diff --git a/book/graphs/other/cig01.qmd b/book/graphs/other/cig01.qmd
index 9972adaaeb..9f10d694a4 100644
--- a/book/graphs/other/cig01.qmd
+++ b/book/graphs/other/cig01.qmd
@@ -154,7 +154,7 @@ The corresponding table is simply obtained using the `rtables` framework:
 ```{r table6, test = list(table_v6 = "table")}
 lyt <- basic_table() %>%
   split_cols_by(var = "ARMCD") %>%
-  summarize_vars(vars = "AVAL", .stats = c("mean_sd", "median"))
+  analyze_vars(vars = "AVAL", .stats = c("mean_sd", "median"))
 table <- build_table(lyt = lyt, df = adlb)
 table
 ```
diff --git a/book/graphs/other/mng01.qmd b/book/graphs/other/mng01.qmd
index 0ccf7949ed..c9e992930d 100644
--- a/book/graphs/other/mng01.qmd
+++ b/book/graphs/other/mng01.qmd
@@ -94,7 +94,7 @@ plot
 plot <- g_lineplot(
   df = adlb_f,
   alt_counts_df = adsl_f,
-  control = control_summarize_vars(conf_level = 0.80),
+  control = control_analyze_vars(conf_level = 0.80),
   title = "Plot of Mean and 80% Confidence Limits by Visit",
   subtitle = "Laboratory Test:"
 )
diff --git a/book/tables/adverse-events/aet04_pi.qmd b/book/tables/adverse-events/aet04_pi.qmd
index 8440a8ab34..f778233670 100644
--- a/book/tables/adverse-events/aet04_pi.qmd
+++ b/book/tables/adverse-events/aet04_pi.qmd
@@ -52,7 +52,7 @@ full_table_aet04_pi <- function(adsl, adae_max) {
       .stats = "unique",
       .labels = "Total number of patients with at least one adverse event"
     ) %>%
-    summarize_vars(
+    analyze_vars(
       "AEDECOD",
       na.rm = FALSE,
       denom = "N_col",
@@ -241,7 +241,7 @@ full_table <- basic_table() %>%
     .stats = "unique",
     .labels = "Total number of patients with at least one adverse event"
   ) %>%
-  summarize_vars(
+  analyze_vars(
     "AEDECOD",
     na.rm = FALSE,
     denom = "N_col",
@@ -298,7 +298,7 @@ full_table <- basic_table() %>%
     .stats = "unique",
     .labels = "Total number of patients with at least one adverse event"
   ) %>%
-  summarize_vars(
+  analyze_vars(
     "AEDECOD",
     na.rm = FALSE,
     denom = "N_col",
@@ -345,7 +345,7 @@ col_counts <- rep(table(adsl$ACTARM), each = length(grade_groups))
 full_table <- basic_table() %>%
   split_cols_by("ACTARM") %>%
   split_cols_by_groups("MAXAETOXGR", groups = grade_groups) %>%
-  summarize_vars(
+  analyze_vars(
     "AEDECOD",
     na.rm = FALSE,
     denom = "N_col",
diff --git a/book/tables/efficacy/dort01.qmd b/book/tables/efficacy/dort01.qmd
index 65dc230f2b..c255568d12 100644
--- a/book/tables/efficacy/dort01.qmd
+++ b/book/tables/efficacy/dort01.qmd
@@ -52,7 +52,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     .labels = "Responders",
     .stats = "count"
   ) %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Responders with subsequent event (%)"),
@@ -68,7 +68,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     indent_mod = 2L,
   ) %>%
   analyze("EVNTDESC") %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_not_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Responders without subsequent event (%)"),
@@ -105,7 +105,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     .labels = "Responders",
     .stats = "count"
   ) %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Responders with subsequent event (%)"),
@@ -121,7 +121,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     indent_mod = 2L,
   ) %>%
   analyze("EVNTDESC") %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_not_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Responders without subsequent event (%)"),
@@ -160,7 +160,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     .labels = "Responders",
     .stats = "count"
   ) %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Responders with subsequent event (%)"),
@@ -176,7 +176,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     indent_mod = 2L,
   ) %>%
   analyze("EVNTDESC") %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_not_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Responders without subsequent event (%)"),
@@ -215,7 +215,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     .labels = "Responders",
     .stats = "count"
   ) %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Responders with subsequent event (%)"),
@@ -231,7 +231,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     indent_mod = 2L,
   ) %>%
   analyze("EVNTDESC") %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_not_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Responders without subsequent event (%)"),
diff --git a/book/tables/efficacy/mmrmt01.qmd b/book/tables/efficacy/mmrmt01.qmd
index c14cb10002..17754c628d 100644
--- a/book/tables/efficacy/mmrmt01.qmd
+++ b/book/tables/efficacy/mmrmt01.qmd
@@ -128,7 +128,7 @@ baseline_dat <- adqs %>%
 b <- basic_table(show_colcounts = TRUE) %>%
   split_cols_by("ARMCD") %>%
   split_rows_by("AVISIT") %>%
-  summarize_vars("AVAL") %>%
+  analyze_vars("AVAL") %>%
   append_topleft("  Statistics") %>%
   build_table(baseline_dat, alt_counts_df = adsl_sub)
 
diff --git a/book/tables/efficacy/ttet01.qmd b/book/tables/efficacy/ttet01.qmd
index 4b8a29e5df..6ad7d13fd6 100644
--- a/book/tables/efficacy/ttet01.qmd
+++ b/book/tables/efficacy/ttet01.qmd
@@ -48,7 +48,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
   split_cols_by(
     var = "ARM", ref_group = "A: Drug X"
   ) %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Patients with event (%)")
@@ -62,7 +62,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     indent_mod = 1L,
   ) %>%
   analyze("EVNTDESC") %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_not_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Patients without event (%)"),
@@ -102,12 +102,12 @@ result
 ```{r variant2, test = list(result_v2 = "result")}
 lyt <- basic_table(show_colcounts = TRUE) %>%
   split_cols_by("ARM", ref_group = "A: Drug X") %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Patients with event (%)")
   ) %>%
-  summarize_vars(
+  analyze_vars(
     "is_not_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Patients without event (%)"),
@@ -144,7 +144,7 @@ result
 ```{r variant3, test = list(result_v3 = "result")}
 lyt <- basic_table(show_colcounts = TRUE) %>%
   split_cols_by("ARM", ref_group = "A: Drug X") %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Patients with event (%)")
@@ -158,7 +158,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     indent_mod = 1L,
   ) %>%
   analyze("EVNTDESC") %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_not_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Patients without event (%)"),
@@ -212,7 +212,7 @@ result
 ```{r variant4, test = list(result_v4 = "result")}
 lyt <- basic_table(show_colcounts = TRUE) %>%
   split_cols_by("ARM", ref_group = "A: Drug X") %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Patients with event (%)")
@@ -226,7 +226,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     indent_mod = 1L,
   ) %>%
   analyze("EVNTDESC") %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_not_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Patients without event (%)"),
@@ -271,7 +271,7 @@ result
 ```{r variant5, test = list(result_v5 = "result")}
 lyt <- basic_table(show_colcounts = TRUE) %>%
   split_cols_by("ARM", ref_group = "A: Drug X") %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Patients with event (%)")
@@ -285,7 +285,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     indent_mod = 1L,
   ) %>%
   analyze("EVNTDESC") %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_not_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Patients without event (%)"),
@@ -324,7 +324,7 @@ result
 ```{r variant6, test = list(result_v6 = "result")}
 lyt <- basic_table(show_colcounts = TRUE) %>%
   split_cols_by("ARM", ref_group = "A: Drug X") %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Patients with event (%)")
@@ -338,7 +338,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     indent_mod = 1L,
   ) %>%
   analyze("EVNTDESC") %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_not_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Patients without event (%)"),
diff --git a/book/tables/lab-results/lbt02.qmd b/book/tables/lab-results/lbt02.qmd
index 5377c976dd..12db94f8f5 100644
--- a/book/tables/lab-results/lbt02.qmd
+++ b/book/tables/lab-results/lbt02.qmd
@@ -49,7 +49,7 @@ l <- basic_table(show_colcounts = TRUE) %>%
     label_pos = "topleft",
     split_label = obj_label(adlb$AVISIT)
   ) %>%
-  summarize_vars(vars = "AVAL")
+  analyze_vars(vars = "AVAL")
 
 result <- build_table(l,
   df = adlb,
diff --git a/book/tables/other/disclosurest01.qmd b/book/tables/other/disclosurest01.qmd
index aaab140fd6..aa095a6804 100644
--- a/book/tables/other/disclosurest01.qmd
+++ b/book/tables/other/disclosurest01.qmd
@@ -113,7 +113,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     split_fun = split_fun
   ) %>%
   summarize_row_groups(label_fstr = "Discontinued Study") %>%
-  summarize_vars(
+  analyze_vars(
     "STDDRS",
     .stats = "count_fraction"
   ) %>%
@@ -166,7 +166,7 @@ var_labels <- c("Age (yr)", "Age group", "Sex", "Race", "Ethnicity")
 lyt <- basic_table(show_colcounts = TRUE) %>%
   split_cols_by(var = "ARM") %>%
   add_overall_col("All Patients") %>%
-  summarize_vars(
+  analyze_vars(
     vars = vars,
     var_labels = var_labels
   )
@@ -203,7 +203,7 @@ var_labels(adsl) <- c(adsl_labels)
 lyt <- basic_table(show_colcounts = TRUE) %>%
   split_cols_by("ARM") %>%
   add_overall_col(label = "All Patients") %>%
-  summarize_vars("COUNTRY") %>%
+  analyze_vars("COUNTRY") %>%
   append_varlabels(adsl, "COUNTRY")
 
 result <- build_table(lyt, adsl)
diff --git a/book/tables/other/ratet01.qmd b/book/tables/other/ratet01.qmd
index 74c8407f4e..5178754a52 100644
--- a/book/tables/other/ratet01.qmd
+++ b/book/tables/other/ratet01.qmd
@@ -33,7 +33,7 @@ anl <- df_explicit_na(anl)
 ```{r variant1, test = list(result_v1 = "result")}
 lyt <- basic_table(show_colcounts = TRUE) %>%
   split_cols_by("ARM", ref_group = "B: Placebo") %>%
-  summarize_vars(
+  analyze_vars(
     "AVAL_f",
     var_labels = "Number of exacerbations per patient",
     .stats = c("count_fraction"),
diff --git a/book/tables/pharmacokinetic/adat02.qmd b/book/tables/pharmacokinetic/adat02.qmd
index d578797766..630e8e817e 100644
--- a/book/tables/pharmacokinetic/adat02.qmd
+++ b/book/tables/pharmacokinetic/adat02.qmd
@@ -93,13 +93,13 @@ lyt_adab_ti <- basic_table(show_colcounts = TRUE) %>%
     var_labels = "Treatment-induced ADA patients with",
     show_labels = "visible"
   ) %>%
-  summarize_vars(
+  analyze_vars(
     "Time to onset of ADA",
     .stats = "median",
     nested = FALSE,
     .labels = c(median = "Median time to onset of ADA (weeks)")
   ) %>%
-  summarize_vars(
+  analyze_vars(
     "Antibody titer units",
     .stats = "range",
     nested = FALSE,
diff --git a/book/tables/pharmacokinetic/pkpt02.qmd b/book/tables/pharmacokinetic/pkpt02.qmd
index cfb7b2dee4..f6133c7a9b 100644
--- a/book/tables/pharmacokinetic/pkpt02.qmd
+++ b/book/tables/pharmacokinetic/pkpt02.qmd
@@ -37,7 +37,7 @@ lyt <- basic_table() %>%
     label_pos = "topleft",
     split_label = "PK Parameter"
   ) %>%
-  tern::summarize_vars(
+  tern::analyze_vars(
     vars = "AVAL",
     .stats = c("n", "mean_sd", "cv", "geom_mean", "geom_cv", "median", "range"),
     .formats = c(
diff --git a/book/tables/pharmacokinetic/pkpt04.qmd b/book/tables/pharmacokinetic/pkpt04.qmd
index d1dc5f6d5d..3784d605f2 100644
--- a/book/tables/pharmacokinetic/pkpt04.qmd
+++ b/book/tables/pharmacokinetic/pkpt04.qmd
@@ -37,7 +37,7 @@ lyt <- basic_table() %>%
     label_pos = "topleft",
     split_label = "PK Parameter"
   ) %>%
-  tern::summarize_vars(
+  tern::analyze_vars(
     vars = "AVAL",
     .stats = c("n", "mean_sd", "cv", "geom_mean", "geom_cv", "median", "range"),
     .formats = c(
diff --git a/book/tables/pharmacokinetic/pkpt06.qmd b/book/tables/pharmacokinetic/pkpt06.qmd
index c72fc0dc3f..e5be398acb 100644
--- a/book/tables/pharmacokinetic/pkpt06.qmd
+++ b/book/tables/pharmacokinetic/pkpt06.qmd
@@ -38,7 +38,7 @@ lyt <- basic_table() %>%
     label_pos = "topleft",
     split_label = "PK Parameter"
   ) %>%
-  tern::summarize_vars(
+  tern::analyze_vars(
     vars = "AVAL",
     .stats = c("n", "mean_sd", "cv", "geom_mean", "geom_cv", "median", "range"),
     .formats = c(
diff --git a/book/tables/pharmacokinetic/pkpt08.qmd b/book/tables/pharmacokinetic/pkpt08.qmd
index fa85e14e00..cdc9b07478 100644
--- a/book/tables/pharmacokinetic/pkpt08.qmd
+++ b/book/tables/pharmacokinetic/pkpt08.qmd
@@ -38,7 +38,7 @@ lyt <- basic_table() %>%
     label_pos = "topleft",
     split_label = "Treatment Arm"
   ) %>%
-  summarize_vars(
+  analyze_vars(
     vars = "AVAL",
     .stats = c(
       "n", "mean", "sd", "cv",
diff --git a/book/tables/safety/dmt01.qmd b/book/tables/safety/dmt01.qmd
index f2c4cf2859..d44696422e 100644
--- a/book/tables/safety/dmt01.qmd
+++ b/book/tables/safety/dmt01.qmd
@@ -101,7 +101,7 @@ var_labels <- c(
 result <- basic_table(show_colcounts = TRUE) %>%
   split_cols_by(var = "ACTARM") %>%
   add_overall_col("All Patients") %>%
-  summarize_vars(
+  analyze_vars(
     vars = vars,
     var_labels = var_labels
   ) %>%
@@ -125,7 +125,7 @@ var_labels <- c(
 
 result <- basic_table(show_colcounts = TRUE) %>%
   split_cols_by(var = "ACTARM") %>%
-  summarize_vars(
+  analyze_vars(
     vars = vars,
     var_labels = var_labels
   ) %>%
@@ -141,14 +141,14 @@ split_fun <- drop_split_levels
 
 result <- basic_table(show_colcounts = TRUE) %>%
   split_cols_by(var = "ACTARM") %>%
-  summarize_vars(
+  analyze_vars(
     vars = c("AGE", "SEX", "RACE"),
     var_labels = c("Age", "Sex", "Race")
   ) %>%
   split_rows_by("STRATA1",
     split_fun = split_fun
   ) %>%
-  summarize_vars("BMRKR1") %>%
+  analyze_vars("BMRKR1") %>%
   build_table(adsl)
 
 result
@@ -159,7 +159,7 @@ result
 ```{r variant4, test = list(result_v4 = "result")}
 result <- basic_table(show_colcounts = TRUE) %>%
   split_cols_by(var = "ACTARM") %>%
-  summarize_vars(
+  analyze_vars(
     vars = c("AGE", "SEX", "RACE", "DBP", "SBP"),
     var_labels = c(
       "Age (yr)",
@@ -179,7 +179,7 @@ result
 ```{r variant5, test = list(result_v5 = "result")}
 result <- basic_table(show_colcounts = TRUE) %>%
   split_cols_by(var = "ACTARM") %>%
-  summarize_vars(
+  analyze_vars(
     vars = c("AGE", "SEX", "RACE", "BBMISI"),
     var_labels = c(
       "Age (yr)",
diff --git a/book/tables/safety/dst01.qmd b/book/tables/safety/dst01.qmd
index cde31a8a83..3a5beb6b77 100644
--- a/book/tables/safety/dst01.qmd
+++ b/book/tables/safety/dst01.qmd
@@ -54,7 +54,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     .stats = "count_fraction",
     show_labels = "hidden"
   ) %>%
-  summarize_vars(
+  analyze_vars(
     "DCSREAS",
     .stats = "count_fraction",
     denom = "N_col",
@@ -80,7 +80,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     show_labels = "hidden"
   ) %>%
   split_rows_by("DCSREASGP", indent_mod = 1L) %>%
-  summarize_vars(
+  analyze_vars(
     "DCSREAS",
     .stats = "count_fraction",
     denom = "N_col",
diff --git a/book/tables/safety/dtht01.qmd b/book/tables/safety/dtht01.qmd
index 30cd1f84e5..ef55337fa2 100644
--- a/book/tables/safety/dtht01.qmd
+++ b/book/tables/safety/dtht01.qmd
@@ -37,7 +37,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     .labels = c(count_fraction = "Total number of deaths"),
     .formats = c(count_fraction = "xx (xx.x%)")
   ) %>%
-  summarize_vars(vars = c("DTHCAT"), var_labels = c("Primary Cause of Death"))
+  analyze_vars(vars = c("DTHCAT"), var_labels = c("Primary Cause of Death"))
 
 result <- build_table(lyt, df = adsl)
 result
@@ -54,15 +54,15 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     .labels = c(count_fraction = "Total number of deaths"),
     .formats = c(count_fraction = "xx (xx.x%)")
   ) %>%
-  summarize_vars(vars = c("DTHCAT"), var_labels = c("Primary Cause of Death")) %>%
+  analyze_vars(vars = c("DTHCAT"), var_labels = c("Primary Cause of Death")) %>%
   split_rows_by("DTHCAT", split_fun = keep_split_levels("OTHER"), child_labels = "hidden") %>%
-  summarize_vars(
+  analyze_vars(
     "DTHCAUS",
     .stats = "count_fraction",
     .indent_mods = c("count_fraction" = 2L),
     show_labels = "hidden"
   ) %>%
-  summarize_vars(
+  analyze_vars(
     vars = "LDDTHGR1",
     nested = FALSE,
     var_labels = "Days from last drug administration",
@@ -74,7 +74,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     split_label = "Primary cause by days from last study drug administration",
     label_pos = "visible"
   ) %>%
-  summarize_vars("DTHCAT")
+  analyze_vars("DTHCAT")
 
 result <- build_table(lyt, df = adsl) %>% prune_table()
 
@@ -94,7 +94,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     .labels = c(count_fraction = "Total number of deaths"),
     .formats = c(count_fraction = "xx (xx.x%)")
   ) %>%
-  summarize_vars(
+  analyze_vars(
     vars = c("DTHCAT"),
     var_labels = c("Primary Cause of Death"),
     table_names = "primary_cause"
@@ -147,7 +147,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     .labels = c(count_fraction = "Total number of deaths"),
     .formats = c(count_fraction = "xx (xx.x%)")
   ) %>%
-  summarize_vars(
+  analyze_vars(
     vars = c("DTHCAT"),
     var_labels = c("Primary Cause of Death"),
     table_names = "primary_cause"
@@ -169,7 +169,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     .indent_mods = c(count_fraction = 2L),
     table_names = "all_other_causes"
   ) %>%
-  summarize_vars(
+  analyze_vars(
     "DTHCAUS_other",
     .stats = "count_fraction",
     .indent_mods = c("count_fraction" = 3L),
diff --git a/book/tables/safety/egt03.qmd b/book/tables/safety/egt03.qmd
index 587e7b7e83..6d335eb12e 100644
--- a/book/tables/safety/egt03.qmd
+++ b/book/tables/safety/egt03.qmd
@@ -80,7 +80,7 @@ lyt <- basic_table() %>%
   split_cols_by("ANRIND") %>%
   split_rows_by("ARMCD", split_fun = split_fun, label_pos = "topleft", split_label = obj_label(adeg_f_pbmin$ARMCD)) %>%
   add_rowcounts() %>%
-  summarize_vars("BNRIND", denom = "N_row", .stats = "count_fraction") %>%
+  analyze_vars("BNRIND", denom = "N_row", .stats = "count_fraction") %>%
   append_varlabels(adeg_f_pbmin, c("BNRIND"), indent = 1L)
 
 result <- build_table(
@@ -127,7 +127,7 @@ lyt <- basic_table() %>%
   split_cols_by("ANRIND") %>%
   split_rows_by("ARMCD", split_fun = split_fun, label_pos = "topleft", split_label = obj_label(adeg_f_pbmax$ARMCD)) %>%
   add_rowcounts() %>%
-  summarize_vars("BNRIND", denom = "N_row", .stats = "count_fraction") %>%
+  analyze_vars("BNRIND", denom = "N_row", .stats = "count_fraction") %>%
   append_varlabels(adeg_f_pbmax, c("BNRIND"), indent = 1L)
 
 result <- build_table(
diff --git a/book/tables/safety/egt04.qmd b/book/tables/safety/egt04.qmd
index e317ab3cbf..fb960b9b2a 100644
--- a/book/tables/safety/egt04.qmd
+++ b/book/tables/safety/egt04.qmd
@@ -73,7 +73,7 @@ lyt <- basic_table() %>%
   split_cols_by("AVALC") %>%
   split_rows_by("ARM", split_fun = split_fun, label_pos = "topleft", split_label = obj_label(adeg_f$ARM)) %>%
   add_rowcounts() %>%
-  summarize_vars(
+  analyze_vars(
     "BASEC",
     denom = "N_row",
     .stats = "count_fraction",
diff --git a/book/tables/safety/egt05_qtcat.qmd b/book/tables/safety/egt05_qtcat.qmd
index fe2d2bf3eb..db249bacc5 100644
--- a/book/tables/safety/egt05_qtcat.qmd
+++ b/book/tables/safety/egt05_qtcat.qmd
@@ -91,7 +91,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     split_fun = split_fun,
     label_pos = "topleft"
   ) %>%
-  summarize_vars(
+  analyze_vars(
     vars = c("AVALCAT1", "CHGCAT1"),
     var_labels = c("Value at Visit", "Change from Baseline")
   ) %>%
diff --git a/book/tables/safety/enrollment01.qmd b/book/tables/safety/enrollment01.qmd
index 5c74110dbc..e1f3b81cc0 100644
--- a/book/tables/safety/enrollment01.qmd
+++ b/book/tables/safety/enrollment01.qmd
@@ -124,7 +124,7 @@ result
 ## `teal` App
 
 Note that for this module application, only the variables passed into `by_vars` are used when `row_groups` is selected.
-Variables passed into `summarize_vars` are additionally used when `row_groups` is deselected.
+Variables passed into `analyze_vars` are additionally used when `row_groups` is deselected.
 
 ```{r teal, message=FALSE, opts.label='skip_if_testing'}
 #| screenshot.opts = list(delay = 8)
diff --git a/book/tables/safety/ext01.qmd b/book/tables/safety/ext01.qmd
index ec97115ed3..c78efad124 100644
--- a/book/tables/safety/ext01.qmd
+++ b/book/tables/safety/ext01.qmd
@@ -89,7 +89,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
   split_cols_by("ACTARM") %>%
   split_rows_by("PARCAT2", split_label = "\nParameter Category (Drug A/Drug B)", label_pos = "topleft") %>%
   split_rows_by("PARAM", split_fun = split_fun) %>%
-  summarize_vars(vars = "AVAL")
+  analyze_vars(vars = "AVAL")
 
 result <- build_table(lyt = lyt, df = adex, alt_counts_df = adsl)
 
@@ -133,7 +133,7 @@ anl <- adex %>%
 lyt <- basic_table(show_colcounts = TRUE) %>%
   split_cols_by("ACTARM") %>%
   split_rows_by("PARCAT2", split_label = "\nParameter Category (Drug A/Drug B)", label_pos = "topleft") %>%
-  summarize_vars(
+  analyze_vars(
     vars = c("TDURD", "TDURDC", "TDOSE", "TNDOSE"),
     var_labels = var_labels(anl)[c("TDURD", "TDURDC", "TDOSE", "TNDOSE")]
   )
@@ -180,7 +180,7 @@ anl <- adex %>%
 lyt <- basic_table(show_colcounts = TRUE) %>%
   split_cols_by("ACTARM") %>%
   split_rows_by("PARCAT2", split_label = "\nParameter Category (Drug A/Drug B)", label_pos = "topleft") %>%
-  summarize_vars(
+  analyze_vars(
     vars = c("TDURD", "TDURDC", "TDOSE", "TNDOSE"),
     var_labels = var_labels(anl)[c("TDURD", "TDURDC", "TDOSE", "TNDOSE")]
   ) %>%