diff --git a/DESCRIPTION b/DESCRIPTION
index f9aa3b8..4c89825 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
 Package: betaselectr
 Title: Selective Standardization in Structural Equation Models
-Version: 0.0.1.14
+Version: 0.0.1.15
 Authors@R:
     c(person(given = "Shu Fai",
              family = "Cheung",
diff --git a/NEWS.md b/NEWS.md
index af4a08d..50623c8 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,4 +1,4 @@
-# betaselectr 0.0.1.14
+# betaselectr 0.0.1.15
 
 - Added `lm_betaselect()` and related
   methods and helper functions.
@@ -77,4 +77,8 @@
   to print confidence intervals by
   default, if available. (0.0.1.13)
 
+- Added `skip_response` to
+  `lm_betaselect()` and `glm_betaselect()`
+  as a convenient way to skip standardizing
+  the response variables. (0.0.1.15)
 
diff --git a/R/lm_betaselect.R b/R/lm_betaselect.R
index d1deb4e..bad876a 100644
--- a/R/lm_betaselect.R
+++ b/R/lm_betaselect.R
@@ -239,6 +239,17 @@
 #' at the same time. Default is `NULL`,
 #' and only `to_standardize` is used.
 #'
+#' @param skip_response Logical. If
+#' `TRUE`, will not standardize the
+#' response (outcome) variable even if
+#' it appears in `to_standardize` or
+#' `to_standardize` is not specified.
+#' Used for models such as logistic
+#' regression models in which there are
+#' some restrictions on the response
+#' variables (e.g., only 0 or 1 for
+#' logistic regression).
+#'
 #' @param do_boot Whether bootstrapping
 #' will be conducted. Default is `TRUE`.
 #'
@@ -352,6 +363,7 @@
 lm_betaselect <- function(...,
                           to_standardize = NULL,
                           not_to_standardize = NULL,
+                          skip_response = FALSE,
                           do_boot = TRUE,
                           bootstrap = 100L,
                           iseed = NULL,
@@ -408,7 +420,10 @@ lm_betaselect <- function(...,
                         input_data = input_data,
                         to_standardize = to_standardize,
                         not_to_standardize = not_to_standardize,
-                        skip_categorical_x = TRUE
+                        skip_categorical_x = TRUE,
+                        skip_response = skip_response,
+                        model_call = model_call,
+                        org_call = my_call
                       )
     # Do standardization
     input_data_z <- input_data
@@ -510,6 +525,7 @@ lm_betaselect <- function(...,
 glm_betaselect <- function(...,
                            to_standardize = NULL,
                            not_to_standardize = NULL,
+                           skip_response = FALSE,
                            do_boot = TRUE,
                            bootstrap = 100L,
                            iseed = NULL,
diff --git a/R/lm_betaselect_helpers.R b/R/lm_betaselect_helpers.R
index 982826a..d6a80d6 100644
--- a/R/lm_betaselect_helpers.R
+++ b/R/lm_betaselect_helpers.R
@@ -48,6 +48,7 @@ fix_to_standardize_lm <- function(object,
     # if (length(prods) > 0) {
     #     to_standardize <- setdiff(to_standardize, names(prods))
     #   }
+    browser()
     to_standardize
   }
 
@@ -58,7 +59,10 @@ fix_to_standardize_lm_data <- function(object,
                                        input_data,
                                        to_standardize = ".all.",
                                        not_to_standardize = NULL,
-                                       skip_categorical_x = TRUE) {
+                                       skip_categorical_x = TRUE,
+                                       skip_response = FALSE,
+                                       model_call = NULL,
+                                       org_call = NULL) {
 
     if (!identical(to_standardize, ".all.") && !is.null(not_to_standardize)) {
         stop("Do not specify both to_standardize and not_to_standardize.")
@@ -96,6 +100,11 @@ fix_to_standardize_lm_data <- function(object,
     if ((length(cat_vars) > 0) && skip_categorical_x) {
         to_standardize <- setdiff(to_standardize, cat_vars)
       }
+    if (skip_response) {
+        lm_terms <- stats::terms(object)
+        lm_y <- all.vars(lm_terms)[attr(lm_terms, "response")]
+        to_standardize <- setdiff(to_standardize, lm_y)
+      }
     # if (length(prods) > 0) {
     #     to_standardize <- setdiff(to_standardize, names(prods))
     #   }
diff --git a/README.md b/README.md
index 20d4e45..0702c29 100644
--- a/README.md
+++ b/README.md
@@ -12,7 +12,7 @@ Not ready for use.
 
 # betaselectr: Do selective standardization in structural equation models and regression models
 
-(Version 0.0.1.14, updated on 2024-10-30, [release history](https://sfcheung.github.io/betaselectr/news/index.html))
+(Version 0.0.1.15, updated on 2024-10-30, [release history](https://sfcheung.github.io/betaselectr/news/index.html))
 
 It computes Beta_Select, standardization
 in structural equation models with only
diff --git a/man/lm_betaselect.Rd b/man/lm_betaselect.Rd
index 6e22f90..2b46b56 100644
--- a/man/lm_betaselect.Rd
+++ b/man/lm_betaselect.Rd
@@ -13,6 +13,7 @@ lm_betaselect(
   ...,
   to_standardize = NULL,
   not_to_standardize = NULL,
+  skip_response = FALSE,
   do_boot = TRUE,
   bootstrap = 100L,
   iseed = NULL,
@@ -27,6 +28,7 @@ glm_betaselect(
   ...,
   to_standardize = NULL,
   not_to_standardize = NULL,
+  skip_response = FALSE,
   do_boot = TRUE,
   bootstrap = 100L,
   iseed = NULL,
@@ -81,6 +83,17 @@ cannot be ued with \code{to_standardize}
 at the same time. Default is \code{NULL},
 and only \code{to_standardize} is used.}
 
+\item{skip_response}{Logical. If
+\code{TRUE}, will not standardize the
+response (outcome) variable even if
+it appears in \code{to_standardize} or
+\code{to_standardize} is not specified.
+Used for models such as logistic
+regression models in which there are
+some restrictions on the response
+variables (e.g., only 0 or 1 for
+logistic regression).}
+
 \item{do_boot}{Whether bootstrapping
 will be conducted. Default is \code{TRUE}.}
 
diff --git a/tests/testthat/test_glm_betaselect_skip_def.R b/tests/testthat/test_glm_betaselect_skip_def.R
new file mode 100644
index 0000000..9368f4c
--- /dev/null
+++ b/tests/testthat/test_glm_betaselect_skip_def.R
@@ -0,0 +1,14 @@
+library(testthat)
+
+dat <- data_test_mod_cat
+
+dat$dv <- ifelse(dat$dv > mean(dat$dv),
+                 yes = 1,
+                 no = 0)
+test_that("skip response", {
+  expect_error(glm_betaselect(dv ~ iv*mod + cov1 + cat1, dat, to_standardize = "dv", do_boot = FALSE, family = binomial),
+               "y values", fixed = TRUE)
+  expect_error(glm_betaselect(dv ~ iv*mod + cov1 + cat1, dat, do_boot = FALSE, family = binomial),
+               "y values", fixed = TRUE)
+  expect_no_error(glm_betaselect(dv ~ iv*mod + cov1 + cat1, dat, skip_response = TRUE, do_boot = FALSE, family = binomial))
+})
diff --git a/vignettes/betaselectr_glm.Rmd b/vignettes/betaselectr_glm.Rmd
index 52f0620..a745f3a 100644
--- a/vignettes/betaselectr_glm.Rmd
+++ b/vignettes/betaselectr_glm.Rmd
@@ -233,7 +233,8 @@ including product terms.
 
 Suppose we only need to
 solve the first problem, standardizing all
-numeric variables,
+numeric variables except for the
+response variable (which is binary),
 with the product
 term computed after `iv` and `mod`
 are standardized.
@@ -242,7 +243,7 @@ are standardized.
 ``` r
 glm_beta_select <- glm_betaselect(dv ~ iv*mod + cov1 + cat1,
                                   data = data_test_mod_cat_binary,
-                                  not_to_standardize = "dv",
+                                  skip_response = TRUE,
                                   family = binomial(),
                                   do_boot = FALSE)
 ```
@@ -262,9 +263,9 @@ variable (`dv` in this example) may not
 be meaningful or may even be not allowed.
 In the case of logistic regression, the
 outcome variable need to be 0 or 1 only.
-Therefore, `not_to_standardize` is set to
-`"dv"`, the name of the outcome variable,
-to request that it is *not* standardized.
+Therefore, `skip_response` is set to
+`TRUE`, to request that the response
+(outcome) variable is *not* standardized.
 
 Moreover, categorical variables (factors and
 string variables) will not be standardized.
@@ -286,7 +287,7 @@ summary(glm_beta_select)
 #> Waiting for profiling to be done...
 #> Call to glm_betaselect():
 #> betaselectr::lm_betaselect(formula = dv ~ iv * mod + cov1 + cat1, 
-#>     family = binomial(), data = data_test_mod_cat_binary, not_to_standardize = "dv", 
+#>     family = binomial(), data = data_test_mod_cat_binary, skip_response = TRUE, 
 #>     do_boot = FALSE, model_call = "glm")
 #> 
 #> Variable(s) standardized: iv, mod, cov1 
@@ -367,7 +368,7 @@ set:
 glm_beta_select_boot <- glm_betaselect(dv ~ iv*mod + cov1 + cat1,
                                        data = data_test_mod_cat_binary,
                                        family = binomial(),
-                                       not_to_standardize = "dv",
+                                       skip_response = TRUE,
                                        bootstrap = 5000,
                                        iseed = 4567)
 ```
@@ -392,7 +393,7 @@ This is the output of `summary()`
 summary(glm_beta_select_boot)
 #> Call to glm_betaselect():
 #> betaselectr::lm_betaselect(formula = dv ~ iv * mod + cov1 + cat1, 
-#>     family = binomial(), data = data_test_mod_cat_binary, not_to_standardize = "dv", 
+#>     family = binomial(), data = data_test_mod_cat_binary, skip_response = TRUE, 
 #>     bootstrap = 5000, iseed = 4567, model_call = "glm")
 #> 
 #> Variable(s) standardized: iv, mod, cov1 
@@ -470,6 +471,7 @@ this, setting
 glm_beta_select_boot_1 <- glm_betaselect(dv ~ iv*mod + cov1 + cat1,
                                          data = data_test_mod_cat_binary,
                                          to_standardize = c("iv", "cov1"),
+                                         skip_response = TRUE,
                                          family = binomial(),
                                          bootstrap = 5000,
                                          iseed = 4567)
@@ -485,6 +487,7 @@ this call, and set
 glm_beta_select_boot_2 <- glm_betaselect(dv ~ iv*mod + cov1 + cat1,
                                          data = data_test_mod_cat_binary,
                                          not_to_standardize = c("dv", "mod"),
+                                         skip_response = TRUE,
                                          family = binomial(),
                                          bootstrap = 5000,
                                          iseed = 4567)
@@ -500,7 +503,8 @@ summary(glm_beta_select_boot_1)
 #> Call to glm_betaselect():
 #> betaselectr::lm_betaselect(formula = dv ~ iv * mod + cov1 + cat1, 
 #>     family = binomial(), data = data_test_mod_cat_binary, to_standardize = c("iv", 
-#>         "cov1"), bootstrap = 5000, iseed = 4567, model_call = "glm")
+#>         "cov1"), skip_response = TRUE, bootstrap = 5000, iseed = 4567, 
+#>     model_call = "glm")
 #> 
 #> Variable(s) standardized: iv, cov1 
 #> 
diff --git a/vignettes/betaselectr_glm.Rmd.original b/vignettes/betaselectr_glm.Rmd.original
index 26fe74f..95882e7 100644
--- a/vignettes/betaselectr_glm.Rmd.original
+++ b/vignettes/betaselectr_glm.Rmd.original
@@ -181,7 +181,8 @@ including product terms.
 
 Suppose we only need to
 solve the first problem, standardizing all
-numeric variables,
+numeric variables except for the
+response variable (which is binary),
 with the product
 term computed after `iv` and `mod`
 are standardized.
@@ -189,7 +190,7 @@ are standardized.
 ```{r, results = FALSE}
 glm_beta_select <- glm_betaselect(dv ~ iv*mod + cov1 + cat1,
                                   data = data_test_mod_cat_binary,
-                                  not_to_standardize = "dv",
+                                  skip_response = TRUE,
                                   family = binomial(),
                                   do_boot = FALSE)
 ```
@@ -209,9 +210,9 @@ variable (`dv` in this example) may not
 be meaningful or may even be not allowed.
 In the case of logistic regression, the
 outcome variable need to be 0 or 1 only.
-Therefore, `not_to_standardize` is set to
-`"dv"`, the name of the outcome variable,
-to request that it is *not* standardized.
+Therefore, `skip_response` is set to
+`TRUE`, to request that the response
+(outcome) variable is *not* standardized.
 
 Moreover, categorical variables (factors and
 string variables) will not be standardized.
@@ -269,7 +270,7 @@ set:
 glm_beta_select_boot <- glm_betaselect(dv ~ iv*mod + cov1 + cat1,
                                        data = data_test_mod_cat_binary,
                                        family = binomial(),
-                                       not_to_standardize = "dv",
+                                       skip_response = TRUE,
                                        bootstrap = 5000,
                                        iseed = 4567)
 ```
@@ -330,6 +331,7 @@ this, setting
 glm_beta_select_boot_1 <- glm_betaselect(dv ~ iv*mod + cov1 + cat1,
                                          data = data_test_mod_cat_binary,
                                          to_standardize = c("iv", "cov1"),
+                                         skip_response = TRUE,
                                          family = binomial(),
                                          bootstrap = 5000,
                                          iseed = 4567)
@@ -344,6 +346,7 @@ this call, and set
 glm_beta_select_boot_2 <- glm_betaselect(dv ~ iv*mod + cov1 + cat1,
                                          data = data_test_mod_cat_binary,
                                          not_to_standardize = c("dv", "mod"),
+                                         skip_response = TRUE,
                                          family = binomial(),
                                          bootstrap = 5000,
                                          iseed = 4567)