# how does health vary with education
ed_table<-
meps_2012%>%
filter(rthlth42>0 & !is.na(ednew))%>%
srvyr::survey_count(rthlth42,ednew)%>%
select(-n_se)%>%
group_by(ednew)%>%
mutate(prop=prop.table(n))%>%
pivot_wider(names_from=ednew,values_from=c(n,prop))%>% # make the names "pretty"
inner_join(srh_labels,by=c("rthlth42"="level"))%>%
select(label,starts_with("prop"))%>%
rename_with(~str_replace(.,"prop_[0-9] - ",""))
# use pcs42 and compute the mean
ed_table<-
ed_table%>%
bind_rows(
meps_2012%>%
filter(pcs42>0 & !is.na(ednew))%>%
group_by(ednew)%>%
srvyr::summarize(pcs42=srvyr::survey_mean(pcs42))%>%
select(-pcs42_se)%>%
pivot_wider(names_from=ednew,values_from=pcs42)%>%
rename_with(~str_replace(.,"[0-9] - ",""))%>%
mutate(label="Mean PCS")
)
ed_table
ed_table%>%
write.csv(file="./output/2.5.7.table1.csv")
age_table<-
meps_2012%>%
filter(rthlth42>0 & !is.na(age_bands))%>%
srvyr::survey_count(rthlth42,age_bands)%>%
select(-ends_with("se"))%>%
group_by(age_bands)%>%
mutate(prop=prop.table(n))%>%
pivot_wider(names_from=age_bands,values_from=c(n,prop))%>% # make the names "pretty"
inner_join(srh_labels,by=c("rthlth42"="level"))%>%
select(label,starts_with("prop"))%>%
rename_with(~str_replace(.,"prop_",""))
# use pcs42 and compute the mean
age_table<-
age_table%>%
bind_rows(
meps_2012%>%
filter(pcs42>0 & !is.na(age_bands))%>%
group_by(age_bands)%>%
srvyr::summarize(pcs42=srvyr::survey_mean(pcs42))%>%
select(-pcs42_se)%>%
pivot_wider(names_from=age_bands,values_from=pcs42)%>%
rename_with(~str_replace(.,"[0-9] - ",""))%>%
mutate(label="Mean PCS")
)
age_table
age_table%>%
write.csv(file="./output/2.5.7.table2.csv")
# how does health vary with education among 25-64 yo
ed_table2<-
meps_2012%>%
filter(rthlth42>0 & !is.na(ednew) & age31x %in% 25:64)%>%
srvyr::survey_count(rthlth42,ednew)%>%
select(-n_se)%>%
group_by(ednew)%>%
mutate(prop=prop.table(n))%>%
pivot_wider(names_from=ednew,values_from=c(n,prop))%>% # make the names "pretty"
inner_join(srh_labels,by=c("rthlth42"="level"))%>%
select(label,starts_with("prop"))%>%
rename_with(~str_replace(.,"prop_[0-9] - ",""))
# use pcs42 and compute the mean
ed_table2<-
ed_table2%>%
bind_rows(
meps_2012%>%
filter(pcs42>0 & !is.na(ednew) & age31x %in% 25:64)%>%
group_by(ednew)%>%
srvyr::summarize(pcs42=srvyr::survey_mean(pcs42))%>%
select(-pcs42_se)%>%
pivot_wider(names_from=ednew,values_from=pcs42)%>%
rename_with(~str_replace(.,"[0-9] - ",""))%>%
mutate(label="Mean PCS")
)
ed_table2
ed_table2%>%
write.csv(file="./output/2.5.7.table3.csv")
Perhaps you can explain what the code does, and we could point you to equivalent SAS code.
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