importFrom

DESCRIPTION

@@ -28,8 +28,6 @@ Depends:
 Imports:
     rlang
 Suggests: 
-    methods,
-    devtools,
     knitr,
     testthat, 
     ggplot2,

R/DesignLibrary.R

@@ -6,10 +6,12 @@
 #' 
 #' @name DesignLibrary
 #' 
+#' @importFrom utils globalVariables
+#' 
 #' 
 
 
-utils::globalVariables(
+globalVariables(
   names = c(
     "A",
     "B",

R/block_cluster_two_arm_designer.R

@@ -32,7 +32,7 @@
 #' @author \href{https://declaredesign.org/}{DeclareDesign Team}
 #' @concept experiment 
 #' @concept blocking
-#' @import DeclareDesign stats utils fabricatr estimatr randomizr
+#' @importFrom rlang is_integerish
 #' @export
 #' @examples
 #' # Generate a design using default arguments:
@@ -54,9 +54,9 @@ block_cluster_two_arm_designer <- function(N_blocks = 1,
                                            treatment_mean = control_mean + ate
 ){  
   if(any(N_blocks < 1, N_clusters_in_block < 1, N_i_in_cluster < 1) ||
-     any(!rlang::is_integerish(N_blocks), 
-         !rlang::is_integerish(N_clusters_in_block), 
-         !rlang::is_integerish(N_i_in_cluster))) stop("N_* arguments must be positive integers")
+     any(!is_integerish(N_blocks), 
+         !is_integerish(N_clusters_in_block), 
+         !is_integerish(N_i_in_cluster))) stop("N_* arguments must be positive integers")
   if(sd_block < 0) stop("sd_block must be nonnegative")
   if(sd_cluster < 0) stop("sd_cluster must be nonnegative")
   if(sd_i_0 < 0) stop("sd_i_0 must be nonnegative")

R/cluster_sampling_designer.R

@@ -18,7 +18,6 @@
 #' @concept clusters
 #' @concept observational
 #' @concept measurement
-#' @import DeclareDesign stats utils fabricatr estimatr randomizr
 #' @export
 #' @examples
 #' # To make a design using default arguments:

R/factorial_designer.R

@@ -17,8 +17,8 @@
 #' 
 #' @author \href{https://declaredesign.org/}{DeclareDesign Team}
 #' @concept factorial
+#' @importFrom rlang is_integerish expr quos sym parse_expr UQS eval_bare
 #' @export
-#' @import rlang
 #' @examples
 #' 
 #' # A factorial design using default arguments
@@ -45,7 +45,7 @@ factorial_designer <- function(
   if(any(grepl(" ", fixed = TRUE, outcome_name))) stop("Please remove spaces from `outcome_name' strings.")
   if(length(outcome_means) != 2^k || length(outcome_sds) != 2^k) stop("`outcome_means' and `outcome_sds` arguments must be the same as length of 2^(k).")
   if(length(probs) != k) stop("`probs` must be the same as length of k.")
-  if(k < 2 || !rlang::is_integerish(k)) stop("`k' should be a positive integer > 1.")
+  if(k < 2 || !is_integerish(k)) stop("`k' should be a positive integer > 1.")
   if(any(outcome_sds<0)) stop("`outcome_sds' should be nonnegative.")
   if(any(probs <= 0)) stop("`probs' should have positive values only.")
 
@@ -80,32 +80,32 @@ factorial_designer <- function(
   outcome_sds_ <- outcome_sds; means_ <- outcome_means; probs_ <- probs; N_ <- N; k_ <- k 
 
   if(is.null(fixed)) fixed <- ""
-  if(!"outcome_sds"   %in% fixed)  outcome_sds_ <- sapply(1:length(outcome_sds), function(i) rlang::expr(outcome_sds[!!i])) 
-  if(!"outcome_means" %in% fixed)  outcome_means_ <- sapply(1:length(outcome_means), function(i) rlang::expr(outcome_means[!!i])) 
-  if(!"N"     %in% fixed)  N_ <- rlang::expr(N)
+  if(!"outcome_sds"   %in% fixed)  outcome_sds_ <- sapply(1:length(outcome_sds), function(i) expr(outcome_sds[!!i])) 
+  if(!"outcome_means" %in% fixed)  outcome_means_ <- sapply(1:length(outcome_means), function(i) expr(outcome_means[!!i])) 
+  if(!"N"     %in% fixed)  N_ <- expr(N)
 
 
   # population --------------------------------------------------------------
-  population_expr <- rlang::expr(declare_population(!!N_))
+  population_expr <- expr(declare_population(!!N_))
 
   # potential outcomes ------------------------------------------------------
   potouts <- sapply(1:length(outcome_means),
-                    function(i) rlang::quos(!!outcome_means_[[i]] + rnorm(!!N_, 0, !!outcome_sds_[[i]])))
+                    function(i) quos(!!outcome_means_[[i]] + rnorm(!!N_, 0, !!outcome_sds_[[i]])))
   names_pos <- paste0(outcome_name, "_", assignment_string)
   names(potouts) <- names_pos
 
-  potentials_expr <- rlang::expr(declare_potential_outcomes(!!!(potouts)))
+  potentials_expr <- expr(declare_potential_outcomes(!!!(potouts)))
 
   # assignment --------------------------------------------------------------
-  Z <- rlang::sym("Z")
-  assignment_given_factor <- sapply(1:length(cond_row), function(i) rlang::quos(as.numeric(!!Z %in% !!cond_row[[i]])))
+  Z <- sym("Z")
+  assignment_given_factor <- sapply(1:length(cond_row), function(i) quos(as.numeric(!!Z %in% !!cond_row[[i]])))
   names(assignment_given_factor) <- treatment_names
 
-  assignment_expr1 <- rlang::expr(declare_assignment(conditions = 1:(2^!!k_), prob_each = !!prob_each))
-  assignment_expr2 <- rlang::expr(declare_step(fabricate, !!!assignment_given_factor))
+  assignment_expr1 <- expr(declare_assignment(conditions = 1:(2^!!k_), prob_each = !!prob_each))
+  assignment_expr2 <- expr(declare_step(fabricate, !!!assignment_given_factor))
 
   # reveal outcomes ---------------------------------------------------------
-  reveal_expr <- rlang::expr(declare_reveal(
+  reveal_expr <- expr(declare_reveal(
     handler = function(data){
       potential_cols <- mapply(paste, data[, !!treatment_names, drop = FALSE], sep = "_", SIMPLIFY = FALSE)
       potential_cols <- do.call(paste, c(!!outcome_name, potential_cols, sep = "_"))
@@ -150,15 +150,15 @@ factorial_designer <- function(
 
   d <- interaction(k)
   estimand_operations <- apply(d[,(k+2):ncol(d)], 2, function(col) paste(col, "*", d$PO, collapse = " + ")) 
-  estimand_preexpr <- sapply(1:2^k, function(i) rlang::expr(mean(!!rlang::parse_expr(estimand_operations[i]))))
+  estimand_preexpr <- sapply(1:2^k, function(i) expr(mean(!!parse_expr(estimand_operations[i]))))
   names(estimand_preexpr) <-  names(estimand_operations)
-  
-  estimand_expr <- rlang::expr(declare_estimand(rlang::UQS(estimand_preexpr), label = "ATE"))
+
+  estimand_expr <- expr(declare_estimand(UQS(estimand_preexpr), label = "ATE"))
 
   # estimators --------------------------------------------------------------
   estimator_formula <- formula(paste0(outcome_name, " ~ ", paste(treatment_names, collapse = "*")))
 
-  estimator_expr <- rlang::expr(
+  estimator_expr <- expr(
     declare_estimator(
       handler = tidy_estimator(function(data){
         data[, names(data) %in% !!treatment_names] <- data[, names(data) %in% !!treatment_names] - 0.5

R/mediation_analysis_designer.R

@@ -18,7 +18,6 @@
 #' @author \href{https://declaredesign.org/}{DeclareDesign Team}
 #' @concept experiment
 #' @concept mediation
-#' @import DeclareDesign stats utils fabricatr estimatr randomizr
 #' @export
 #' @examples
 #' # Generate a mediation analysis design using default arguments:

R/multi_arm_designer.R

@@ -17,7 +17,6 @@
 #' @author \href{https://declaredesign.org/}{DeclareDesign Team}
 #' @concept experiment
 #' @concept multiarm trial
-#' @import DeclareDesign stats utils fabricatr estimatr randomizr rlang
 #' @export
 #' @examples
 #'
@@ -64,7 +63,7 @@ multi_arm_designer <- function(N = 30,
   conditions <- as.character(conditions)
 
   f_Y <- formula(
-    paste0("Y ~ ",paste0(
+    paste0("Y ~ ", paste0(
       "(", outcome_means_, " + ", error_names,
       ")*( Z == '", conditions, "')",
       collapse = " + "), "+ u"))

R/pretest_posttest_designer.R

@@ -18,7 +18,6 @@
 #' @concept experiment
 #' @concept difference-in-differences
 #' @concept baseline
-#' @import DeclareDesign stats utils fabricatr estimatr randomizr
 #' @export
 #' @examples
 #' # Generate a pre-test post-test design using default arguments:

R/process_tracing_designer.R

@@ -34,7 +34,7 @@
 #' @author \href{https://declaredesign.org/}{DeclareDesign Team}
 #' @concept qualitative 
 #' @concept process tracing
-#' @import DeclareDesign stats utils fabricatr estimatr randomizr
+#' @importFrom rlang is_integerish is_character
 #' @export
 #' @examples
 #' # Generate a process-tracing design using default arguments:
@@ -77,7 +77,7 @@ process_tracing_designer <- function(
   label_E1 = "Smoking Gun",
   label_E2 = "Straw in the Wind"
 ){
-  if(!rlang::is_integerish(N) || N < 1) stop("N must be a positive integer.")
+  if(!is_integerish(N) || N < 1) stop("N must be a positive integer.")
   if(prob_X < 0 || prob_X > 1) stop("prob_X must be in [0,1].")
   if(length(process_proportions) != 4) stop("process_proportions must be of length 4.")
   if(sum(process_proportions) != 1 || any(process_proportions < 0) || any(process_proportions> 1)) stop("process_proportions must be a 3-simplex.")
@@ -93,8 +93,8 @@ process_tracing_designer <- function(
     c((1 - p1) * (1 - p2) + r,p2 * (1 - p1) - r, p1 * (1 - p2) - r, p1 * p2 + r)}
   if(min(test_prob(p_E1_H, p_E2_H, cor_E1E2_H)) < 0) stop("Correlation coefficient not compatible with probabilities")
   if(min(test_prob(p_E1_not_H, p_E2_not_H, cor_E1E2_not_H)) < 0) stop("Correlation coefficient not compatible with probabilities")
-  if(!rlang::is_character(label_E1) || length(label_E1) > 1) stop("label_E1 must be a character of length 1.")
-  if(!rlang::is_character(label_E2) || length(label_E2) > 1) stop("label_E2 must be a character of length 1.")
+  if(!is_character(label_E1) || length(label_E1) > 1) stop("label_E1 must be a character of length 1.")
+  if(!is_character(label_E2) || length(label_E2) > 1) stop("label_E2 must be a character of length 1.")
   {{{
     # M: Model
     population <- declare_population(

R/randomized_response_designer.R

@@ -15,7 +15,6 @@
 #' @author \href{https://declaredesign.org/}{DeclareDesign Team}
 #' @concept experiment
 #' @concept descriptive
-#' @import DeclareDesign stats utils fabricatr estimatr randomizr
 #' @export
 #'
 #' @examples

R/regression_discontinuity_designer.R

@@ -16,7 +16,7 @@
 #' @author \href{https://declaredesign.org/}{DeclareDesign Team}
 #' @concept observational
 #' @concept regression discontinuity
-#' @import DeclareDesign stats utils fabricatr estimatr randomizr
+#' @importFrom rlang is_integerish
 #' @export
 #' @examples
 #' # Generate a regression discontinuity design using default arguments:
@@ -34,7 +34,7 @@ regression_discontinuity_designer <- function(
 ){
   if(cutoff <= 0 || cutoff >= 1) stop("cutoff must be in (0,1).")
   if(poly_reg_order < 1) stop("poly_reg_order must be at least 1.")
-  if(!rlang::is_integerish(poly_reg_order)) stop("poly_reg_order must be an integer.")
+  if(!is_integerish(poly_reg_order)) stop("poly_reg_order must be an integer.")
   if(length(control_coefs) < 1) stop("control_coefs must be a numeric vector of length > 0.")
   if(length(treatment_coefs) < 1) stop("treatment_coefs must be a numeric vector of length > 0.")
   if(outcome_sd < 0) stop("outcome_sd must be positive.")

R/simple_factorial_designer.R

@@ -27,7 +27,6 @@
 #' @return A two-by-two factorial design.
 #' @author \href{https://declaredesign.org/}{DeclareDesign Team}
 #' @concept experiment factorial
-#' @import DeclareDesign stats utils fabricatr estimatr randomizr
 #' @export
 #'
 #' @examples

R/simple_iv_designer.R

@@ -19,7 +19,6 @@
 #' @return A simple instrumental variables design.
 #' @author \href{https://declaredesign.org/}{DeclareDesign Team}
 #' @concept experiment
-#' @import DeclareDesign stats utils fabricatr estimatr randomizr
 #' @export
 #'
 #' @examples

R/simple_spillover_designer.R

@@ -21,7 +21,6 @@
 #' @author \href{https://declaredesign.org/}{DeclareDesign Team}
 #' @concept experiment
 #' @concept spillovers
-#' @import DeclareDesign stats utils fabricatr estimatr randomizr
 #' @export
 #' @examples
 #' # Generate a simple spillover design using default arguments:

R/simple_two_arm_designer.R

@@ -20,7 +20,6 @@
 #' @return A simple two-arm design.
 #' @author \href{https://declaredesign.org/}{DeclareDesign Team}
 #' @concept experiment
-#' @import DeclareDesign stats utils fabricatr estimatr randomizr
 #' @export
 #'
 #' @examples

R/two_arm_attrition_designer.R

@@ -22,7 +22,6 @@
 #' @return A post-treatment design.
 #' @author \href{https://declaredesign.org/}{DeclareDesign Team} 
 #' @concept post-treatment
-#' @import DeclareDesign stats utils fabricatr estimatr randomizr
 #' @export
 #' @examples
 #' # To make a design using default argument (missing completely at random):

tests/testthat/test_designers.R

@@ -1,7 +1,6 @@
 
 context(desc = "Testing that designers in the library work as they should")
 
-
 functions <- ls("package:DesignLibrary")
 designers <- functions[grepl("_designer\\b",functions)]
 

tests/testthat/test_helpers.R

@@ -1,9 +1,7 @@
 context(desc = "Testing that helpers in the library work as they should")
 
-
-
 testthat::test_that(
-  desc = paste0("functions can be passed to designer and returned by construct_design_code"),
+  desc = "functions can be passed to designer and returned by construct_design_code",
   code = {
 
     test_designer <- function(summary_function,N){