diff --git a/DESCRIPTION b/DESCRIPTION
index 99a51aec8..b19f9c897 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,7 +1,7 @@
 Type: Package
 Package: bayestestR
 Title: Understand and Describe Bayesian Models and Posterior Distributions
-Version: 0.14.0.8
+Version: 0.14.0.9
 Authors@R:
     c(person(given = "Dominique",
              family = "Makowski",
diff --git a/NEWS.md b/NEWS.md
index db28c58f5..c3232190d 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -2,14 +2,18 @@
 
 ## Changes
 
-* Support for `posterior::rvar`-type column in data frames. 
-  For example, a data frame `df` with an `rvar` column `".pred"` can now be 
+* Support for `posterior::rvar`-type column in data frames.
+  For example, a data frame `df` with an `rvar` column `".pred"` can now be
   called directly via `p_direction(df, rvar_col = ".pred")`.
 
 * Added support for `{marginaleffects}`
 
+* The ROPE or threshold ranges in `rope()`, `describe_posterior()`, `p_significance()`
+  and `equivalence_test()` can now be specified as a list. This allows for different
+  ranges for different parameters.
+
 * Results from objects generated by `{emmeans}` (`emmGrid`/`emm_list`) now
-  return results with appended grid-data. 
+  return results with appended grid-data.
 
 * Usability improvements for `p_direction()`:
 
diff --git a/R/describe_posterior.R b/R/describe_posterior.R
index 80085750f..715501f31 100644
--- a/R/describe_posterior.R
+++ b/R/describe_posterior.R
@@ -18,9 +18,10 @@
 #'   For each "test", the corresponding \pkg{bayestestR} function is called
 #'   (e.g. [bayestestR::rope()] or [bayestestR::p_direction()]) and its results
 #'   included in the summary output.
-#' @param rope_range ROPE's lower and higher bounds. Should be a list of two
-#'   values (e.g., `c(-0.1, 0.1)`) or `"default"`. If `"default"`,
-#'   the bounds are set to `x +- 0.1*SD(response)`.
+#' @param rope_range ROPE's lower and higher bounds. Should be a vector of two
+#'   values (e.g., `c(-0.1, 0.1)`), `"default"` or a list of numeric vectors of
+#'   the same length as numbers of parameters. If `"default"`, the bounds are
+#'   set to `x +- 0.1*SD(response)`.
 #' @param rope_ci The Credible Interval (CI) probability, corresponding to the
 #'   proportion of HDI, to use for the percentage in ROPE.
 #' @param keep_iterations If `TRUE`, will keep all iterations (draws) of
@@ -90,6 +91,7 @@
 #'   describe_posterior(model)
 #'   describe_posterior(model, centrality = "all", dispersion = TRUE, test = "all")
 #'   describe_posterior(model, ci = c(0.80, 0.90))
+#'   describe_posterior(model, rope_range = list(c(-10, 5), c(-0.2, 0.2), "default"))
 #'
 #'   # emmeans estimates
 #'   # -----------------------------------------------
diff --git a/R/equivalence_test.R b/R/equivalence_test.R
index 57d4b2058..638af6102 100644
--- a/R/equivalence_test.R
+++ b/R/equivalence_test.R
@@ -85,6 +85,10 @@
 #' \donttest{
 #' model <- rstanarm::stan_glm(mpg ~ wt + cyl, data = mtcars)
 #' equivalence_test(model)
+#' # multiple ROPE ranges - asymmetric, symmetric, default
+#' equivalence_test(model, range = list(c(10, 40), c(-5, -4), "default"))
+#' # named ROPE ranges
+#' equivalence_test(model, range = list(wt = c(-5, -4), `(Intercept)` = c(10, 40)))
 #'
 #' # plot result
 #' test <- equivalence_test(model)
@@ -163,13 +167,33 @@ equivalence_test.data.frame <- function(x, range = "default", ci = 0.95, rvar_co
     return(.append_datagrid(out, x))
   }
 
-  l <- insight::compact_list(lapply(
-    x,
-    equivalence_test,
-    range = range,
-    ci = ci,
-    verbose = verbose
-  ))
+  # multiple ranges for the parameters - iterate over parameters and range
+  if (is.list(range)) {
+    # check if list of values contains only valid values
+    range <- .check_list_range(range, x)
+    # apply thresholds to each column
+    l <- insight::compact_list(mapply(
+      function(p, r) {
+        equivalence_test(
+          p,
+          range = r,
+          ci = ci,
+          verbose = verbose
+        )
+      },
+      x,
+      range,
+      SIMPLIFY = FALSE
+    ))
+  } else {
+    l <- insight::compact_list(lapply(
+      x,
+      equivalence_test,
+      range = range,
+      ci = ci,
+      verbose = verbose
+    ))
+  }
 
   dat <- do.call(rbind, l)
   out <- data.frame(
@@ -244,7 +268,7 @@ equivalence_test.BFBayesFactor <- function(x, range = "default", ci = 0.95, verb
                                      verbose = TRUE) {
   if (all(range == "default")) {
     range <- rope_range(x, verbose = verbose)
-  } else if (!all(is.numeric(range)) || length(range) != 2L) {
+  } else if (!is.list(range) && (!all(is.numeric(range)) || length(range) != 2L)) {
     insight::format_error("`range` should be 'default' or a vector of 2 numeric values (e.g., c(-0.1, 0.1)).")
   }
 
@@ -257,24 +281,7 @@ equivalence_test.BFBayesFactor <- function(x, range = "default", ci = 0.95, verb
     verbose = verbose
   )
 
-  l <- sapply(
-    params,
-    equivalence_test,
-    range = range,
-    ci = ci,
-    verbose = verbose,
-    simplify = FALSE
-  )
-
-  dat <- do.call(rbind, l)
-  out <- data.frame(
-    Parameter = rep(names(l), each = nrow(dat) / length(l)),
-    dat,
-    stringsAsFactors = FALSE
-  )
-
-  class(out) <- unique(c("equivalence_test", "see_equivalence_test", class(out)))
-  out
+  equivalence_test(params, range = range, ci = ci, verbose = verbose)
 }
 
 
diff --git a/R/eti.R b/R/eti.R
index 4bcf75af1..404a9f036 100644
--- a/R/eti.R
+++ b/R/eti.R
@@ -316,8 +316,8 @@ eti.get_predicted <- function(x, ci = 0.95, use_iterations = FALSE, verbose = TR
   ))
 
   data.frame(
-    "CI" = ci,
-    "CI_low" = results[1],
-    "CI_high" = results[2]
+    CI = ci,
+    CI_low = results[1],
+    CI_high = results[2]
   )
 }
diff --git a/R/p_rope.R b/R/p_rope.R
index df8f3a9e4..5a93dda7b 100644
--- a/R/p_rope.R
+++ b/R/p_rope.R
@@ -229,7 +229,7 @@ p_rope.mcmc.list <- p_rope.mcmc
 #' @keywords internal
 .p_rope <- function(rope_rez) {
   cols <- c("Parameter", "ROPE_low", "ROPE_high", "ROPE_Percentage", "Effects", "Component")
-  out <- as.data.frame(rope_rez[cols[cols %in% names(rope_rez)]])
+  out <- as.data.frame(rope_rez)[cols[cols %in% names(rope_rez)]]
   names(out)[names(out) == "ROPE_Percentage"] <- "p_ROPE"
 
   class(out) <- c("p_rope", "see_p_rope", "data.frame")
diff --git a/R/p_significance.R b/R/p_significance.R
index 46c8bd1c5..12a692c1b 100644
--- a/R/p_significance.R
+++ b/R/p_significance.R
@@ -15,7 +15,11 @@
 #'   (i.e. the threshold range is set to -0.1 and 0.1, i.e. reflects a symmetric
 #'   interval)
 #' - a numeric vector of length two (e.g., `c(-0.2, 0.1)`), useful for
-#'   asymmetric intervals.
+#'   asymmetric intervals
+#' - a list of numeric vectors, where each vector corresponds to a parameter
+#' - a list of *named* numeric vectors, where names correspond to parameter
+#'   names. In this case, all parameters that have no matching name in `threshold`
+#'   will be set to `"default"`.
 #' @inheritParams rope
 #' @inheritParams hdi
 #'
@@ -53,6 +57,10 @@
 #'   chains = 2, refresh = 0
 #' )
 #' p_significance(model)
+#' # multiple thresholds - asymmetric, symmetric, default
+#' p_significance(model, threshold = list(c(-10, 5), 0.2, "default"))
+#' # named thresholds
+#' p_significance(model, threshold = list(wt = 0.2, `(Intercept)` = c(-10, 5)))
 #' }
 #' @export
 p_significance <- function(x, ...) {
@@ -128,11 +136,26 @@ p_significance.data.frame <- function(x, threshold = "default", rvar_col = NULL,
   }
 
 
-  threshold <- .select_threshold_ps(threshold = threshold)
+  threshold <- .select_threshold_ps(threshold = threshold, params = x)
   x <- .select_nums(x)
 
   if (ncol(x) == 1) {
     ps <- .p_significance(x[, 1], threshold = threshold, ...)
+  } else if (is.list(threshold)) {
+    # check if list of values contains only valid values
+    threshold <- .check_list_range(threshold, x, larger_two = TRUE)
+    # apply thresholds to each column
+    ps <- mapply(
+      function(p, thres) {
+        .p_significance(
+          p,
+          threshold = thres
+        )
+      },
+      x,
+      threshold,
+      SIMPLIFY = FALSE
+    )
   } else {
     ps <- sapply(x, .p_significance, threshold = threshold, simplify = TRUE, ...)
   }
@@ -268,12 +291,15 @@ p_significance.stanreg <- function(x,
                                    ...) {
   effects <- match.arg(effects)
   component <- match.arg(component)
-  threshold <- .select_threshold_ps(model = x, threshold = threshold, verbose = verbose)
+  params <- insight::get_parameters(x, effects = effects, component = component, parameters = parameters)
 
-  result <- p_significance(
-    insight::get_parameters(x, effects = effects, component = component, parameters = parameters),
-    threshold = threshold
+  threshold <- .select_threshold_ps(
+    model = x,
+    threshold = threshold,
+    params = params,
+    verbose = verbose
   )
+  result <- p_significance(params, threshold = threshold)
 
   cleaned_parameters <- insight::clean_parameters(x)
   out <- .prepare_output(result, cleaned_parameters, inherits(x, "stanmvreg"))
@@ -304,12 +330,15 @@ p_significance.brmsfit <- function(x,
                                    ...) {
   effects <- match.arg(effects)
   component <- match.arg(component)
-  threshold <- .select_threshold_ps(model = x, threshold = threshold, verbose = verbose)
+  params <- insight::get_parameters(x, effects = effects, component = component, parameters = parameters)
 
-  result <- p_significance(
-    insight::get_parameters(x, effects = effects, component = component, parameters = parameters),
-    threshold = threshold
+  threshold <- .select_threshold_ps(
+    model = x,
+    threshold = threshold,
+    params = params,
+    verbose = verbose
   )
+  result <- p_significance(params, threshold = threshold)
 
   cleaned_parameters <- insight::clean_parameters(x)
   out <- .prepare_output(result, cleaned_parameters)
@@ -364,7 +393,42 @@ as.double.p_significance <- as.numeric.p_significance
 # helpers --------------------------
 
 #' @keywords internal
-.select_threshold_ps <- function(model = NULL, threshold = "default", verbose = TRUE) {
+.select_threshold_ps <- function(model = NULL, threshold = "default", params = NULL, verbose = TRUE) {
+  if (is.list(threshold)) {
+    # if we have named elements, complete list
+    if (!is.null(params)) {
+      named_threshold <- names(threshold)
+      if (!is.null(named_threshold)) {
+        # find out which name belongs to which parameter
+        pos <- match(named_threshold, colnames(params))
+        # if not all element names were found, error
+        if (anyNA(pos)) {
+          insight::format_error(paste(
+            "Not all elements of `threshold` were found in the parameters. Please check following names:",
+            toString(named_threshold[is.na(pos)])
+          ))
+        }
+        # now "fill" non-specified elements with "default"
+        out <- as.list(rep("default", ncol(params)))
+        out[pos] <- threshold
+        # overwrite former threshold
+        threshold <- out
+      }
+    }
+    lapply(threshold, function(i) {
+      out <- .select_threshold_list(model = model, threshold = i, verbose = verbose)
+      if (length(out) == 1) {
+        out <- c(-1 * abs(out), abs(out))
+      }
+      out
+    })
+  } else {
+    .select_threshold_list(model = model, threshold = threshold, verbose = verbose)
+  }
+}
+
+#' @keywords internal
+.select_threshold_list <- function(model = NULL, threshold = "default", verbose = TRUE) {
   # If default
   if (all(threshold == "default")) {
     if (is.null(model)) {
@@ -372,13 +436,49 @@ as.double.p_significance <- as.numeric.p_significance
     } else {
       threshold <- rope_range(model, verbose = verbose)[2]
     }
-  } else if (!all(is.numeric(threshold)) || length(threshold) > 2) {
+  } else if (!is.list(threshold) && (!all(is.numeric(threshold)) || length(threshold) > 2)) {
     insight::format_error(
       "`threshold` should be one of the following values:",
       "- \"default\", in which case the threshold is based on `rope_range()`",
-      "- a single numeric value (e.g., 0.1), which is used as range around zero (i.e. the threshold range is set to -0.1 and 0.1)",
+      "- a single numeric value (e.g., 0.1), which is used as range around zero (i.e. the threshold range is set to -0.1 and 0.1)", # nolint
       "- a numeric vector of length two (e.g., `c(-0.2, 0.1)`)"
     )
   }
   threshold
 }
+
+.check_list_range <- function(range, params, larger_two = FALSE) {
+  # if we have named elements, complete list
+  named_range <- names(range)
+  if (!is.null(named_range)) {
+    # find out which name belongs to which parameter
+    pos <- match(named_range, colnames(params))
+    # if not all element names were found, error
+    if (anyNA(pos)) {
+      insight::format_error(paste(
+        "Not all elements of `range` were found in the parameters. Please check following names:",
+        toString(named_range[is.na(pos)])
+      ))
+    }
+    # now "fill" non-specified elements with "default"
+    out <- as.list(rep("default", ncol(params)))
+    out[pos] <- range
+    # overwrite former range
+    range <- out
+  }
+  if (length(range) != ncol(params)) {
+    insight::format_error("Length of `range` (i.e. number of ROPE limits) should match the number of parameters.")
+  }
+  # check if list of values contains only valid values
+  checks <- vapply(range, function(r) {
+    if (larger_two) {
+      !all(r == "default") || !all(is.numeric(r)) || length(r) > 2
+    } else {
+      !all(r == "default") || !all(is.numeric(r)) || length(r) != 2
+    }
+  }, logical(1))
+  if (!all(checks)) {
+    insight::format_error("`range` should be 'default' or a vector of 2 numeric values (e.g., c(-0.1, 0.1)).")
+  }
+  range
+}
diff --git a/R/print.R b/R/print.R
index fbe3a2fd6..dfc62eeb7 100644
--- a/R/print.R
+++ b/R/print.R
@@ -70,14 +70,19 @@ print.map_estimate <- function(x,
 
 #' @export
 print.p_rope <- function(x, digits = 2, ...) {
-  caption <- sprintf(
-    "Proportion of samples inside the ROPE [%.*f, %.*f]",
-    digits,
-    x$ROPE_low[1],
-    digits,
-    x$ROPE_high[1]
-  )
-  x$ROPE_low <- x$ROPE_high <- NULL
+  # check if we have multiple ROPE values
+  if (insight::n_unique(x$ROPE_low) > 1) {
+    caption <- "Proportion of samples inside the ROPE"
+  } else {
+    caption <- sprintf(
+      "Proportion of samples inside the ROPE [%.*f, %.*f]",
+      digits,
+      x$ROPE_low[1],
+      digits,
+      x$ROPE_high[1]
+    )
+    x$ROPE_low <- x$ROPE_high <- NULL
+  }
   .print_default(
     x = x,
     digits = digits,
@@ -90,14 +95,26 @@ print.p_rope <- function(x, digits = 2, ...) {
 
 #' @export
 print.p_significance <- function(x, digits = 2, ...) {
-  caption <- sprintf(
-    "Practical Significance (threshold: %s)",
-    insight::format_value(attributes(x)$threshold, digits = digits)
-  )
+  threshold <- attributes(x)$threshold
+  if (is.list(threshold)) {
+    caption <- "Practical Significance"
+    out <- as.data.frame(do.call(rbind, threshold))
+    colnames(out) <- c("ROPE_low", "ROPE_high")
+    x$ROPE_low <- out$ROPE_low
+    x$ROPE_high <- out$ROPE_high
+    ci_string <- "ROPE"
+  } else {
+    caption <- sprintf(
+      "Practical Significance (threshold: %s)",
+      insight::format_value(attributes(x)$threshold, digits = digits)
+    )
+    ci_string <- NULL
+  }
   .print_default(
     x = x,
     digits = digits,
     caption = caption,
+    ci_string = ci_string,
     ...
   )
 }
@@ -302,7 +319,7 @@ print.bayesfactor_parameters <- function(x, digits = 3, log = FALSE, ...) {
     sep = " ",
     header = NULL,
     format = "text",
-    align = align,
+    align = align
   ))
 
   invisible(x)
diff --git a/R/print.equivalence_test.R b/R/print.equivalence_test.R
index 1b9d03cac..9bf61fdb6 100644
--- a/R/print.equivalence_test.R
+++ b/R/print.equivalence_test.R
@@ -2,7 +2,10 @@
 print.equivalence_test <- function(x, digits = 2, ...) {
   orig_x <- x
   insight::print_color("# Test for Practical Equivalence\n\n", "blue")
-  cat(sprintf("  ROPE: [%.*f %.*f]\n\n", digits, x$ROPE_low[1], digits, x$ROPE_high[1]))
+  # print ROPE limits, if we just have one set of ROPE values
+  if (insight::n_unique(x$ROPE_low) == 1) {
+    cat(sprintf("  ROPE: [%.*f %.*f]\n\n", digits, x$ROPE_low[1], digits, x$ROPE_high[1]))
+  }
 
   # fix "sd" pattern
   model <- .retrieve_model(x)
@@ -23,15 +26,8 @@ print.equivalence_test <- function(x, digits = 2, ...) {
     }
   }
 
-  # find the longest HDI-value, so we can align the brackets in the ouput
-  x$HDI_low <- sprintf("%.*f", digits, x$HDI_low)
-  x$HDI_high <- sprintf("%.*f", digits, x$HDI_high)
-
-  maxlen_low <- max(nchar(x$HDI_low))
-  maxlen_high <- max(nchar(x$HDI_high))
-
   x$ROPE_Percentage <- sprintf("%.*f %%", digits, x$ROPE_Percentage * 100)
-  x$HDI <- sprintf("[%*s %*s]", maxlen_low, x$HDI_low, maxlen_high, x$HDI_high)
+  x$HDI <- insight::format_ci(x$HDI_low, x$HDI_high, ci = NULL, digits = digits)
 
   ci <- unique(x$CI)
   keep.columns <- c(
@@ -39,6 +35,12 @@ print.equivalence_test <- function(x, digits = 2, ...) {
     "ROPE_Equivalence", "ROPE_Percentage", "CI", "HDI"
   )
 
+  # keep ROPE columns for multiple ROPE values
+  if (insight::n_unique(x$ROPE_low) > 1) {
+    keep.columns <- c(keep.columns, "ROPE")
+    x$ROPE <- insight::format_ci(x$ROPE_low, x$ROPE_high, ci = NULL, digits = digits)
+  }
+
   x <- x[, intersect(keep.columns, colnames(x))]
 
   colnames(x)[which(colnames(x) == "ROPE_Equivalence")] <- "H0"
diff --git a/R/print_html.R b/R/print_html.R
index a7a4be75c..fb487c405 100644
--- a/R/print_html.R
+++ b/R/print_html.R
@@ -31,22 +31,41 @@ print_html.p_map <- function(x, digits = 2, caption = "MAP-based p-value", ...)
 
 #' @export
 print_html.p_rope <- function(x, digits = 2, ...) {
-  caption <- sprintf(
-    "Proportion of samples inside the ROPE [%.*f, %.*f]",
-    digits, x$ROPE_low[1], digits, x$ROPE_high[1]
-  )
-  x$ROPE_low <- x$ROPE_high <- NULL
+  # check if we have multiple ROPE values
+  if (insight::n_unique(x$ROPE_low) > 1) {
+    caption <- "Proportion of samples inside the ROPE"
+  } else {
+    caption <- sprintf(
+      "Proportion of samples inside the ROPE [%.*f, %.*f]",
+      digits,
+      x$ROPE_low[1],
+      digits,
+      x$ROPE_high[1]
+    )
+    x$ROPE_low <- x$ROPE_high <- NULL
+  }
   .print_html_default(x = x, digits = digits, caption = caption, ci_string = "ROPE", ...)
 }
 
 
 #' @export
 print_html.p_significance <- function(x, digits = 2, ...) {
-  caption <- sprintf(
-    "Practical Significance (threshold: %s)",
-    insight::format_value(attributes(x)$threshold, digits = digits)
-  )
-  .print_html_default(x = x, digits = digits, caption = caption, ...)
+  threshold <- attributes(x)$threshold
+  if (is.list(threshold)) {
+    caption <- "Practical Significance"
+    out <- as.data.frame(do.call(rbind, threshold))
+    colnames(out) <- c("ROPE_low", "ROPE_high")
+    x$ROPE_low <- out$ROPE_low
+    x$ROPE_high <- out$ROPE_high
+    ci_string <- "ROPE"
+  } else {
+    caption <- sprintf(
+      "Practical Significance (threshold: %s)",
+      insight::format_value(attributes(x)$threshold, digits = digits)
+    )
+    ci_string <- NULL
+  }
+  .print_html_default(x = x, digits = digits, caption = caption, ci_string = ci_string, ...)
 }
 
 
@@ -86,7 +105,7 @@ print_html.bayesfactor_models <- function(x,
     log = log,
     show_names = show_names,
     caption = caption,
-    align = c("llr"),
+    align = "llr",
     ...
   )
 }
@@ -103,7 +122,7 @@ print_html.bayesfactor_inclusion <- function(x,
     digits = digits,
     log = log,
     caption = caption,
-    align = c("lrrr"),
+    align = "lrrr",
     ...
   )
 }
diff --git a/R/print_md.R b/R/print_md.R
index f8910a123..053ae0472 100644
--- a/R/print_md.R
+++ b/R/print_md.R
@@ -30,22 +30,41 @@ print_md.p_map <- function(x, digits = 2, caption = "MAP-based p-value", ...) {
 
 #' @export
 print_md.p_rope <- function(x, digits = 2, ...) {
-  caption <- sprintf(
-    "Proportion of samples inside the ROPE [%.*f, %.*f]",
-    digits, x$ROPE_low[1], digits, x$ROPE_high[1]
-  )
-  x$ROPE_low <- x$ROPE_high <- NULL
+  # check if we have multiple ROPE values
+  if (insight::n_unique(x$ROPE_low) > 1) {
+    caption <- "Proportion of samples inside the ROPE"
+  } else {
+    caption <- sprintf(
+      "Proportion of samples inside the ROPE [%.*f, %.*f]",
+      digits,
+      x$ROPE_low[1],
+      digits,
+      x$ROPE_high[1]
+    )
+    x$ROPE_low <- x$ROPE_high <- NULL
+  }
   .print_md_default(x = x, digits = digits, caption = caption, ci_string = "ROPE", ...)
 }
 
 
 #' @export
 print_md.p_significance <- function(x, digits = 2, ...) {
-  caption <- sprintf(
-    "Practical Significance (threshold: %s)",
-    insight::format_value(attributes(x)$threshold, digits = digits)
-  )
-  .print_md_default(x = x, digits = digits, caption = caption, ...)
+  threshold <- attributes(x)$threshold
+  if (is.list(threshold)) {
+    caption <- "Practical Significance"
+    out <- as.data.frame(do.call(rbind, threshold))
+    colnames(out) <- c("ROPE_low", "ROPE_high")
+    x$ROPE_low <- out$ROPE_low
+    x$ROPE_high <- out$ROPE_high
+    ci_string <- "ROPE"
+  } else {
+    caption <- sprintf(
+      "Practical Significance (threshold: %s)",
+      insight::format_value(attributes(x)$threshold, digits = digits)
+    )
+    ci_string <- NULL
+  }
+  .print_md_default(x = x, digits = digits, caption = caption, ci_string = ci_string, ...)
 }
 
 
@@ -85,7 +104,7 @@ print_md.bayesfactor_models <- function(x,
     log = log,
     show_names = show_names,
     caption = caption,
-    align = c("llr"),
+    align = "llr",
     ...
   )
 }
@@ -102,7 +121,7 @@ print_md.bayesfactor_inclusion <- function(x,
     digits = digits,
     log = log,
     caption = caption,
-    align = c("lrrr"),
+    align = "lrrr",
     ...
   )
 }
diff --git a/R/rope.R b/R/rope.R
index 782967a8f..24c3a9b4a 100644
--- a/R/rope.R
+++ b/R/rope.R
@@ -6,13 +6,21 @@
 #' @param x Vector representing a posterior distribution. Can also be a
 #' `stanreg` or `brmsfit` model.
 #' @param range ROPE's lower and higher bounds. Should be `"default"` or
-#' depending on the number of outcome variables a vector or a list. In
-#' models with one response, `range` should be a vector of length two (e.g.,
-#' `c(-0.1, 0.1)`). In multivariate models, `range` should be a list with a
-#' numeric vectors for each response variable. Vector names should correspond
-#' to the name of the response variables. If `"default"` and input is a vector,
-#' the range is set to `c(-0.1, 0.1)`. If `"default"` and input is a Bayesian
-#' model, [`rope_range()`][rope_range] is used.
+#' depending on the number of outcome variables a vector or a list. For models
+#' with one response, `range` can be:
+#'
+#' - a vector of length two (e.g., `c(-0.1, 0.1)`),
+#' - a list of numeric vector of the same length as numbers of parameters (see
+#'   'Examples').
+#' - a list of *named* numeric vectors, where names correspond to parameter
+#'   names. In this case, all parameters that have no matching name in `range`
+#'   will be set to `"default"`.
+#'
+#' In multivariate models, `range` should be a list with a numeric vectors for
+#' each response variable. Vector names should correspond to the name of the
+#' response variables. If `"default"` and input is a vector, the range is set to
+#' `c(-0.1, 0.1)`. If `"default"` and input is a Bayesian model,
+#' [`rope_range()`] is used.
 #' @param ci The Credible Interval (CI) probability, corresponding to the
 #' proportion of HDI, to use for the percentage in ROPE.
 #' @param ci_method The type of interval to use to quantify the percentage in
@@ -33,7 +41,7 @@
 #' size according to Cohen, 1988). This could be generalized: For instance,
 #' for linear models, the ROPE could be set as `0 +/- .1 * sd(y)`.
 #' This ROPE range can be automatically computed for models using the
-#' [rope_range] function.
+#' [`rope_range()`] function.
 #'
 #' Kruschke (2010, 2011, 2014) suggests using the proportion of  the `95%`
 #' (or `89%`, considered more stable) [HDI][hdi] that falls within the
@@ -110,6 +118,12 @@
 #' rope(model)
 #' rope(model, ci = c(0.90, 0.95))
 #'
+#' # multiple ROPE ranges
+#' rope(model, range = list(c(-10, 5), c(-0.2, 0.2), "default"))
+#'
+#' # named ROPE ranges
+#' rope(model, range = list(gear = c(-3, 2), wt = c(-0.2, 0.2)))
+#'
 #' library(emmeans)
 #' rope(emtrends(model, ~1, "wt"), ci = c(0.90, 0.95))
 #'
@@ -381,7 +395,7 @@ rope.stanreg <- function(x, range = "default", ci = 0.95, ci_method = "ETI", eff
 
   if (all(range == "default")) {
     range <- rope_range(x, verbose = verbose)
-  } else if (!all(is.numeric(range)) || length(range) != 2) {
+  } else if (!is.list(range) && (!all(is.numeric(range)) || length(range) != 2)) {
     insight::format_error("`range` should be 'default' or a vector of 2 numeric values (e.g., c(-0.1, 0.1)).")
   }
 
@@ -442,7 +456,7 @@ rope.brmsfit <- function(x,
         "With a multivariate model, `range` should be 'default' or a list of named numeric vectors with length 2."
       )
     }
-  } else if (!all(is.numeric(range)) || length(range) != 2) {
+  } else if (!is.list(range) && (!all(is.numeric(range)) || length(range) != 2)) {
     insight::format_error(
       "`range` should be 'default' or a vector of 2 numeric values (e.g., c(-0.1, 0.1))."
     )
@@ -514,7 +528,7 @@ rope.sim.merMod <- function(x,
 
   if (all(range == "default")) {
     range <- rope_range(x, verbose = verbose)
-  } else if (!all(is.numeric(range)) || length(range) != 2) {
+  } else if (!is.list(range) && (!all(is.numeric(range)) || length(range) != 2)) {
     insight::format_error("`range` should be 'default' or a vector of 2 numeric values (e.g., c(-0.1, 0.1)).")
   }
 
@@ -574,7 +588,7 @@ rope.sim.merMod <- function(x,
 rope.sim <- function(x, range = "default", ci = 0.95, ci_method = "ETI", parameters = NULL, verbose = TRUE, ...) {
   if (all(range == "default")) {
     range <- rope_range(x, verbose = verbose)
-  } else if (!all(is.numeric(range)) || length(range) != 2) {
+  } else if (!is.list(range) && (!all(is.numeric(range)) || length(range) != 2)) {
     insight::format_error("`range` should be 'default' or a vector of 2 numeric values (e.g., c(-0.1, 0.1)).")
   }
 
@@ -607,15 +621,35 @@ rope.sim <- function(x, range = "default", ci = 0.95, ci_method = "ETI", paramet
 
 #' @keywords internal
 .prepare_rope_df <- function(parms, range, ci, ci_method, verbose) {
-  tmp <- sapply(
-    parms,
-    rope,
-    range = range,
-    ci = ci,
-    ci_method = ci_method,
-    verbose = verbose,
-    simplify = FALSE
-  )
+  if (is.list(range)) {
+    # check if list of values contains only valid values
+    range <- .check_list_range(range, parms)
+    # apply thresholds to each column
+    tmp <- mapply(
+      function(p, r) {
+        rope(
+          p,
+          range = r,
+          ci = ci,
+          ci_method = ci_method,
+          verbose = verbose
+        )
+      },
+      parms,
+      range,
+      SIMPLIFY = FALSE
+    )
+  } else {
+    tmp <- sapply(
+      parms,
+      rope,
+      range = range,
+      ci = ci,
+      ci_method = ci_method,
+      verbose = verbose,
+      simplify = FALSE
+    )
+  }
 
   HDI_area <- lapply(tmp, attr, which = "HDI_area")
 
diff --git a/man/describe_posterior.Rd b/man/describe_posterior.Rd
index bc3e0fcfe..a81b821fa 100644
--- a/man/describe_posterior.Rd
+++ b/man/describe_posterior.Rd
@@ -121,9 +121,10 @@ For each "test", the corresponding \pkg{bayestestR} function is called
 (e.g. \code{\link[=rope]{rope()}} or \code{\link[=p_direction]{p_direction()}}) and its results
 included in the summary output.}
 
-\item{rope_range}{ROPE's lower and higher bounds. Should be a list of two
-values (e.g., \code{c(-0.1, 0.1)}) or \code{"default"}. If \code{"default"},
-the bounds are set to \code{x +- 0.1*SD(response)}.}
+\item{rope_range}{ROPE's lower and higher bounds. Should be a vector of two
+values (e.g., \code{c(-0.1, 0.1)}), \code{"default"} or a list of numeric vectors of
+the same length as numbers of parameters. If \code{"default"}, the bounds are
+set to \code{x +- 0.1*SD(response)}.}
 
 \item{rope_ci}{The Credible Interval (CI) probability, corresponding to the
 proportion of HDI, to use for the percentage in ROPE.}
@@ -210,6 +211,7 @@ if (require("rstanarm") && require("emmeans")) {
   describe_posterior(model)
   describe_posterior(model, centrality = "all", dispersion = TRUE, test = "all")
   describe_posterior(model, ci = c(0.80, 0.90))
+  describe_posterior(model, rope_range = list(c(-10, 5), c(-0.2, 0.2), "default"))
 
   # emmeans estimates
   # -----------------------------------------------
diff --git a/man/equivalence_test.Rd b/man/equivalence_test.Rd
index accbbcaae..27fc778f7 100644
--- a/man/equivalence_test.Rd
+++ b/man/equivalence_test.Rd
@@ -51,13 +51,22 @@ equivalence_test(x, ...)
 \item{...}{Currently not used.}
 
 \item{range}{ROPE's lower and higher bounds. Should be \code{"default"} or
-depending on the number of outcome variables a vector or a list. In
-models with one response, \code{range} should be a vector of length two (e.g.,
-\code{c(-0.1, 0.1)}). In multivariate models, \code{range} should be a list with a
-numeric vectors for each response variable. Vector names should correspond
-to the name of the response variables. If \code{"default"} and input is a vector,
-the range is set to \code{c(-0.1, 0.1)}. If \code{"default"} and input is a Bayesian
-model, \code{\link[=rope_range]{rope_range()}} is used.}
+depending on the number of outcome variables a vector or a list. For models
+with one response, \code{range} can be:
+\itemize{
+\item a vector of length two (e.g., \code{c(-0.1, 0.1)}),
+\item a list of numeric vector of the same length as numbers of parameters (see
+'Examples').
+\item a list of \emph{named} numeric vectors, where names correspond to parameter
+names. In this case, all parameters that have no matching name in \code{range}
+will be set to \code{"default"}.
+}
+
+In multivariate models, \code{range} should be a list with a numeric vectors for
+each response variable. Vector names should correspond to the name of the
+response variables. If \code{"default"} and input is a vector, the range is set to
+\code{c(-0.1, 0.1)}. If \code{"default"} and input is a Bayesian model,
+\code{\link[=rope_range]{rope_range()}} is used.}
 
 \item{ci}{The Credible Interval (CI) probability, corresponding to the
 proportion of HDI, to use for the percentage in ROPE.}
@@ -164,6 +173,10 @@ print(test, digits = 4)
 \donttest{
 model <- rstanarm::stan_glm(mpg ~ wt + cyl, data = mtcars)
 equivalence_test(model)
+# multiple ROPE ranges - asymmetric, symmetric, default
+equivalence_test(model, range = list(c(10, 40), c(-5, -4), "default"))
+# named ROPE ranges
+equivalence_test(model, range = list(wt = c(-5, -4), `(Intercept)` = c(10, 40)))
 
 # plot result
 test <- equivalence_test(model)
diff --git a/man/p_rope.Rd b/man/p_rope.Rd
index 8791c0224..4d27fe375 100644
--- a/man/p_rope.Rd
+++ b/man/p_rope.Rd
@@ -42,13 +42,22 @@ p_rope(x, ...)
 \item{...}{Currently not used.}
 
 \item{range}{ROPE's lower and higher bounds. Should be \code{"default"} or
-depending on the number of outcome variables a vector or a list. In
-models with one response, \code{range} should be a vector of length two (e.g.,
-\code{c(-0.1, 0.1)}). In multivariate models, \code{range} should be a list with a
-numeric vectors for each response variable. Vector names should correspond
-to the name of the response variables. If \code{"default"} and input is a vector,
-the range is set to \code{c(-0.1, 0.1)}. If \code{"default"} and input is a Bayesian
-model, \code{\link[=rope_range]{rope_range()}} is used.}
+depending on the number of outcome variables a vector or a list. For models
+with one response, \code{range} can be:
+\itemize{
+\item a vector of length two (e.g., \code{c(-0.1, 0.1)}),
+\item a list of numeric vector of the same length as numbers of parameters (see
+'Examples').
+\item a list of \emph{named} numeric vectors, where names correspond to parameter
+names. In this case, all parameters that have no matching name in \code{range}
+will be set to \code{"default"}.
+}
+
+In multivariate models, \code{range} should be a list with a numeric vectors for
+each response variable. Vector names should correspond to the name of the
+response variables. If \code{"default"} and input is a vector, the range is set to
+\code{c(-0.1, 0.1)}. If \code{"default"} and input is a Bayesian model,
+\code{\link[=rope_range]{rope_range()}} is used.}
 
 \item{verbose}{Toggle off warnings.}
 
diff --git a/man/p_significance.Rd b/man/p_significance.Rd
index 30b2170e5..5d6d0fbaf 100644
--- a/man/p_significance.Rd
+++ b/man/p_significance.Rd
@@ -59,7 +59,11 @@ and based on \code{\link[=rope_range]{rope_range()}} if a (Bayesian) model is pr
 (i.e. the threshold range is set to -0.1 and 0.1, i.e. reflects a symmetric
 interval)
 \item a numeric vector of length two (e.g., \code{c(-0.2, 0.1)}), useful for
-asymmetric intervals.
+asymmetric intervals
+\item a list of numeric vectors, where each vector corresponds to a parameter
+\item a list of \emph{named} numeric vectors, where names correspond to parameter
+names. In this case, all parameters that have no matching name in \code{threshold}
+will be set to \code{"default"}.
 }}
 
 \item{use_iterations}{Logical, if \code{TRUE} and \code{x} is a \code{get_predicted} object,
@@ -131,6 +135,10 @@ model <- rstanarm::stan_glm(mpg ~ wt + cyl,
   chains = 2, refresh = 0
 )
 p_significance(model)
+# multiple thresholds - asymmetric, symmetric, default
+p_significance(model, threshold = list(c(-10, 5), 0.2, "default"))
+# named thresholds
+p_significance(model, threshold = list(wt = 0.2, `(Intercept)` = c(-10, 5)))
 }
 \dontshow{\}) # examplesIf}
 }
diff --git a/man/rope.Rd b/man/rope.Rd
index 87036d460..242edb880 100644
--- a/man/rope.Rd
+++ b/man/rope.Rd
@@ -54,13 +54,22 @@ rope(x, ...)
 \item{...}{Currently not used.}
 
 \item{range}{ROPE's lower and higher bounds. Should be \code{"default"} or
-depending on the number of outcome variables a vector or a list. In
-models with one response, \code{range} should be a vector of length two (e.g.,
-\code{c(-0.1, 0.1)}). In multivariate models, \code{range} should be a list with a
-numeric vectors for each response variable. Vector names should correspond
-to the name of the response variables. If \code{"default"} and input is a vector,
-the range is set to \code{c(-0.1, 0.1)}. If \code{"default"} and input is a Bayesian
-model, \code{\link[=rope_range]{rope_range()}} is used.}
+depending on the number of outcome variables a vector or a list. For models
+with one response, \code{range} can be:
+\itemize{
+\item a vector of length two (e.g., \code{c(-0.1, 0.1)}),
+\item a list of numeric vector of the same length as numbers of parameters (see
+'Examples').
+\item a list of \emph{named} numeric vectors, where names correspond to parameter
+names. In this case, all parameters that have no matching name in \code{range}
+will be set to \code{"default"}.
+}
+
+In multivariate models, \code{range} should be a list with a numeric vectors for
+each response variable. Vector names should correspond to the name of the
+response variables. If \code{"default"} and input is a vector, the range is set to
+\code{c(-0.1, 0.1)}. If \code{"default"} and input is a Bayesian model,
+\code{\link[=rope_range]{rope_range()}} is used.}
 
 \item{ci}{The Credible Interval (CI) probability, corresponding to the
 proportion of HDI, to use for the percentage in ROPE.}
@@ -107,7 +116,7 @@ to the -0.1 to 0.1 range of a standardized parameter (negligible effect
 size according to Cohen, 1988). This could be generalized: For instance,
 for linear models, the ROPE could be set as \verb{0 +/- .1 * sd(y)}.
 This ROPE range can be automatically computed for models using the
-\link{rope_range} function.
+\code{\link[=rope_range]{rope_range()}} function.
 
 Kruschke (2010, 2011, 2014) suggests using the proportion of  the \verb{95\%}
 (or \verb{89\%}, considered more stable) \link[=hdi]{HDI} that falls within the
@@ -171,6 +180,12 @@ model <- suppressWarnings(
 rope(model)
 rope(model, ci = c(0.90, 0.95))
 
+# multiple ROPE ranges
+rope(model, range = list(c(-10, 5), c(-0.2, 0.2), "default"))
+
+# named ROPE ranges
+rope(model, range = list(gear = c(-3, 2), wt = c(-0.2, 0.2)))
+
 library(emmeans)
 rope(emtrends(model, ~1, "wt"), ci = c(0.90, 0.95))
 
diff --git a/tests/testthat/_snaps/equivalence_test.md b/tests/testthat/_snaps/equivalence_test.md
new file mode 100644
index 000000000..cf351f609
--- /dev/null
+++ b/tests/testthat/_snaps/equivalence_test.md
@@ -0,0 +1,72 @@
+# equivalence test, rstanarm
+
+    Code
+      print(out)
+    Output
+      # Test for Practical Equivalence
+      
+        ROPE: [-0.18 0.18]
+      
+      Parameter   |       H0 | inside ROPE |        95% HDI
+      -----------------------------------------------------
+      (Intercept) | Rejected |      0.00 % | [-2.68, -0.50]
+      size        | Accepted |    100.00 % |  [-0.04, 0.07]
+      period2     | Rejected |      0.00 % | [-1.61, -0.36]
+      period3     | Rejected |      0.00 % | [-1.77, -0.40]
+      period4     | Rejected |      0.00 % | [-2.52, -0.76]
+      
+      
+
+---
+
+    Code
+      print(out)
+    Output
+      # Test for Practical Equivalence
+      
+      Parameter   |        H0 | inside ROPE |        95% HDI |          ROPE
+      ----------------------------------------------------------------------
+      (Intercept) | Undecided |     15.82 % | [-2.68, -0.50] | [-1.00, 1.00]
+      size        |  Accepted |    100.00 % |  [-0.04, 0.07] | [-0.10, 0.10]
+      period2     |  Rejected |      0.00 % | [-1.61, -0.36] |  [0.00, 2.00]
+      period3     |  Accepted |    100.00 % | [-1.77, -0.40] | [-2.00, 0.00]
+      period4     |  Rejected |      0.00 % | [-2.52, -0.76] | [-0.10, 0.10]
+      
+      
+
+# equivalence test, df
+
+    Code
+      print(out)
+    Output
+      # Test for Practical Equivalence
+      
+        ROPE: [-0.10 0.10]
+      
+      Parameter   |       H0 | inside ROPE |        95% HDI
+      -----------------------------------------------------
+      (Intercept) | Rejected |      0.00 % | [-2.68, -0.50]
+      size        | Accepted |    100.00 % |  [-0.04, 0.07]
+      period2     | Rejected |      0.00 % | [-1.61, -0.36]
+      period3     | Rejected |      0.00 % | [-1.77, -0.40]
+      period4     | Rejected |      0.00 % | [-2.52, -0.76]
+      
+      
+
+---
+
+    Code
+      print(out)
+    Output
+      # Test for Practical Equivalence
+      
+      Parameter   |        H0 | inside ROPE |        95% HDI |          ROPE
+      ----------------------------------------------------------------------
+      (Intercept) | Undecided |     15.82 % | [-2.68, -0.50] | [-1.00, 1.00]
+      size        |  Accepted |    100.00 % |  [-0.04, 0.07] | [-0.10, 0.10]
+      period2     |  Rejected |      0.00 % | [-1.61, -0.36] |  [0.00, 2.00]
+      period3     |  Accepted |    100.00 % | [-1.77, -0.40] | [-2.00, 0.00]
+      period4     |  Rejected |      0.00 % | [-2.52, -0.76] | [-0.10, 0.10]
+      
+      
+
diff --git a/tests/testthat/test-bayesian_as_frequentist.R b/tests/testthat/test-bayesian_as_frequentist.R
index 8066f3483..0fafdbcb9 100644
--- a/tests/testthat/test-bayesian_as_frequentist.R
+++ b/tests/testthat/test-bayesian_as_frequentist.R
@@ -34,7 +34,7 @@ test_that("brms beta to freq", {
   skip_if_not_or_load_if_installed("betareg")
 
   set.seed(333)
-  m <- insight::download_model("brms_beta_1")
+  m <- suppressWarnings(insight::download_model("brms_beta_1"))
   data(FoodExpenditure, package = "betareg")
   m1 <- glmmTMB::glmmTMB(
     I(food / income) ~ income + (1 | persons),
@@ -56,7 +56,7 @@ test_that("ordbetareg to freq", {
 
   set.seed(333)
   data(sleepstudy, package = "lme4")
-  m <- insight::download_model("ordbetareg_1")
+  m <- suppressWarnings(insight::download_model("ordbetareg_1"))
   sleepstudy$y <- datawizard::normalize(sleepstudy$Reaction)
   m1 <- glmmTMB::glmmTMB(
     y ~ Days + (Days | Subject),
diff --git a/tests/testthat/test-describe_posterior.R b/tests/testthat/test-describe_posterior.R
index f21a10787..db265a679 100644
--- a/tests/testthat/test-describe_posterior.R
+++ b/tests/testthat/test-describe_posterior.R
@@ -146,6 +146,20 @@ test_that("describe_posterior", {
   )
   expect_identical(dim(rez), c(4L, 21L))
 
+  # allow multiple ropes
+  rez <- describe_posterior(x, rope_range = list(c(-1, 1), "default"))
+  expect_identical(rez$ROPE_low, c(-1, -0.1), tolerance = 1e-3)
+  expect_identical(rez$ROPE_high, c(1, 0.1), tolerance = 1e-3)
+
+  expect_error(
+    describe_posterior(x, rope_range = list(1, "default")),
+    regex = "should be 'default'"
+  )
+  expect_error(
+    describe_posterior(x, rope_range = list(c(1, 1), c(2, 2), c(2, 3))),
+    regex = "Length of"
+  )
+
   rez <- describe_posterior(
     x,
     centrality = NULL,
diff --git a/tests/testthat/test-equivalence_test.R b/tests/testthat/test-equivalence_test.R
new file mode 100644
index 000000000..e7ce74cac
--- /dev/null
+++ b/tests/testthat/test-equivalence_test.R
@@ -0,0 +1,69 @@
+skip_on_cran()
+
+test_that("equivalence test, rstanarm", {
+  skip_if_offline()
+  skip_if_not_or_load_if_installed("rstanarm")
+  m <- insight::download_model("stanreg_merMod_5")
+
+  out <- equivalence_test(m, verbose = FALSE)
+  expect_snapshot(print(out))
+
+  out <- equivalence_test(
+    m,
+    range = list(c(-1, 1), "default", c(0, 2), c(-2, 0), "default"),
+    verbose = FALSE
+  )
+  expect_snapshot(print(out))
+
+  expect_error(
+    equivalence_test(
+      m,
+      range = list(c(-1, 1), "default", c(0, 2), c(-2, 0)),
+      verbose = FALSE
+    ),
+    regex = "Length of"
+  )
+  expect_error(
+    equivalence_test(
+      m,
+      range = list(c(-1, 1), "default", c(0, 2), c(-2, 0), "a"),
+      verbose = FALSE
+    ),
+    regex = "should be 'default'"
+  )
+})
+
+
+test_that("equivalence test, df", {
+  skip_if_offline()
+  skip_if_not_or_load_if_installed("rstanarm")
+  m <- insight::download_model("stanreg_merMod_5")
+  params <- as.data.frame(m)[1:5]
+
+  out <- equivalence_test(params, verbose = FALSE)
+  expect_snapshot(print(out))
+
+  out <- equivalence_test(
+    params,
+    range = list(c(-1, 1), "default", c(0, 2), c(-2, 0), "default"),
+    verbose = FALSE
+  )
+  expect_snapshot(print(out))
+
+  expect_error(
+    equivalence_test(
+      params,
+      range = list(c(-1, 1), "default", c(0, 2), c(-2, 0)),
+      verbose = FALSE
+    ),
+    regex = "Length of"
+  )
+  expect_error(
+    equivalence_test(
+      params,
+      range = list(c(-1, 1), "default", c(0, 2), c(-2, 0), "a"),
+      verbose = FALSE
+    ),
+    regex = "should be 'default'"
+  )
+})
diff --git a/tests/testthat/test-p_rope.R b/tests/testthat/test-p_rope.R
new file mode 100644
index 000000000..854722b76
--- /dev/null
+++ b/tests/testthat/test-p_rope.R
@@ -0,0 +1,19 @@
+test_that("p_rope", {
+  skip_if_offline()
+  skip_if_not_or_load_if_installed("rstanarm")
+  m <- insight::download_model("stanreg_merMod_5")
+  expect_equal(
+    p_rope(as.data.frame(m)[2:4], range = list(c(0, 40), "default", c(-1, 0.8)))$p_ROPE,
+    c(0.598, 0.002, 0.396),
+    tolerance = 1e-3
+  )
+
+  expect_error(
+    p_rope(as.data.frame(m)[2:4], range = list(c(0, 40), c(-1, 0.8))),
+    regex = "Length of"
+  )
+  expect_error(
+    p_rope(as.data.frame(m)[2:4], range = list(c(0, 40), "a", c(-1, 0.8))),
+    regex = "should be 'default'"
+  )
+})
diff --git a/tests/testthat/test-p_significance.R b/tests/testthat/test-p_significance.R
index 6f542f3c0..d11ecbb25 100644
--- a/tests/testthat/test-p_significance.R
+++ b/tests/testthat/test-p_significance.R
@@ -37,7 +37,6 @@ test_that("p_significance", {
 test_that("stanreg", {
   skip_if_offline()
   skip_if_not_or_load_if_installed("rstanarm")
-
   m <- insight::download_model("stanreg_merMod_5")
 
   expect_equal(
@@ -49,7 +48,7 @@ test_that("stanreg", {
 
 test_that("brms", {
   skip_if_offline()
-  skip_if_not_or_load_if_installed("rstanarm")
+  skip_if_not_or_load_if_installed("brms")
 
   m2 <- insight::download_model("brms_1")
 
@@ -58,4 +57,50 @@ test_that("brms", {
     c(1.0000, 0.9985, 0.9785),
     tolerance = 0.01
   )
+
+  out <- p_significance(m2, threshold = list(1, "default", 2), effects = "all")
+  expect_equal(
+    out$ps,
+    c(1.00000, 0.99850, 0.12275),
+    tolerance = 0.01
+  )
+  expect_equal(
+    attributes(out)$threshold,
+    list(c(-1, 1), c(-0.60269480520891, 0.60269480520891), c(-2, 2)),
+    tolerance = 1e-4
+  )
+
+  expect_error(
+    p_significance(m2, threshold = list(1, "a", 2), effects = "all"),
+    regex = "should be one of"
+  )
+  expect_error(
+    p_significance(m2, threshold = list(1, 2, 3, 4), effects = "all"),
+    regex = "Length of"
+  )
+})
+
+test_that("stan", {
+  skip_if_offline()
+  skip_if_not_or_load_if_installed("rstanarm")
+  m <- insight::download_model("stanreg_merMod_5")
+
+  expect_equal(
+    p_significance(m, threshold = list("(Intercept)" = 1, period4 = 1.5, period3 = 0.5))$ps,
+    p_significance(m, threshold = list(1, "default", "default", 0.5, 1.5))$ps,
+    tolerance = 1e-4
+  )
+
+  expect_error(
+    p_significance(m, threshold = list("(Intercept)" = 1, point = 1.5, period3 = 0.5)),
+    regex = "Not all elements"
+  )
+  expect_error(
+    p_significance(m, threshold = list(1, "a", 2), effects = "all"),
+    regex = "should be one of"
+  )
+  expect_error(
+    p_significance(m, threshold = list(1, 2, 3, 4), effects = "all"),
+    regex = "Length of"
+  )
 })
diff --git a/tests/testthat/test-rope.R b/tests/testthat/test-rope.R
index 8367e3d80..0c9059854 100644
--- a/tests/testthat/test-rope.R
+++ b/tests/testthat/test-rope.R
@@ -49,6 +49,33 @@ test_that("rope", {
     rope(p, verbose = FALSE)$ROPE_Percentage,
     tolerance = 1e-3
   )
+
+  # list range
+  expect_equal(
+    rope(m, range = list(c(-1, 0.1), "default", "default", c(-1, 1), c(-1.5, -1)))$ROPE_Percentage,
+    c(0.15823, 1, 0, 0.3903, 0.38186),
+    tolerance = 1e-3
+  )
+
+  # named elements, chooses "default" for unnamed
+  expect_equal(
+    rope(m, range = list(c(-1, 0.1), "default", "default", c(-1, 1), c(-1.5, -1)))$ROPE_Percentage,
+    rope(m, range = list("(Intercept)" = c(-1, 0.1), period4 = c(-1.5, -1), period3 = c(-1, 1)))$ROPE_Percentage,
+    tolerance = 1e-3
+  )
+
+  expect_error(
+    rope(m, range = list(c(-0.1, 0.1), c(2, 2))),
+    regex = "Length of"
+  )
+  expect_error(
+    rope(m, range = list(c(-0.1, 0.1), c(2, 2), "default", "a", c(1, 3))),
+    regex = "should be 'default'"
+  )
+  expect_error(
+    rope(m, range = list("(Intercept)" = c(-1, 0.1), pointout = c(-1.5, -1), period3 = c(-1, 1))),
+    regex = "Not all elements"
+  )
 })