R 的新手。我有一组来自 Stata 的代码，我想在 R 中重现

Question

I have programmed the following code in Stata that I wanted to reproduce in R.

heckman wage i.age i.profstat i.edlevel, select(i.profstat i.edlevel ur i.ethnicity mstatus) twostep first mills(imr)

predict simwage, xb
replace wage = simwage if missing(wage) & !missing(profstat)

Any insights on how to do it? I'm new to R.

Data - sample:

data = structure(list(ethnicity = c(6, 1, 2, 1, 7, 2, 5, 1, 2, 2, 4, 5, 4), 
                      age = factor(c(1, 1, 2, 2, 3, 1, 4, 1, 1, 3, 1, 3, 4)), 
                      ur = c(1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 0, 1, 0), 
                      edlevel = c(2, 2, 3, 1, 2, 2, 2, 1, 2, 2, 2, 1, 1), 
                      mstatus = c(1, 3, 3, 3, 2, 1, 2, 3, 3, 1, 1, 6, 6), 
                      profstat = factor(c(4, 4, 2, NA, 1, NA, NA, 2, 2, NA, 2, 1, NA)), 
                      income = c(10, NA, 9, NA, 10, NA, NA, 4, 4, NA, 8, 8, 4), 
                      wage = c(1794, NA, 1483, NA, 1529, NA, NA, 415, 550, NA, 1169, 1096, 543)), 
                 row.names = c(NA, -13L), class = c("tbl_df", "tbl", "data.frame"))

Answer 1

Something like that. We need asses the model and perform a imputation process. in selection equation you have to use proper I() or a new variable

your other question How do I correct this Error in Heckman selectionmodel when implementing in R?

So it is possible that you do not have NA in wage although 0 or sth else then use eq like: I(wage != 0)

Edit after discussion:

require(sampleSelection)
#Hecman model
  
heckman <- selection(selection = I(!is.na(wage)) ~ ur + mstatus, outcome = wage ~ profstat, 
                                data = data, method = "2step")

#prediction
simwage <- predict(heckman, data)

data$wage_p <- simwage 
# imputation - replace NA wage with a new assesment
data$wage_org <- data$wage
data$wage[is.na(data$wage) & !is.na(data$profstat)] <- simwage[is.na(data$wage) & !is.na(data$profstat)]

head(data)

# A tibble: 6 x 10
  ethnicity age      ur edlevel mstatus profstat income  wage wage_p wage_org
      <dbl> <fct> <dbl>   <dbl>   <dbl> <fct>     <dbl> <dbl>  <dbl>    <dbl>
1         6 1         1       2       1 4            10 1794    767.     1794
2         1 1         1       2       3 4            NA  767.   767.       NA
3         2 2         1       3       3 2             9 1483    305.     1483
4         1 2         1       1       3 NA           NA   NA     NA        NA
5         7 3         1       2       2 1            10 1529    792.     1529
6         2 1         1       2       1 NA           NA   NA     NA        NA