Merge pull request #255 from DeclareDesign/cran-fix

Cran fix

Author: jaspercooper

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: DesignLibrary
 Type: Package
 Title: Library of Research Designs
-Version: 0.1.4.9999
+Version: 0.1.5
 Authors@R: c(person("Graeme", "Blair", email = "graeme.blair@ucla.edu", role = c("aut")),
              person("Jasper", "Cooper", email = "jjc2247@columbia.edu", role = c("aut", "cre")),
              person("Alexander", "Coppock", email = "alex.coppock@yale.edu", role = c("aut")),

NAMESPACE

@@ -35,9 +35,9 @@ importFrom(DeclareDesign,diagnose_design)
 importFrom(DeclareDesign,draw_data)
 importFrom(DeclareDesign,draw_estimands)
 importFrom(DeclareDesign,draw_estimates)
+importFrom(DeclareDesign,label_estimator)
 importFrom(DeclareDesign,redesign)
 importFrom(DeclareDesign,set_diagnosands)
-importFrom(DeclareDesign,tidy_estimator)
 importFrom(estimatr,difference_in_means)
 importFrom(estimatr,iv_robust)
 importFrom(estimatr,lm_lin)

NEWS.md

@@ -1,3 +1,9 @@
+# DesignLibrary 0.1.5
+
+* fixed bug in randomized_response_designer diagnosands
+
+* deprecated `tidy_estimator()`
+
 # DesignLibrary 0.1.4
 
 * updated tests to be compatible with rlang 0.3.0

R/factorial_designer.R

@@ -25,7 +25,7 @@
 #' 
 #' @author \href{https://declaredesign.org/}{DeclareDesign Team}
 #' @concept factorial
-#' @importFrom DeclareDesign declare_assignment declare_estimand declare_estimator declare_population declare_potential_outcomes declare_reveal declare_step diagnose_design tidy_estimator
+#' @importFrom DeclareDesign declare_assignment declare_estimand declare_estimator declare_population declare_potential_outcomes declare_reveal declare_step diagnose_design label_estimator
 #' @importFrom fabricatr fabricate fabricate
 #' @importFrom randomizr conduct_ra 
 #' @importFrom estimatr tidy lm_robust
@@ -211,7 +211,7 @@ factorial_designer <- function(
 
   estimator_expr <- expr(
     declare_estimator(
-      handler = tidy_estimator(function(data){
+      handler = label_estimator(function(data){
         data[, names(data) %in% !!treatment_names] <- data[, names(data) %in% !!treatment_names] - 0.5
         mod <- lm_robust(formula = !!estimator_formula, data = data, weights = 1/Z_cond_prob)
         estimate_df <- tidy(mod)

R/process_tracing_designer.R

@@ -190,25 +190,25 @@ process_tracing_designer <- function(
       ))}
 
     prior_only_estimator <- declare_estimator(
-      handler = tidy_estimator(prior_only),
+      handler = label_estimator(prior_only),
       label = "No tests (Prior)",
       estimand = estimand
     )
 
     E1_only_estimator <- declare_estimator(
-      handler = tidy_estimator(E1_only),
+      handler = label_estimator(E1_only),
       label = label_E1,
       estimand = estimand
     )
 
     E2_only_estimator <- declare_estimator(
-      handler = tidy_estimator(E2_only),
+      handler = label_estimator(E2_only),
       label = label_E2,
       estimand = estimand
     )
 
     E1_and_E2_estimator <- declare_estimator(
-      handler = tidy_estimator(E1_and_E2),
+      handler = label_estimator(E1_and_E2),
       label = paste(label_E1, "and", label_E2),
       estimand = estimand
     )

R/randomized_response_designer.R

@@ -16,7 +16,7 @@
 #' @author \href{https://declaredesign.org/}{DeclareDesign Team}
 #' @concept experiment
 #' @concept descriptive
-#' @importFrom DeclareDesign declare_assignment declare_diagnosands declare_estimand declare_estimator declare_population declare_potential_outcomes declare_reveal set_diagnosands tidy_estimator
+#' @importFrom DeclareDesign declare_assignment declare_diagnosands declare_estimand declare_estimator declare_population declare_potential_outcomes declare_reveal set_diagnosands label_estimator
 #' @importFrom fabricatr fabricate draw_binary
 #' @importFrom randomizr conduct_ra 
 #' @export
@@ -58,7 +58,7 @@ randomized_response_designer <- function(N = 1000,
 
     # A: Answer Strategy
     estimator_randomized_response <- declare_estimator(
-      handler = tidy_estimator(
+      handler = label_estimator(
         function(data) with(
           data,
           data.frame(estimate = (mean(Y) - prob_forced_yes) / (1 - prob_forced_yes)))),
@@ -67,7 +67,7 @@ randomized_response_designer <- function(N = 1000,
     )
 
     estimator_direct_question <- declare_estimator(
-      handler = tidy_estimator(function(data) with(
+      handler = label_estimator(function(data) with(
         data,
         data.frame(estimate = mean(direct_answer)))),
       estimand = estimand,
@@ -81,7 +81,8 @@ randomized_response_designer <- function(N = 1000,
 
     randomized_response_design <- set_diagnosands(
       randomized_response_design,
-      declare_diagnosands(select = bias)
+      declare_diagnosands(bias = mean(estimate - estimand)
+)
     )
 
   }}}