0.1.1.77: Improve printout of sim_data

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: power4mome
 Title: Power Analysis for Moderation and Mediation
-Version: 0.1.1.75
+Version: 0.1.1.77
 Authors@R:
     c(person(given = "Shu Fai",
            family = "Cheung",

NEWS.md

@@ -1,4 +1,4 @@
-# power4mome 0.1.1.75
+# power4mome 0.1.1.77
 
 - Improve the function for extending the
   initial interval before doing a
@@ -448,6 +448,19 @@
   `mode` of `q_power_mediation()`
   and friends. (0.1.1.75)
 
+- If the model is a multigroup model,
+  descriptive statistics for the
+  generated data are printed by
+  group, using `psych::describeBy()`.
+  (0.1.1.76)
+
+- Response proportions will be printed
+  with `data_long = TRUE` if a variable
+  has 10 or fewer unique values
+  (e.g., ordinal variables),
+  using `psych::responseFrequency()`.
+  (0.1.1.77)
+
 # power4mome 0.1.1
 
 - Updated to be compatible with the

R/sim_data.R

@@ -901,11 +901,52 @@ print.sim_data <- function(x,
                   hw = .4,
                   prefix = "\n",
                   suffix = "\n\n"))
+    if (ngroups > 1) {
+      tmp <- which(colnames(all_data) == x_i$group_name)
+      print(psych::describeBy(
+                            all_data[, -tmp],
+                            group = all_data[[x_i$group_name]],
+                            range = FALSE),
+            digits = digits_descriptive)
+    } else {
+      print(psych::describe(all_data,
+                            range = FALSE),
+            digits = digits_descriptive)
+    }
 
-    print(psych::describe(all_data,
-                          range = FALSE),
-          digits = digits_descriptive)
+    # ==== Response Frequencies ====
+
+    response_count <- sapply(
+                        all_data[seq_len(n * nrep), ],
+                        \(x) length(unique(x))
+                      )
+    tmp1 <- response_count <= 10
+    if (!is.null(x_i$group_name)) {
+      tmp1[x_i$group_name] <- FALSE
+    }
 
+    if (any(tmp1)) {
+      cat(header_str("Response Proportions",
+                    hw = .4,
+                    prefix = "\n",
+                    suffix = "\n"))
+      tmp2 <- unique(response_count[tmp1])
+      if (ngroups > 1) {
+        group <- all_data[[x_i$group_name]]
+      } else {
+        group <- rep("Single Group", nrow(all_data))
+      }
+      for (zz in tmp2) {
+        tmp3 <- (response_count == zz)
+        tmp5 <- by(all_data[, tmp3, drop = FALSE],
+                   INDICES = group,
+                   psych::responseFrequency,
+                   simplify = FALSE)
+        cat("\n")
+        print(tmp5,
+              digits = digits_descriptive)
+      }
+    }
     # Print missing data pattern
 
     mp <- tryCatch(miss_pattern(all_data),

README.md

@@ -8,7 +8,7 @@
 [![R-CMD-check](https://github.com/sfcheung/power4mome/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/sfcheung/power4mome/actions/workflows/R-CMD-check.yaml)
 <!-- badges: end -->
 
-(Version 0.1.1.75, updated on 2026-03-15, [release history](https://sfcheung.github.io/power4mome/news/index.html))
+(Version 0.1.1.77, updated on 2026-03-17, [release history](https://sfcheung.github.io/power4mome/news/index.html))
 
 # power4mome <a href="https://sfcheung.github.io/power4mome/"><img src="man/figures/logo.png" align="right" height="120" alt="power4mome website" /></a>
 

tests/testthat/test-ordinal.R

@@ -41,6 +41,9 @@ sim_only1 <- power4test(
                   parallel = FALSE,
                   iseed = 1234)
 
+expect_output(print(sim_only1, data_long = TRUE),
+              " Response Proportions ")
+
 tmp <- pool_sim_data(sim_only1)
 
 expect_equal(length(table(tmp$m1)), 4)

tests/testthat/test-sim_data_print_mg_des.R

@@ -0,0 +1,33 @@
+library(testthat)
+suppressMessages(library(lavaan))
+
+test_that("sim_out: descriptive for multigroup model", {
+
+mod <-
+"
+m ~ x
+y ~ m + x
+"
+
+es <-
+"
+y ~ m: l
+m ~ x:
+  - nil
+  - s
+y ~ x: nil
+"
+
+data_all <- sim_data(nrep = 2,
+                     model = mod,
+                     pop_es = es,
+                     n = 100,
+                     progress = !is_testing(),
+                     iseed = 1234)
+
+expect_output(print(data_all),
+              "Descriptive statistics by group",
+              fixed = TRUE)
+
+
+})

vignettes/articles/n_from_power_mediation_ordinal_lav_simple.Rmd

@@ -1,6 +1,6 @@
 ---
 title: "Sample Size Determination with Ordinal Variables: Latent Variable Models"
-date: "2026-03-16"
+date: "2026-03-17"
 output:
   html_document:
     fig.align: "center"
@@ -263,6 +263,31 @@ to linear transformation of the variables,
 which is usually the case for most common
 tests.
 
+If there are variables with 10 or few
+unique values, the response proportions
+are also printed:
+
+
+```
+#> ===== Response Proportions =====
+#> 
+#> group: Single Group
+#>      1   2 miss
+#> x1 0.5 0.5    0
+#> x2 0.5 0.5    0
+#> x3 0.5 0.5    0
+#> x4 0.5 0.5    0
+#> y1 0.5 0.5    0
+#> y2 0.5 0.5    0
+#> y3 0.5 0.5    0
+#> 
+#> group: Single Group
+#>        1    2    3    4     5 miss
+#> m1 0.067 0.24 0.38 0.24 0.068    0
+#> m2 0.067 0.24 0.38 0.24 0.066    0
+#> m3 0.068 0.24 0.38 0.24 0.067    0
+```
+
 If necessary, the data generated can be
 retrieved by `pool_sim_data()` and
 inspected directly:

vignettes/articles/n_from_power_mediation_ordinal_lav_simple.Rmd.original

@@ -295,6 +295,16 @@ to linear transformation of the variables,
 which is usually the case for most common
 tests.
 
+If there are variables with 10 or few
+unique values, the response proportions
+are also printed:
+
+```{r des2, echo=FALSE}
+i1 <- which(grepl("= Response Proportions =", tmp))
+i2 <- which(grepl("==== Parameter Estimates ", tmp))
+cat(tmp[i1:(i2 - 1)], sep = "\n")
+```
+
 If necessary, the data generated can be
 retrieved by `pool_sim_data()` and
 inspected directly: