Merge pull request #20 from sfcheung/devel

Draft lm vignette

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: betaselectr
 Title: Selective Standardization in Structural Equation Models
-Version: 0.0.1.11
+Version: 0.0.1.12
 Authors@R:
     c(person(given = "Shu Fai",
              family = "Cheung",

NEWS.md

@@ -1,4 +1,4 @@
-# betaselectr 0.0.1.11
+# betaselectr 0.0.1.12
 
 - Added `lm_betaselect()` and related
   methods and helper functions.
@@ -63,4 +63,8 @@
 
 - Updated `print.summary.lm_betaselect()`
   to print confidence intervals by
-  default, if available. (0.0.1.11)
+  default, if available. (0.0.1.11)
+
+- Fixed a bug in printing the bootstrap
+  *p*-values for `summary.lm_betaselect()`.
+  (0.0.1.12)

R/data_test.R

@@ -56,4 +56,33 @@
 #' summary(lm_out)
 #'
 #'
-"data_test_mod_cat"
+"data_test_mod_cat"
+
+#' @title Test Dataset with Moderator
+#' and Categorical Variables (Version 2)
+#'
+#' @description This dataset has one
+#' predictor, one moderator, one
+#' control variable, one dependent
+#' variable, and a categorical variable.
+#'
+#' Similar to `data_test_mod_cat` but
+#' generated from another population.
+#'
+#' @format A data frame with 500 rows
+#' and five variables:
+#' \describe{
+#'   \item{dv}{Dependent variable, continuous}
+#'   \item{iv}{Independent variable, continuous}
+#'   \item{mod}{Moderator, continuous}
+#'   \item{cov1}{Control variable, continuous}
+#'   \item{cat1}{String variable with these values: "gp1", "gp2", and "gp3"}
+#' }
+#'
+#' @examples
+#'
+#' lm_out <- lm(dv ~ iv * mod + cov1 + cat1, data_test_mod_cat)
+#' summary(lm_out)
+#'
+#'
+"data_test_mod_cat2"

R/lm_betaselect_methods.R

@@ -949,6 +949,7 @@ summary.lm_betaselect <- function(object,
         colnames(out$coefficients)[i] <- "z value"
         if (boot_pvalue_type == "asymmetric") {
             boot_est_list <- split(boot_est, rownames(boot_est))
+            boot_est_list <- boot_est_list[rownames(boot_est)]
             boot_pvalues <- sapply(boot_est_list,
                                    est2p,
                                    h0 = 0)
@@ -1462,6 +1463,7 @@ summary.glm_betaselect <- function(object,
         colnames(out$coefficients)[i] <- "z value"
         if (boot_pvalue_type == "asymmetric") {
             boot_est_list <- split(boot_est, rownames(boot_est))
+            boot_est_list <- boot_est_list[names(boot_est_list)]
             boot_pvalues <- sapply(boot_est_list,
                                    est2p,
                                    h0 = 0)

README.md

@@ -12,7 +12,7 @@ Not ready for use.
 
 # betaselectr: Do selective standardization in structural equation models and regression models
 
-(Version 0.0.1.11, updated on 2024-10-29, [release history](https://sfcheung.github.io/betaselectr/news/index.html))
+(Version 0.0.1.12, updated on 2024-10-29, [release history](https://sfcheung.github.io/betaselectr/news/index.html))
 
 It computes Beta_Select, standardization
 in structural equation models with only

data-raw/data_test_03.R

@@ -0,0 +1,43 @@
+# Adapted from stdmod
+
+set.seed(41543)
+n <- 300
+x <- rnorm(n)
+w <- .4 * x + sqrt(1 - .4^2) * rnorm(n)
+v1 <- rnorm(n)
+cat1 <- sample(c("gp1", "gp2", "gp3"), n, replace = TRUE, prob = c(.2, .3, .5))
+y <- .2 * x + .3 * w + .35 * x * w + .12 * v1 +
+      sapply(cat1,
+             switch,
+             gp1 = 0,
+             gp2 = .4,
+             gp3 = .6) +
+      rnorm(n, 0, 1.4)
+dat <- data.frame(dv = y,
+                  iv = x,
+                  mod = w,
+                  cov1 = v1,
+                  cat1,
+                  stringsAsFactors = FALSE)
+out <- lm(dv ~ iv * mod + cov1 + cat1,
+          dat)
+summary(out)
+apply(dat[, 1:4], 2, sd)
+colMeans(dat[, 1:4])
+b <- 1 / c(5, 2, 4, 2)
+a <- c(20, 15, 50, 20) * -b
+dat0 <- scale(dat[, 1:4],
+              center = a,
+              scale = b)
+dat0 <- round(dat0, 2)
+apply(dat0, 2, sd)
+colMeans(dat0)
+apply(dat0, 2, range)
+dat1 <- data.frame(dat0, cat1 = dat$cat1)
+head(dat1)
+out <- lm(dv ~ iv * mod + cov1 + cat1,
+          dat1)
+summary(out)
+summary(lm.beta::lm.beta(out))
+data_test_mod_cat2 <- dat1
+usethis::use_data(data_test_mod_cat2, overwrite = TRUE)

rebuild_vignettes.R

@@ -4,6 +4,7 @@ base_dir <- getwd()
 
 setwd("vignettes/")
 knitr::knit("betaselectr_lav.Rmd.original", output = "betaselectr_lav.Rmd")
+knitr::knit("betaselectr_lm.Rmd.original", output = "betaselectr_lm.Rmd")
 
 setwd(base_dir)