diff --git a/R/test_catcat.R b/R/test_catcat.R
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+#' @title 
+#' Compute chi-square or Fisher's exact test for two categorical variables
+#'
+#' @description 
+#' This function computes a chi-square or Fisher's exact test for two categorical variables in a data frame.
+#'
+#' @param data A data frame containing the variables of interest.
+#' @param x A character string specifying the name of the first variable.
+#' @param y A character string specifying the name of the second variable.
+#' @param na_x A vector of values to be treated as missing in \code{x}.
+#' @param na_y A vector of values to be treated as missing in \code{y}.
+#' 
+#' @details 
+#' If the cell counts are lower than 5, the function will use Fisher's exact test. Otherwise, it will use a chi-square test.
+#'
+#' @return A tibble containing the results of the chi-square or Fisher's exact test.
+#'
+#' @examples
+#' data("mtcars")
+#' test_catcat(mtcars, "cyl", "vs")
+#'
+#' @importFrom rstatix chisq_test
+#' @importFrom stats fisher.test
+#' @importFrom dplyr filter mutate select
+#' @importFrom tidyr pivot_longer
+#' @importFrom broom tidy
+#'
+#' @export
+test_chisq <- function(data, x, y, na_x = NULL, na_y = NULL){
+  
+  # remove NA values
+  data2 <- 
+    data %>%
+    filter(!(!!sym(x) %in% na_x)) %>%
+    filter(!(!!sym(y) %in% na_y))
+  
+  # Create new variables to feed into `rstatix::chisq_test()`
+  stat_x <- data2[[x]]
+  stat_y <- data2[[y]]
+  
+  # Check expected cell counts
+  expected_counts <-
+    chisq.test(table(data2[[x]], data2[[y]]))$expected %>%
+    suppressWarnings()
+  
+  if (any(expected_counts < 5)) {
+    # Use Fisher's exact test if expected cell counts are low
+    result <- fisher.test(x = factor(stat_x), y = factor(stat_y)) %>%
+      broom::tidy(out) %>% # Return a data frame
+      mutate(n = NA,
+             statistic = NA,
+             df = NA,
+             `p.signif` = NA,
+             p = `p.value`) %>%
+      select(
+        n, 
+        statistic,
+        p, 
+        df,
+        method, 
+        p.signif,
+        alternative
+      )
+    
+  } else {
+    # Use chi-square test if expected cell counts are not low
+    result <- rstatix::chisq_test(x = stat_x, y = stat_y) %>%
+      mutate(alternative = NULL)
+  }
+  
+  # Return results
+  dplyr::tibble(
+    col_x = x,
+    col_y = y
+  ) %>%
+    cbind(result) %>%
+    dplyr::as_tibble()
+  
+}
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