resolve all remaining notes

konfound-project · Apr 14, 2024 · daacc84 · daacc84
1 parent 6a96db4
commit daacc84
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Showing 3 changed files with 7 additions and 3 deletions.
diff --git a/NAMESPACE b/NAMESPACE
@@ -59,6 +59,8 @@ importFrom(stats,chisq.test)
 importFrom(stats,cor)
 importFrom(stats,fisher.test)
 importFrom(stats,glm)
+importFrom(stats,pt)
 importFrom(stats,qt)
+importFrom(stats,var)
 importFrom(tidyr,gather)
 importFrom(utils,globalVariables)
diff --git a/R/konfound-lm.R b/R/konfound-lm.R
@@ -16,6 +16,7 @@
 #' @return The results of the konfound analysis for the specified variable(s).
 #' @importFrom broom tidy glance
 #' @importFrom dplyr select filter bind_cols
+#' @importFrom stats var
 konfound_lm <- function(model_object,
                         tested_variable_string,
                         alpha,
@@ -26,7 +27,7 @@ konfound_lm <- function(model_object,
     glance_output <- broom::glance(model_object)
 
     coef_df <- tidy_output[tidy_output$term == tested_variable_string, ]
-    sdx = unname(sqrt(diag(var(model_object$model)))[tested_variable_string])
+    sdx = unname(sqrt(diag(stats::var(model_object$model)))[tested_variable_string])
 
   est_eff <- coef_df$estimate
   std_err <- coef_df$std.error

diff --git a/R/test_sensitivity_ln.R b/R/test_sensitivity_ln.R
@@ -1,6 +1,7 @@
 # Main function to test sensitivity for non-linear models to be wrapped
 # with pkonfound(), konfound(), and mkonfound()
 
+#' @importFrom stats pt
 test_sensitivity_ln <- function(est_eff,
                                 std_err,
                                 n_obs,
@@ -315,8 +316,8 @@ test_sensitivity_ln <- function(est_eff,
 
  ### Add to calculate p-value
  if (tails == 2) {
-	 p_start <- 2 * pt(abs(final_solution$t_start), n_obs - n_covariates - 2, lower.tail = FALSE)
-	 p_final <- 2 * pt(abs(final_solution$t_final), n_obs - n_covariates - 2, lower.tail = FALSE)
+	 p_start <- 2 * stats::pt(abs(final_solution$t_start), n_obs - n_covariates - 2, lower.tail = FALSE)
+	 p_final <- 2 * stats::pt(abs(final_solution$t_final), n_obs - n_covariates - 2, lower.tail = FALSE)
  } else if (tails == 1) {
 	 p_start = pt(abs(final_solution$t_start), n_obs - n_covariates - 2, lower.tail = FALSE)
 	 p_final = pt(abs(final_solution$t_final), n_obs - n_covariates - 2, lower.tail = FALSE)