Add one-sided tests, convenience functions for t-test, median test

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: boot.pval
 Title: Bootstrap p-Values
-Version: 0.6
+Version: 0.6.0.2000
 Authors@R: 
     person(given = "Måns",
            family = "Thulin",

NAMESPACE

@@ -1,7 +1,17 @@
 # Generated by roxygen2: do not edit by hand
 
+S3method(boot_median_test,data.frame)
+S3method(boot_median_test,default)
+S3method(boot_median_test,formula)
+S3method(boot_median_test,matrix)
+S3method(boot_t_test,data.frame)
+S3method(boot_t_test,default)
+S3method(boot_t_test,formula)
+S3method(boot_t_test,matrix)
 export(boot.pval)
+export(boot_median_test)
 export(boot_summary)
+export(boot_t_test)
 export(censboot_summary)
 export(summary_to_flextable)
 export(summary_to_gt)

NEWS.md

@@ -1,5 +1,5 @@
 # boot.pval development version
-Updated documentation for boot_summary and censboot_summary to not mention studentized intervals (which aren't supported by upstream packages).
+Added support for one-sided tests. Added the boot_t_test and boot_median_test functions for carrying out bootstrap tests of location. Updated documentation for boot_summary and censboot_summary to not mention studentized intervals (which aren't supported by upstream packages). Added a new vignette.
 
 # boot.pval version 0.6
 Added automatic handling of missing values, so that these don't have to be removed manually from the data prior to using boot_summary(). Added support for BCa intervals again, and improved performance for these intervals. Improved presentation of p-values in regression models. Added a vignette.

R/boot.pval.R

@@ -6,6 +6,7 @@
 #' @param type A vector of character strings representing the type of interval to base the test on. The value should be one of "norm", "basic", "stud", "perc" (the default), and "bca".
 #' @param theta_null The value of the parameter under the null hypothesis.
 #' @param pval_precision The desired precision for the p-value. The default is 1/R,  where R is the number of bootstrap samples in \code{boot_res}.
+#' @param alternative A character string specifying the alternative hypothesis. Must be one of "two.sided" (default), "greater", or "less".
 #' @param ... Additional arguments passed to \code{boot.ci}.
 #'
 #' @return A bootstrap p-value.
@@ -16,7 +17,8 @@
 #' @references
 #'  \insertRef{hall92}{boot.pval}
 #'
-#'  \insertRef{thulin21}{boot.pval}
+#'  \insertRef{thulin21}{boot.pval}'
+#' @seealso [boot_t_test()] for bootstrap t-tests, [boot_median_test()] for bootstrap tests for medians, [boot_summary()] for bootstrap tests for coefficients of regression models.
 #' @examples
 #' # Hypothesis test for the city data
 #' # H0: ratio = 1.4
@@ -46,6 +48,7 @@ boot.pval <- function(boot_res,
                       type = "perc",
                       theta_null = 0,
                       pval_precision = NULL,
+                      alternative = "two.sided",
                       ...)
 {
     if(is.null(pval_precision)) { pval_precision = 1/boot_res$R }
@@ -56,7 +59,7 @@ boot.pval <- function(boot_res,
     # Compute the 1-alpha confidence intervals, and extract
     # their bounds:
     ci <- suppressWarnings(boot::boot.ci(boot_res,
-            conf = 1- alpha_seq,
+            conf = 1-alpha_seq,
             type = type,
             ...))
 
@@ -69,7 +72,24 @@ boot.pval <- function(boot_res,
 
     # Find the smallest alpha such that theta_null is not contained in the 1-alpha
     # confidence interval:
-    alpha <- alpha_seq[which.min(theta_null >= bounds[,1] & theta_null <= bounds[,2])]
+    if(alternative == "two.sided") {
+      alpha <- alpha_seq[which.min(theta_null >= bounds[,1] & theta_null <= bounds[,2])]
+    }
+    if(alternative == "greater") {
+      if(sum(theta_null < bounds[,1]) == 0)
+      { alpha <- 1 } else
+      {
+        alpha <- alpha_seq[which.min(theta_null >= bounds[,1])]/2
+      }
+
+    }
+    if(alternative == "less") {
+      if(sum(theta_null > bounds[,2]) == 0)
+      { alpha <- 1 } else
+      {
+        alpha <- alpha_seq[which.min(theta_null <= bounds[,2])]/2
+      }
+    }
 
   # Return the p-value:
   return(alpha)

R/boot_summary.R

@@ -22,6 +22,7 @@
 #' @references
 #'  \insertRef{hall92}{boot.pval}
 #'  \insertRef{thulin21}{boot.pval}
+#' @seealso [boot_t_test()] for bootstrap t-tests, [boot_median_test()] for bootstrap tests for medians.
 #' @examples
 #' # Bootstrap summary of a linear model for mtcars:
 #' model <- lm(mpg ~ hp + vs, data = mtcars)