Merge pull request #187 from DeclareDesign/ls/gp

Ls/gp

.travis.yml

@@ -44,6 +44,7 @@ addons:
 r_github_packages:
 - DeclareDesign/DDtools
 - ropensci/git2r
+- DeclareDesign/fabricatr@v0.4.0
 
 r_packages:
 - broom

DESCRIPTION

@@ -1,7 +1,8 @@
 Package: estimatr
 Type: Package
 Title: Fast Estimators for Design-Based Inference
-Version: 0.5.0
+Version: 0.6.0
+Date: 2018-03-21
 Authors@R: c(person("Graeme", "Blair", email = "graeme.blair@ucla.edu", role = c("aut", "cre")),
              person("Jasper", "Cooper", email = "jjc2247@columbia.edu", role = c("aut")),
              person("Alexander", "Coppock", email = "alex.coppock@yale.edu", role = c("aut")),
@@ -33,4 +34,3 @@ Suggests:
 Enhances:
     broom,
     texreg
-Additional_Repositories: http://r.declaredesign.org

NEWS.md

@@ -1,11 +1,22 @@
-# estimatr 0.5.0 (GitHub version)
+# estimatr 0.6.0
 
-* Fixed bug that caused variances, standard errors, and p-values to be wrong for weighted "CR2" variance estimation
 * Added support for multivariate linear models
 * Added support for instrumental variables regression
+* Major change to name of object output elements to mostly match with `broom::tidy`
+  * old -> new
+  * `coefficient_names` -> `term`
+  * `se` -> `std.error`
+  * `p` -> `p.values`
+  * `ci_lower` -> `ci.lower`
+  * `ci_upper` -> `ci.upper`
+  * All of the above changes are also made to the column names on the output of `tidy`; furthermore for `tidy` objects one further name change from `coefficients` -> `estimate` has been made
+* Fixed bug that caused variances, standard errors, and p-values to be wrong for weighted "CR2" variance estimation
+* Fixed incorrect estimates when both weights and blocks were passed to `difference_in_means`
 * Rewrite NSE handling to be done by `rlang`
+* Rewrite `na.omit` handler in R
+* Major refactor of C++ underlying regression estimators
 
-# estimatr 0.4.0 (CRAN version)
+# estimatr 0.4.0
 
 * Changed suffix added to centered variables in `lm_lin()` from `_bar` to `_c`
 * Added all vignettes to `.Rbuildignore`, only available on website now

R/RcppExports.R

@@ -29,7 +29,7 @@ lm_variance_cr2 <- function(X, Xunweighted, XtX_inv, ei, weight_mean, clusters,
     .Call(`_estimatr_lm_variance_cr2`, X, Xunweighted, XtX_inv, ei, weight_mean, clusters, J, ci, which_covs)
 }
 
-naomitwhy <- function(df, is_na_generic) {
-    .Call(`_estimatr_naomitwhy`, df, is_na_generic)
+naomitwhy <- function(df, recursive_subset) {
+    .Call(`_estimatr_naomitwhy`, df, recursive_subset)
 }
 

R/S3_confint.R

@@ -19,26 +19,24 @@ confint.iv_robust <- confint_lm_like
 
 
 #' @export
-confint.difference_in_means <-
-  function(object,
-           parm = NULL,
-           level = NULL,
-           ...) {
-    cis <- get_ci_mat(object, level)
+confint.difference_in_means <- function(object,
+                                        parm = NULL,
+                                        level = NULL,
+                                        ...) {
+  cis <- get_ci_mat(object, level)
 
-    return(cis)
-  }
+  return(cis)
+}
 
 #' @export
-confint.horvitz_thompson <-
-  function(object,
-           parm = NULL,
-           level = NULL,
-           ...) {
-    cis <- get_ci_mat(object, level, ttest = FALSE)
+confint.horvitz_thompson <- function(object,
+                                     parm = NULL,
+                                     level = NULL,
+                                     ...) {
+  cis <- get_ci_mat(object, level, ttest = FALSE)
 
-    return(cis)
-  }
+  return(cis)
+}
 
 
 ## internal method that builds confidence intervals and labels the matrix to be returned

R/S3_predict.R

@@ -119,7 +119,6 @@ predict.lm_robust <- function(object,
   interval <- match.arg(interval)
 
   if (se.fit || interval != "none") {
-
     if (ncol(coefs) > 1) {
       stop("Can't set `se.fit` == TRUE with multivariate outcome")
     }

R/S3_print.R

@@ -13,7 +13,8 @@ print_summary_lm_like <- function(x,
                                   ...) {
   cat(
     "\nCall:\n", paste(deparse(x$call, nlines = 5), sep = "\n", collapse = "\n"),
-    "\n\n", sep = ""
+    "\n\n",
+    sep = ""
   )
   if (x$weighted) {
     cat("Weighted, ")
@@ -67,18 +68,13 @@ print.summary.iv_robust <- function(x,
 }
 
 #' @export
-print.difference_in_means <-
-  function(
-           x,
-           ...) {
-    cat("Design: ", x$design, "\n")
-    print(summarize_tidy(x))
-  }
+print.difference_in_means <- function(x, ...) {
+  cat("Design: ", x$design, "\n")
+  print(summarize_tidy(x))
+}
 
 
 #' @export
-print.horvitz_thompson <-
-  function(x,
-           ...) {
-    print(summarize_tidy(x))
-  }
+print.horvitz_thompson <- function(x, ...) {
+  print(summarize_tidy(x))
+}

R/S3_summary.R

@@ -1,7 +1,5 @@
 #' @export
-summary.lm_robust <- function(object,
-                              ...) {
-
+summary.lm_robust <- function(object, ...) {
   if (is.matrix(coef(object))) {
     ny <- ncol(coef(object))
 
@@ -29,7 +27,6 @@ summary.lm_robust <- function(object,
     all_models <- object
 
     for (i in seq(ny)) {
-
       for (nm in names(object)) {
         if (nm %in% mat_objs) {
           object[[nm]] <- all_models[[nm]][, i, drop = TRUE]
@@ -52,9 +49,7 @@ summary.lm_robust <- function(object,
 }
 
 #' @export
-summary.iv_robust <- function(object,
-                              ...) {
-
+summary.iv_robust <- function(object, ...) {
   summary_lm_model(object)
 }
 
@@ -85,8 +80,7 @@ summary_lm_model <- function(object) {
 
 
 #' @export
-summary.difference_in_means <- function(object,
-                                        ...) {
+summary.difference_in_means <- function(object, ...) {
   return(list(
     coefficients = summarize_tidy(object),
     design = object$design
@@ -95,12 +89,9 @@ summary.difference_in_means <- function(object,
 
 
 #' @export
-summary.horvitz_thompson <-
-  function(
-           object,
-           ...) {
-    return(list(coefficients = summarize_tidy(object, "z")))
-  }
+summary.horvitz_thompson <- function(object, ...) {
+  return(list(coefficients = summarize_tidy(object, "z")))
+}
 
 summarize_tidy <- function(object, test = "t", ...) {
   remove_cols <- c("term", "outcome")

R/S3_tidy.R

@@ -83,7 +83,6 @@ tidy.horvitz_thompson <- function(object, ...) {
 
 
 tidy_data_frame <- function(object, digits = NULL) {
-
   vec_cols <-
     c(
       "coefficients",
@@ -94,7 +93,9 @@ tidy_data_frame <- function(object, digits = NULL) {
       "df"
     )
 
-  tidy_mat <- do.call("cbind", lapply(vec_cols, function(x) {as.vector(object[[x]])}))
+  tidy_mat <- do.call("cbind", lapply(vec_cols, function(x) {
+    as.vector(object[[x]])
+  }))
   vec_cols[which(vec_cols == "coefficients")] <- "estimate"
   colnames(tidy_mat) <- vec_cols
   return_frame <- data.frame(