Patch to bypass misaem error (#71)

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: WeightIt
 Type: Package
 Title: Weighting for Covariate Balance in Observational Studies
-Version: 1.3.0
+Version: 1.3.0.9000
 Authors@R: c(
     person("Noah", "Greifer", role=c("aut", "cre"), 
            email = "noah.greifer@gmail.com",

NEWS.md

@@ -1,6 +1,10 @@
 WeightIt News and Updates
 ======
 
+# `WeightIt` (development version)
+
+* Changed defaults with `missing = "saem"` for binary and multi-category treatments to bypass bug in `misaem` code. (#71)
+
 # `WeightIt` 1.3.0
 
 * Added `anova()` methods for `glm_weightit`, `multinom_weightit`, `ordinal_weightit`, and `coxph_weightit` objects to perform Wald tests for comparing nested models. The models do not have to be symbolically nested.

R/weightit2glm.R

@@ -234,11 +234,11 @@ weightit2glm <- function(covs, treat, s.weights, subset, estimand, focal,
     rlang::check_installed("misaem")
     if (is_null(A[["saem.method"]])) A[["saem.method"]] <- "map"
     if (is_null(A[["control"]])) A[["control"]] <- list()
-    if (is_null(A[["control"]][["var_cal"]])) A[["control"]][["var_cal"]] <- FALSE
+    if (is_null(A[["control"]][["var_cal"]])) A[["control"]][["var_cal"]] <- TRUE #need TRUE to bypass error in miss.glm.fit()
     if (is_null(A[["control"]][["ll_obs_cal"]])) A[["control"]][["ll_obs_cal"]] <- FALSE
 
     data <- data.frame(treat, covs)
-
+# browser()
     withCallingHandlers({
       verbosely({
         fit <- misaem::miss.glm(formula(data), data = data, control = as.list(A[["control"]]))
@@ -614,7 +614,7 @@ weightit2glm.multi <- function(covs, treat, s.weights, subset, estimand, focal,
     rlang::check_installed("misaem")
     if (is_null(A[["saem.method"]])) A[["saem.method"]] <- "map"
     if (is_null(A[["control"]])) A[["control"]] <- list()
-    if (is_null(A[["control"]][["var_cal"]])) A[["control"]][["var_cal"]] <- FALSE
+    if (is_null(A[["control"]][["var_cal"]])) A[["control"]][["var_cal"]] <- TRUE #need TRUE to bypass error in miss.glm.fit()
     if (is_null(A[["control"]][["ll_obs_cal"]])) A[["control"]][["ll_obs_cal"]] <- FALSE
 
     ps <- make_df(levels(treat), nrow = length(treat))