Translating STATA syntax into R syntax [closed] - r

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I'm having some trouble translating some STATA codes to R codes:
Stata codes:
gen joint_gpw = sbud_jpw * q44 if sbud_jpw < 888 & q44 < 888
gen sbud_gpw_all = sbud_gpw if sbud_gpw < 888
replace sbud_gpw_all = q31 if sbud_gpw_all ==. & q31 < 888
replace sbud_gpw_all = joint_gpw if sbud_gpw_all ==. & joint_gpw !=.
replace sbud_gpw_all = 888 if q16_1 == 0 & sbud_gpw_all ==.
replace sbud_gpw_all = 888 if (sbud_gpw == 888 & q31 == 888 & sbud_jpw == 888 & q44 == 888) & sbud_gpw_all ==.
replace sbud_gpw_all = 999 if (sbud_gpw == 999 | q31 == 999 | sbud_jpw == 999 | q44 == 999 | (q44 !=. & sbud_jpw == 888)) & sbud_gpw_all ==.
Here is the R code I tried:
dat%>%
dplyr::mutate(joint_gpw = ifelse((sbud_jpw<888 & q44<888),sbud_jpw * q44,NA))%>%
dplyr::mutate(sbud_gpw_all = ifelse(sbud_gpw < 888,sbud_gpw,NA))%>%
dplyr::mutate(sbud_gpw_all = ifelse((sbud_gpw_all= NA & q31<888),q31,NA))%>%
dplyr::mutate(sbud_gpw_all = ifelse((sbud_gpw_all = NA & joint_gpw != NA),joint_gpw,NA))%>%
dplyr::mutate(sbud_gpw_all) = ifelse((q16_1 = 0 & sbud_gpw_all = NA),888,NA)%>%
dplyr::mutate(sbud_gpw_all) = ifelse((sbud_gpw = 888 & q31 = 888 & sbud_jpw = 888 & q44 = 888) & sbud_gpw_all = NA,888,NA)%>%
dplyr::mutate(sbud_gpw_all) = ifelse(((sbud_gpw = 999 | q31 = 999 | sbud_jpw = 999 | q44 = 999 | (q44 != NA & sbud_jpw == 888)) & sbud_gpw_all = NA)),999,NA)
Errors that showed up before:
Error: unexpected '=' in:
" dplyr::mutate(sbud_gpw_all) = ifelse((q16_1 = 0 & sbud_gpw_all = NA),888,NA)%>%
dplyr::mutate(sbud_gpw_all) = ifelse((sbud_gpw = 888 & q31 = 888 & sbud_jpw = 888 & q44 = 888) & sbud_gpw_all ="
I would like to know that if these two set of codes are equivalent? I greatly appreciate all the help there is! Thanks!!!

Answer 1

The error originates from the closing parenthesis ) after sbud_gpw_all in the last three lines.
Also, despite not the error thrown, you're overwriting sbud_gpw_all with every mutate. I don't know Stata and you didn't provide a minimal reproducible example but I have a feeling your code could work like this:
dat %>%
mutate(
joint_gpw = if_else(sbud_jpw < 888 & q44 < 888, sbud_jpw * q44, NA_real_),
sbud_gpw_all = case_when(
sbud_gpw < 888 ~ sbud_gpw,
q31 < 888 ~ q31,
!is.na(joint_gpw) ~ joint_gpw,
q16_1 == 0 ~ 888,
sbud_gpw == 888 & q31 == 888 & sbud_jpw == 888 & q44 == 888 ~ 888,
sbud_gpw == 999 | q31 == 999 | sbud_jpw == 999 | q44 == 999 | (!is.na(q44) & sbud_jpw == 888) ~ 999
)
)
This will first create the column joint_gpw using dplyr::if_else() if sbud_jpw < 888 & q44 < 888. Afterwards, there is a set of conditions (before the ~) that are checked sequentially. The first that matches the row, provides the value (behind the ~ operator).
Note that, as Sotos pointed out in a comment, NAs in R are checked with is.na(x), not with ==/!=, as those will always return NA. I omitted the NA check for most lines because those are implied in the sequential nature of case_when() -- as soon as one condition matches, the later ones are not evaluated anymore. The NA_real_ is a numeric NA value. Using if_else() and case_when(), you have to be explicit about the data type.