update documentation

NAMESPACE

@@ -2,17 +2,9 @@
 
 export(fastEmuTest)
 export(old_fastEmuTest)
-import(MASS)
-import(Matrix)
 import(radEmu)
-importFrom(stats,cov)
-importFrom(stats,median)
 importFrom(stats,model.matrix)
-importFrom(stats,optim)
-importFrom(stats,pchisq)
-importFrom(stats,qnorm)
 importFrom(stats,rbinom)
 importFrom(stats,rnbinom)
 importFrom(stats,rnorm)
 importFrom(stats,rpois)
-importFrom(stats,weighted.mean)

R/fastEmuTest.R

@@ -1,7 +1,5 @@
 #' Fit radEmu model after collapsing data into smaller joint model, runs score tests
 #'
-#' @param model either "full" to run score tests with the full joint model, "drop" to run score tests with
-#' a conditional joint model, or "agg" to run score tests with a joint marginal model
 #' @param constraint_cats a vector of category indices for categories that should be involved in the constraint
 #' and retained in any smaller joint model
 #' @param Y an n x J matrix or dataframe of nonnegative observations, or a phyloseq object containing an otu table and sample data.
@@ -72,6 +70,10 @@
 #' information matrix computed from full model fit and from null model fits? Default is
 #' FALSE. This parameter is used for simulations - in any applied analysis, type of
 #' p-value to be used should be chosen before conducting tests.
+#' @param model deprecated argument, default is "drop" to run the reduced model that drops
+#' all categories not in the constraint or being tested for each score test, "full" to run tests
+#' with the full joint model (equivalent to radEmu), or "agg" to run a different version of the reduced
+#' model in which all categories not in the constraint or being tested are aggregated together
 #'
 #' @return A list containing elements 'coef', 'B', 'penalized', 'Y_augmented',
 #' 'I', and 'Dy'.  Parameter estimates by
@@ -88,8 +90,7 @@
 #'
 #' @export
 #'
-fastEmuTest <- function(model = "full",
-                        constraint_cats,
+fastEmuTest <- function(constraint_cats,
                         Y,
                         X = NULL,
                         formula = NULL,
@@ -125,7 +126,8 @@ fastEmuTest <- function(model = "full",
                         max_step = 1,
                         trackB = FALSE,
                         return_nullB = FALSE,
-                        return_both_score_pvals = FALSE) {
+                        return_both_score_pvals = FALSE,
+                        model = NULL) {
 
   if (sum(rowSums(Y) == 0) > 0) {
     stop("There is at least one sample with no counts in any category. Please remove samples that have no counts in any category.")
@@ -190,7 +192,9 @@ fastEmuTest <- function(model = "full",
     }
   }
 
-
+  if (is.null(model)) {
+    model = "drop"
+  }
   # update model based on model chosen and categories to use
   if (model == "full") {
     mod_Y <- Y[, new_order]

tests/testthat/test-fastEmuTest.R

@@ -95,3 +95,60 @@ test_that("test-fastEmuTest works", {
                           return_both_score_pvals = TRUE)
   expect_false(is.na(res_drop$p_vals$score_pval_null_info))
 })
+
+test_that("new updates to fastEmuTest work the same as old version", {
+
+  library(fastEmu)
+  library(radEmu)
+
+  # simulate data
+  n <- 100
+  J <- 200
+  b0 <- rnorm(J)
+  b1 <- rnorm(J)
+  X <- cbind(1, rep(c(0, 1), each = n/2),
+             rnorm(n))
+  Y <- radEmu:::simulate_data(n = n,
+                              J = J,
+                              b0 = b0,
+                              b1 = b1,
+                              distn = "Poisson",
+                              zinb_size = 5,
+                              zinb_zero_prop = 0.6,
+                              mean_count_before_ZI = 50)
+  colnames(Y) <- paste0("category", 1:ncol(Y))
+
+  # test 100th category
+  # randomly select 25 categories to use as constraint
+  cats <- sample((1:ncol(Y))[-100], 25)
+
+  # run dropped model
+  # run dropped model, cat categories as constraint, test 100th
+  res_drop <- fastEmuTest(constraint_cats = cats,
+                          Y = Y,
+                          X = X,
+                          test_kj = data.frame(k = 2, j = 100),
+                          tau = 2,
+                          B_null_tol = 0.005,
+                          tolerance = 0.005,
+                          constraint_tol = 0.001,
+                          return_wald_p = TRUE,
+                          use_both_cov = FALSE,
+                          use_fullmodel_info = TRUE,
+                          return_both_score_pvals = TRUE)
+  old_res_drop <- old_fastEmuTest(model = "drop",
+                              constraint_cats = cats,
+                              Y = Y,
+                              X = X,
+                              test_kj = data.frame(k = 2, j = 100),
+                              tau = 2,
+                              B_null_tol = 0.005,
+                              tolerance = 0.005,
+                              constraint_tol = 0.001,
+                              return_wald_p = TRUE,
+                              use_both_cov = FALSE,
+                              use_fullmodel_info = TRUE,
+                              return_both_score_pvals = TRUE)
+  expect_true(all.equal(res_drop$coef[26, ], old_res_drop$coef[26, ]))
+
+})