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Fix iplot parsing for IV sunab terms #633

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Fix iplot parsing for IV sunab terms #633

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21 changes: 18 additions & 3 deletions R/coefplot.R
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Original file line number Diff line number Diff line change
Expand Up @@ -2089,7 +2089,24 @@ coefplot_prms = function(all_models, vcov = NULL, se, ci_low, ci_high, x, x.shif
# avoids bug with IVs => problem if user names the variables that way
is_IV = FALSE
if(isTRUE(object$iv) && identical(object$iv_stage, 2)){
all_vars = gsub("^fit_", "", all_vars)
iv_fit_names = object[["iv_endo_names_fit"]]
if(is.character(iv_fit_names) && length(iv_fit_names) > 0){
# Restrict renaming to fitted endogenous terms only.
# This avoids altering user variables that simply start with "fit_".
is_fit = all_vars %in% iv_fit_names
if(any(is_fit)){
all_vars_fit = all_vars[is_fit]
# fit_x:var -> var (single ':'), but keep names like fit_user::2 unchanged here.
all_vars_fit = sub("^fit_[^:]+:(?!:)", "", all_vars_fit, perl = TRUE)
# For fitted terms still starting with fit_ (e.g. fit_x2::2), remove the prefix.
all_vars_fit = sub("^fit_", "", all_vars_fit)
all_vars[is_fit] = all_vars_fit
}
} else {
# Legacy fallback for old objects without iv_endo_names_fit.
all_vars = sub("^fit_[^:]+:(?!:)", "", all_vars, perl = TRUE)
all_vars = sub("^fit_", "", all_vars)
}
names(estimate) = all_vars
}

Expand Down Expand Up @@ -2878,8 +2895,6 @@ getFixest_coefplot = function(){








34 changes: 29 additions & 5 deletions tests/fixest_tests.R
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Expand Up @@ -2000,6 +2000,35 @@ res_sunab = feols(y ~ x1 + sunab(year_treated, year, bin.rel = "bin::2"), base_s
iplot(res_sunab)
test(length(coef(res_sunab)), 12)

# IV + sunab + interacted fitted regressor
set.seed(20260213)
n_id = 200L
never_cohort = 100L
dt_sunab_iv = expand.grid(id = 1:n_id, rel_time = -2:2)
dt_sunab_iv$high_growth = as.integer(dt_sunab_iv$id <= n_id / 2L)
dt_sunab_iv$cohort = ifelse(dt_sunab_iv$high_growth == 1L, 0L, never_cohort)
dt_sunab_iv$x = rnorm(nrow(dt_sunab_iv))
dt_sunab_iv$id_fe = rnorm(n_id)[dt_sunab_iv$id]
dt_sunab_iv$y = 0.08 * dt_sunab_iv$x * (dt_sunab_iv$rel_time >= 0L) * dt_sunab_iv$high_growth + dt_sunab_iv$id_fe + rnorm(nrow(dt_sunab_iv), sd = 0.25)

res_sunab_iv = feols(y ~ 1 | x:sunab(cohort, rel_time, ref.p = -1, ref.c = never_cohort, no_agg = TRUE) ~ sunab(cohort, rel_time, ref.p = -1, ref.c = never_cohort, no_agg = TRUE), dt_sunab_iv)
iv_sunab_iplot_ok = tryCatch({
iplot(res_sunab_iv)
TRUE
}, error = function(e) FALSE)
test(iv_sunab_iplot_ok, TRUE)

# IV with an exogenous i() variable whose name starts with "fit_"
set.seed(1)
base$fit_user = sample(1:3, nrow(base), TRUE)
res_iv_fit_user = feols(y ~ i(fit_user) | x2 ~ x3, base)
iv_fit_user_iplot_ok = tryCatch({
iplot(res_iv_fit_user)
TRUE
}, error = function(e) FALSE)
test(iv_fit_user_iplot_ok, TRUE)
base$fit_user = NULL


####
#### bin ####
Expand Down Expand Up @@ -3182,8 +3211,3 @@ test(nrow(fixest_data(est_mult, "esti")), 45)