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DeclareDesign · Mar 28, 2018 · 12f9a29 · 12f9a29
2 parents 29f3e0c + 7366241
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -9,7 +9,7 @@ Authors@R: c(person("Graeme", "Blair", email = "graeme.blair@ucla.edu", role = c
              person("Macartan", "Humphreys", email = "macartan@gmail.com", role = c("aut")),
              person("Luke", "Sonnet", email = "luke.sonnet@gmail.com", role = c("aut")),
              person("Neal", "Fultz", email = "nfultz@gmail.com", role = c("ctb")))
-Description: Fast procedures for small set of commonly-used, design-appropriate estimators with robust standard errors and confidence intervals. Includes estimators for linear regression, regression improving precision of experimental estimates by interacting treatment with centered pre-treatment covariates introduced by Lin (2013) <doi:10.1214/12-AOAS583>, difference-in-means, and Horvitz-Thompson estimation.
+Description: Fast procedures for small set of commonly-used, design-appropriate estimators with robust standard errors and confidence intervals. Includes estimators for linear regression, instrumental variables regresion, difference-in-means, Horvitz-Thompson estimation, and regression improving precision of experimental estimates by interacting treatment with centered pre-treatment covariates introduced by Lin (2013) <doi:10.1214/12-AOAS583>.
 URL: http://estimatr.declaredesign.org, https://github.com/DeclareDesign/estimatr
 BugReports: https://github.com/DeclareDesign/estimatr/issues
 License: MIT + file LICENSE

diff --git a/R/helper_lm_robust_fit.R b/R/helper_lm_robust_fit.R
@@ -320,13 +320,29 @@ lm_robust_fit <- function(y,
     }
     if (iv_second_stage && se_type != "none") {
       indices <- seq.int(has_int + 1, rank, by = 1)
-      fstat <- setNames(
-        crossprod(
-          fit$beta_hat[indices],
-          solve(vcov_fit$Vcov_hat[indices, indices], fit$beta_hat[indices])
-        ) / (rank - has_int),
+      setNames(
+        fstat <-
+          tryCatch({
+              crossprod(
+                fit$beta_hat[indices],
+                solve(vcov_fit$Vcov_hat[indices, indices], fit$beta_hat[indices])
+             ) / (rank - has_int)
+          }, error = function(e) {
+            if (grepl("system is computationally singular", e)) {
+              warning(
+                "Unable to compute f-statistic due to rank deficient variance-",
+                "covariance matrix"
+              )
+            } else {
+              warning(
+                "Unable to compute f-statistic"
+              )
+            }
+            NA
+          }),
         fstat_names
       )
+
     } else {
       fstat <- setNames(
         return_list[["r.squared"]] * return_list[["df.residual"]] /
@@ -348,8 +364,6 @@ lm_robust_fit <- function(y,
           rep(paste0(return_list[["outcome"]], ":"), each = rank),
           rep(return_list$term, times = ny)
         )
-        # print(return_list[["vcov"]])
-        # print(coef_names)
         dimnames(return_list[["vcov"]]) <- list(
           coef_names,
           coef_names

diff --git a/tests/testthat/test-iv-robust.R b/tests/testthat/test-iv-robust.R
@@ -209,6 +209,20 @@ test_that("iv_robust matches AER + ivpack", {
     na.omit(as.matrix(tidy(ivdef2clrw)[, c("estimate", "std.error", "p.value")])),
     na.omit(as.matrix(ivdef2clsew)[, c(1, 2, 4)])
   )
+
+  # F-stat fails properly with blocks of size 1
+  set.seed(42)
+  N <- 20
+  dat <- data.frame(y = rnorm(N), x = rnorm(N), z = rnorm(N), bl = sample(letters, size = N, replace = T))
+  expect_warning(
+    ivr <- iv_robust(y ~ bl + x | bl + z, data = dat, se_type = "stata"),
+    "Unable to compute f\\-statistic"
+  )
+  expect_equivalent(
+    ivr$fstatistic[1],
+    NA_integer_
+  )
+
 })