diff --git a/DESCRIPTION b/DESCRIPTION
index c4cec27076..b34b5af0c6 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -55,7 +55,7 @@ Imports:
     tibble (>= 3.2.1),
     tidyr (>= 1.3.0)
 Suggests: 
-    cardx (>= 0.1.0.9020),
+    cardx (>= 0.1.0.9022),
     knitr,
     testthat (>= 3.2.0)
 VignetteBuilder: 
diff --git a/R/utils-add_p_tests.R b/R/utils-add_p_tests.R
index d585ce4915..2e759910bf 100644
--- a/R/utils-add_p_tests.R
+++ b/R/utils-add_p_tests.R
@@ -34,6 +34,20 @@ add_p_test_wilcox.test <- function(data, variable, by, test.args, ...) {
     )
 }
 
+add_p_test_mcnemar.test <- function(data, variable, by, test.args, ...) {
+  check_pkg_installed("cardx", reference_pkg = "gtsummary")
+
+  rlang::inject(
+    cardx::ard_stats_mcnemar_test(
+      data = data,
+      variable = all_of(variable),
+      by = all_of(by),
+      conf.level = conf.level,
+      !!!test.args
+    )
+  )
+}
+
 add_p_test_chisq.test <- function(data, variable, by, test.args, ...) {
   check_pkg_installed("cardx", reference_pkg = "gtsummary")
 
@@ -61,6 +75,7 @@ add_p_test_chisq.test.no.correct <- function(data, variable, by, test.args, ...)
 
 add_p_test_mood.test <- function(data, variable, by, test.args, ...) {
   check_pkg_installed("cardx", reference_pkg = "gtsummary")
+
   rlang::inject(
     cardx::ard_stats_mood_test(
       data = data,
@@ -71,8 +86,12 @@ add_p_test_mood.test <- function(data, variable, by, test.args, ...) {
   )
 }
 
+add_p_test_mcnemar.test_wide <- function(data, variable, by, test.args, ...) {
+  # TODO: Add this function
+}
 add_p_test_kruskal.test <- function(data, variable, by, ...) {
   check_pkg_installed("cardx", reference_pkg = "gtsummary")
+
   rlang::inject(
     cardx::ard_stats_kruskal_test(
       data = data,
@@ -103,17 +122,321 @@ add_p_test_fisher.test <- function(data, variable, by, test.args, conf.level = 0
     )
 }
 
-add_p_test_lme4 <- function(data, variable, by, group, type, ...) {
+add_p_test_aov <- function(data, variable, by, ...) {
+  check_pkg_installed("cardx", reference_pkg = "gtsummary")
+
+  rlang::inject(
+    cardx::ard_stats_aov(
+      # TODO: Update this to cardx::reformulate2()
+      formula = stats::reformulate(termlabels = by, response = variable),
+      data = data,
+      !!!test.args
+    )
+  )
+}
+
+add_p_test_oneway.test <- function(data, variable, by, test.args, ...) {
+  check_pkg_installed("cardx", reference_pkg = "gtsummary")
+
+  rlang::inject(
+    cardx::ard_stats_oneway_test(
+      # TODO: Update this to cardx::reformulate2()
+      formula = stats::reformulate(termlabels = by, response = variable),
+      data = data,
+      !!!test.args
+    )
+  )
+}
+
+add_p_test_mood.test <- function(data, variable, by, ...) {
+  check_pkg_installed("cardx", reference_pkg = "gtsummary")
+
+  rlang::inject(
+    cardx::ard_stats_mood_test(
+      data = data,
+      variable = all_of(variable),
+      by = all_of(by)
+    )
+  )
+}
 
+add_p_test_lme4 <- function(data, variable, by, group, ...) {
   check_pkg_installed("cardx", reference_pkg = "gtsummary")
   check_pkg_installed("lme4", reference_pkg = "cardx")
-  data <-
-    dplyr::select(data, all_of(c(variable, by, group))) %>%
-    dplyr::filter(stats::complete.cases(.)) |>
-    dplyr::mutate("{by}" := as.factor(.data[[by]]))
 
-  # formula0 <- reformulate()
+  cardx::ard_stats_anova(
+    x = data,
+    formulas = list(
+      glue::glue("as.factor({cardx::bt(by)}) ~ 1 + (1 | {cardx::bt(group)})") |> stats::as.formula(),
+      glue::glue("as.factor({cardx::bt(by)}) ~ {cardx::bt(variable)} + (1 | {cardx::bt(group)})") |> stats::as.formula()
+    ),
+    method = "glmer",
+    method.args = list(family = stats::binomial),
+    package = "lme4",
+    method_text = "random intercept logistic regression"
+  ) |>
+    # keep results associated with 2nd model
+    dplyr::filter(.data$variable %in% dplyr::last(.data$variable)) |>
+    dplyr::mutate(
+      variable = .env$variable,
+      warning = list(NULL)
+    )
+}
+
+
+add_p_tbl_summary_paired.t.test <- function(data, variable, by, group, test.args, conf.level = 0.95, ...) {
+  check_pkg_installed("cardx", reference_pkg = "gtsummary")
+
+  rlang::inject(
+    cardx::ard_stats_paired_t_test(
+      data = data,
+      variable = all_of(variable),
+      by = all_of(by),
+      id = all_of(id),
+      conf.level = conf.level,
+      !!!test.args
+    )
+  )
+}
+
+add_p_tbl_summary_paired.wilcox.test <- function(data, variable, by, group, test.args, conf.level = 0.95, ...) {
+  check_pkg_installed("cardx", reference_pkg = "gtsummary")
+
+  rlang::inject(
+    cardx::ard_stats_paired_wilcox_test(
+      data = data,
+      variable = all_of(variable),
+      by = all_of(by),
+      id = all_of(id),
+      conf.level = conf.level,
+      !!!test.args
+    )
+  )
+}
+
+add_p_test_prop.test <- function(data, variable, by, group, test.args, conf.level = 0.95, ...) {
+  check_pkg_installed("cardx", reference_pkg = "gtsummary")
+
+  rlang::inject(
+    cardx::ard_stats_prop_test(
+      data = data,
+      variable = all_of(variable),
+      by = all_of(by),
+      id = all_of(id),
+      conf.level = conf.level,
+      !!!test.args
+    )
+  )
+}
+
+add_p_test_ancova <- function(data, variable, by, adj.vars, ...) {
+  check_pkg_installed("cardx", reference_pkg = "gtsummary")
+
+  cardx::ard_regression_basic(
+    x =
+      cardx::construct_model(
+        data = data,
+        formula = cardx::reformulate2(c(by, adj.vars), response = variable),
+        method = "lm"
+      )
+  ) |>
+    dplyr::filter(
+      .data$variable %in% .env$by,
+      .data$stat_name %in% c("estimate", "p.value", "statistic", "std.error", "conf.low", "conf.high")
+    ) |>
+    dplyr::bind_rows(
+      .,
+      dplyr::filter(., dplyr::row_number() == 1L) |>
+        dplyr::mutate(
+          stat = "method",
+          stat_name = "method",
+          stat =
+            dplyr::case_when(
+              is.null(adj.vars) ~ "One-way ANOVA",
+              TRUE ~ "ANCOVA"
+            ),
+          fmt_fun = list(NULL)
+        )
+    )
+}
+
+
+add_p_test_cohens_d <- function(data, variable, by, test.args, conf.level = 0.95, ...) {
+  check_pkg_installed("cardx", reference_pkg = "gtsummary")
+
+  rlang::inject(
+    cardx::ard_effectsize_cohens_d(
+      data = data,
+      variable = all_of(variable),
+      by = all_of(by),
+      ci = conf.level,
+      !!!test.args
+    )
+  )
+}
+
+# TODO: Add this function to the test xlsx file
+add_p_test_paired_cohens_d <- function(data, variable, by, test.args, group, conf.level = 0.95, ...) {
+  check_pkg_installed("cardx", reference_pkg = "gtsummary")
+
+  rlang::inject(
+    cardx::ard_effectsize_paired_cohens_d(
+      data = data,
+      variable = all_of(variable),
+      by = all_of(by),
+      id = all_of(group),
+      ci = conf.level,
+      !!!test.args
+    )
+  )
+}
+
+# TODO: Add this function to the test xlsx file
+add_p_test_hedges_g <- function(data, variable, by, test.args, conf.level = 0.95, ...) {
+  check_pkg_installed("cardx", reference_pkg = "gtsummary")
+
+  rlang::inject(
+    cardx::ard_effectsize_hedges_g(
+      data = data,
+      variable = all_of(variable),
+      by = all_of(by),
+      ci = conf.level,
+      !!!test.args
+    )
+  )
+}
 
+# TODO: Add this function to the test xlsx file
+add_p_test_paired_hedges_g <- function(data, variable, by, test.args, group, conf.level = 0.95, ...) {
+  check_pkg_installed("cardx", reference_pkg = "gtsummary")
 
+  rlang::inject(
+    cardx::ard_effectsize_paired_hedges_g(
+      data = data,
+      variable = all_of(variable),
+      by = all_of(by),
+      id = all_of(group),
+      ci = conf.level,
+      !!!test.args
+    )
+  )
 }
 
+add_p_test_smd <- function(data, variable, by, ...) {
+  check_pkg_installed("cardx", reference_pkg = "gtsummary")
+
+  cardx::ard_smd_smd(
+    data = data,
+    variable = all_of(variable),
+    by = all_of(by)
+  )
+}
+
+
+# TODO: Do we need an ARD solution for this? This is just copied from the previous version
+add_p_test_emmeans <- function(data, variable, by, adj.vars, conf.level = 0.95,
+                               type, group = NULL, ...) {
+  if (!is.null(group)) check_pkg_installed("lme4", reference_pkg = "cardx")
+  if (inherits(data, "survey.design")) check_pkg_installed("survey", reference_pkg = "cardx")
+
+  data_frame <-
+    .extract_data_frame(data)
+
+  # checking inputs
+  if (!type %in% c("continuous", "dichotomous")) {
+    cli::cli_abort("Variable must be summary type 'continuous' or 'dichotomous'", call = get_cli_abort_call())
+  }
+  if (dplyr::n_distinct(data_frame[[by]], na.rm = TRUE) != 2) {
+    cli::cli_abort("`by=` must have exactly 2 levels", call = get_cli_abort_call())
+  }
+  if (type %in% "dichotomous" && dplyr::n_distinct(data_frame[[by]], na.rm = TRUE) != 2) {
+    cli::cli_abort("`variable=` must have exactly 2 levels", call = get_cli_abort_call())
+  }
+  if (is_survey(data) && !is.null(group)) {
+    cli::cli_abort("Cannot use `group=` argument with 'emmeans' and survey data.", call = get_cli_abort_call())
+  }
+
+  # assembling formula
+  # styler: off
+  termlabels <-
+    if (is.null(group)) c(by, adj.vars)
+    else c(by, adj.vars, glue::glue("(1 | {cardx::bt(group)})"))
+  response <-
+    if (type == "dichotomous") glue::glue("as.factor({cardx::bt(variable)})")
+    else cardx::bt(variable)
+  f <- stats::reformulate(termlabels, response)
+  f_by <- cardx::reformulate2(by)
+
+    rlang::inject(~ !!rlang::sym(chr_w_backtick(by)))
+  # styler: on
+
+  type2 <-
+    dplyr::case_when(
+      is.data.frame(data) && is.null(group) ~ type,
+      inherits(data, "survey.design") && is.null(group) && type == "dichotomous" ~ "dichotomous_svy",
+      inherits(data, "survey.design") && is.null(group) && type == "continuous" ~ "continuous_svy",
+      is.data.frame(data) && type == "dichotomous" ~ "dichotomous_mixed",
+      is.data.frame(data) && type == "continuous" ~ "continuous_mixed",
+    )
+
+  model_fun <-
+    switch(type2,
+           "dichotomous" =
+             cardx::construct_model(x = data)
+             purrr::partial(stats::glm, formula = f, data = data, family = stats::binomial),
+           "continuous" =
+             purrr::partial(stats::lm, formula = f, data = data),
+           "dichotomous_svy" =
+             purrr::partial(survey::svyglm, formula = f, design = data, family = stats::binomial),
+           "continuous_svy" =
+             purrr::partial(survey::svyglm, formula = f, design = data),
+           "dichotomous_mixed" =
+             purrr::partial(lme4::glmer, formula = f, data = data, family = stats::binomial),
+           "continuous_mixed" =
+             purrr::partial(lme4::lmer, formula = f, data = data)
+    )
+
+  emmeans_fun <-
+    switch(type,
+           "dichotomous" =
+             purrr::partial(emmeans::emmeans, specs = f_by, regrid = "response"),
+           "continuous" =
+             purrr::partial(emmeans::emmeans, specs = f_by)
+    )
+
+  # building model
+  model_fun() %>%
+    emmeans_fun() %>%
+    emmeans::contrast(method = "pairwise") %>%
+    summary(infer = TRUE, level = conf.level) %>%
+    tibble::as_tibble() %>%
+    dplyr::rename(
+      conf.low = any_of("asymp.LCL"),
+      conf.high = any_of("asymp.UCL"),
+      conf.low = any_of("lower.CL"),
+      conf.high = any_of("upper.CL")
+    ) %>%
+    dplyr::select(
+      "estimate",
+      std.error = "SE",
+      "conf.low", "conf.high",
+      "p.value"
+    ) %>%
+    dplyr::mutate(
+      method =
+        ifelse(
+          is.null(.env$adj.vars),
+          "Regression least-squares mean difference",
+          "Regression least-squares adjusted mean difference"
+        )
+    )
+
+}
+
+# TODO: we should be able to delete this is the emmeans functions gets deleted.
+.extract_data_frame <- function(x) {
+  if (is.data.frame(x)) {
+    return(x)
+  }
+  x$variables # return survey object data frame
+}