Converting R Code to SAS

[terrifk]

# 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")

[PaigeMiller]

Perhaps you can explain what the code does, and we could point you to equivalent SAS code.