_1+nbl5ug_1+
nlninc_2+npcemply_2+npcwelf_2+npcmarr_2+npcengl_2+ncondadvg_2+nbl5ug_2+
nlninc_3+npcemply_3+npcwelf_3+npcmarr_3+npcengl_3+ncondadvg_3+nbl5ug_3,data=boot.phdcn))
boot.Cm<-cbind(1,
boot.phdcn$nbl5ug_1_r,
boot.phdcn$nbl5ug_1_r*boot.phdcn$ncondadvg_2,
boot.phdcn$nbl5ug_1_r*boot.phdcn$ncondadvg_3,
boot.phdcn$nbl5ug_1_r*boot.phdcn$npcage_b,
boot.phdcn$nbl5ug_1_r*boot.phdcn$npchsgrad_b,
boot.phdcn$nbl5ug_1_r*boot.phdcn$npcsomcol_b,
boot.phdcn$nbl5ug_1_r*boot.phdcn$npccolgrd_b,
boot.phdcn$nbl5ug_1_r*boot.phdcn$nownhome_b,
boot.phdcn$nbl5ug_1_r*boot.phdcn$nfemale_b,
boot.phdcn$nbl5ug_1_r*boot.phdcn$nblack_b,
boot.phdcn$nbl5ug_1_r*boot.phdcn$nhispan_b,
boot.phdcn$nbl5ug_1_r*boot.phdcn$nothrace_b,
boot.phdcn$nbl5ug_1_r*boot.phdcn$nfamsize_b,
boot.phdcn$nbl5ug_1_r*boot.phdcn$nlninc_1,
boot.phdcn$nbl5ug_1_r*boot.phdcn$npcemply_1,
boot.phdcn$nbl5ug_1_r*boot.phdcn$npcwelf_1,
boot.phdcn$nbl5ug_1_r*boot.phdcn$npcmarr_1,
boot.phdcn$nbl5ug_1_r*boot.phdcn$npcengl_1,
boot.phdcn$nbl5ug_1_r*boot.phdcn$ncondadvg_1,
boot.phdcn$nlninc_2_r,