Update Docs for CRAN version

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: faux
 Title: Simulation for Factorial Designs
-Version: 0.0.1.4
-Date: 2020-08-12
+Version: 0.0.1.5
+Date: 2020-09-11
 Authors@R: c(
     person(
         given = "Lisa", 
@@ -45,7 +45,8 @@ Suggests:
     ggExtra,
     purrr,
     broom,
-    broom.mixed
+    broom.mixed,
+    psych
 VignetteBuilder: knitr
 RoxygenNote: 7.1.1
 Encoding: UTF-8

NAMESPACE

@@ -6,6 +6,7 @@ S3method(print,design)
 S3method(print,nested_list)
 S3method(print,psychds_codebook)
 export("%>%")
+export(average_r2tau_0)
 export(check_design)
 export(check_mixed_design)
 export(check_sim_stats)
@@ -40,6 +41,7 @@ export(sim_design)
 export(sim_df)
 export(sim_mixed_cc)
 export(sim_mixed_df)
+export(std_alpha2average_r)
 export(trunc2norm)
 export(unif2norm)
 export(unique_pairs)

NEWS.md

@@ -1,3 +1,8 @@
+# faux 0.0.1.5 (2020-09-11)
+
+* Removed a test using markdown that failed on Solaris (causing faux to be pulled from CRAN) Back on CRAN!
+* `seed` arguments reinstated as deprecated and produce a warning
+
 # faux 0.0.1.4 (2020-08-12)
 
 * Even more fixes for CRAN (on CRAN from 2009-08-19!)

R/distribution_convertors.R

@@ -240,3 +240,31 @@ norm2likert <- function(x, prob, mu = mean(x), sd = stats::sd(x)) {
   sapply(p, function(a) n + 1 - sum(a < cprob))
 }
 
+
+#' Standardized Alpha to Average R
+#'
+#' @param std_alpha The standarized alpha 
+#' @param n The number of items
+#'
+#' @return The average inter-item correlation
+#' @export
+#'
+#' @examples
+#' std_alpha2average_r(.8, 10)
+std_alpha2average_r <- function(std_alpha, n) {
+  sumR <- -n / ((std_alpha / (n/(n - 1))) - 1)
+  (sumR - n)/(n * (n - 1))
+}
+
+#' Average r to Random Intercept SD
+#'
+#' @param average_r The average inter-item correlation
+#' @param sigma Total error variance
+#'
+#' @return The standard deviation of the random intercept
+#' @export
+#'
+#' @examples
+average_r2tau_0 <- function(average_r, sigma) {
+  sqrt((average_r * sigma^2) / (1 - average_r))
+}

R/rnorm_multi.R

@@ -10,6 +10,7 @@
 #' @param varnames optional names for the variables (string vector of length vars) defaults if r is a matrix with column names
 #' @param empirical logical. If true, mu, sd and r specify the empirical not population mean, sd and covariance 
 #' @param as.matrix logical. If true, returns a matrix
+#' @param seed DEPRECATED use set.seed() instead
 #' 
 #' @return a tbl of vars vectors
 #' 
@@ -21,11 +22,12 @@
 
 rnorm_multi <- function(n, vars = NULL, mu = 0, sd = 1, r = 0,
                        varnames = NULL, empirical = FALSE, 
-                       as.matrix = FALSE) {
-  # if (!is.null(seed)) {
+                       as.matrix = FALSE, seed = NULL) {
+  if (!is.null(seed)) {
+    warning("The seed argument is deprecated. Please set seed using set.seed() instead")
   #   # reinstate system seed after simulation
   #   gs <- global_seed(); on.exit(global_seed(gs))
-  # }
+  }
 
   # error handling ----
   if ( !is.numeric(n) || n %% 1 > 0 || n < 1 ) {

R/sim_design.R

@@ -16,6 +16,7 @@
 #' @param interactive whether to run the function interactively
 #' @param design a design list including within, between, n, mu, sd, r, dv, id
 #' @param rep the number of data frames to return (default 1); if greater than 1, the returned data frame is nested by rep
+#' @param seed DEPRECATED use set.seed() instead
 #' 
 #' @return a tbl
 #' 
@@ -28,7 +29,7 @@ sim_design <- function(within = list(), between = list(),
                        id = list(id = "id"),
                        plot = faux_options("plot"), 
                        interactive = FALSE, 
-                       design = NULL, rep = 1) {
+                       design = NULL, rep = 1, seed = NULL) {
   # check the design is specified correctly
   if (interactive) {
     design <- interactive_design(plot = plot)
@@ -45,6 +46,10 @@ sim_design <- function(within = list(), between = list(),
                          dv = dv, id = id, plot = plot)
   }
 
+  if (!is.null(seed)) {
+    warning("The seed argument is deprecated. Please set seed using set.seed() instead")
+  }
+
   # simulate the data
   data <- sim_data(design, empirical = empirical, long = long, rep = rep)
 
@@ -60,12 +65,13 @@ sim_design <- function(within = list(), between = list(),
 #' @param long Whether the returned tbl is in wide (default = FALSE) or long (TRUE) format
 #' @param rep the number of data frames to return (default 1); if greater than 1, the returned data frame is nested by rep
 #' @param sep separator for within-columns, defaults to _
+#' @param seed DEPRECATED use set.seed() instead
 #' 
 #' @return a tbl
 #' @export
 #' 
 sim_data <- function(design, empirical = FALSE, long = FALSE, 
-                     rep = 1, sep = faux_options("sep")) {
+                     rep = 1, sep = faux_options("sep"), seed = NULL) {
   if (!is.numeric(rep)) {
     stop("rep must be a number")
   } else if (rep < 1) {
@@ -74,11 +80,12 @@ sim_data <- function(design, empirical = FALSE, long = FALSE,
     warning("rep should be an integer")
   }
 
-  # if (!is.null(seed)) {
+  if (!is.null(seed)) {
+    warning("The seed argument is deprecated. Please set seed using set.seed() instead")
   #   # reinstate system seed after simulation
   #   gs <- global_seed(); on.exit(global_seed(gs))
   #   set.seed(seed, kind = "Mersenne-Twister", normal.kind = "Inversion")
-  # }
+  }
 
   # defaults
   within <- list()

R/sim_df.R

@@ -13,6 +13,7 @@
 #' @param id the names of the column(s) for grouping observations
 #' @param empirical Should the returned data have these exact parameters? (versus be sampled from a population with these parameters)
 #' @param long whether to return the data table in long format
+#' @param seed DEPRECATED use set.seed() instead
 #' 
 #' @return a tbl
 #' @examples
@@ -22,12 +23,13 @@
 
 sim_df <- function (data, n = 100, within = c(), between = c(), 
                     id = "id", dv = "value",
-                    empirical = FALSE, long = FALSE) {
-  # if (!is.null(seed)) {
+                    empirical = FALSE, long = FALSE, seed = NULL) {
+  if (!is.null(seed)) {
+    warning("The seed argument is deprecated. Please set seed using set.seed() instead")
   #   # reinstate system seed after simulation
   #   gs <- global_seed(); on.exit(global_seed(gs))
   #   set.seed(seed, kind = "Mersenne-Twister", normal.kind = "Inversion")
-  # }
+  }
 
   # error checking ------
   if ( !is.numeric(n) || n %% 1 > 0 || n < 3 ) {

R/sim_mixed_cc.R

@@ -9,6 +9,7 @@
 #' @param item_sd the SD of item random intercepts (or an item_n-length named vector of random intercepts for each item)
 #' @param error_sd the SD of the error term
 #' @param empirical Should the returned data have these exact parameters? (versus be sampled from a population with these parameters)
+#' @param seed DEPRECATED use set.seed() instead
 #'
 #' @return a tbl 
 #' @export
@@ -18,12 +19,13 @@
 #' sim_mixed_cc(10, 10)
 sim_mixed_cc <- function(sub_n = 100, item_n = 20, grand_i = 0, 
                          sub_sd = 1, item_sd = 1, error_sd = 1, 
-                         empirical = FALSE) {
-  # if (!is.null(seed)) {
+                         empirical = FALSE, seed = NULL) {
+  if (!is.null(seed)) {
+    warning("The seed argument is deprecated. Please set seed using set.seed() instead")
   #   # reinstate system seed after simulation
   #   gs <- global_seed(); on.exit(global_seed(gs))
   #   set.seed(seed, kind = "Mersenne-Twister", normal.kind = "Inversion")
-  # }
+  }
 
   # sample subject random intercepts----
   if (length(sub_sd) == sub_n) {