Merge pull request #95 from neuropsychology/dev

0.4.0 - lots of updates and breaking changes
neuropsychology · Dec 23, 2018 · 1dffaf9 · 1dffaf9
2 parents a66be65 + 4f60a2b
commit 1dffaf9
Show file tree

Hide file tree

Showing 192 changed files with 3,138 additions and 2,295 deletions.
diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,7 +1,7 @@
 Package: psycho
 Type: Package
 Title: Efficient and Publishing-Oriented Workflow for Psychological Science
-Version: 0.3.6
+Version: 0.4.0
 Authors@R: c(
     person("Dominique", 
         "Makowski", 
@@ -28,9 +28,9 @@ Description: The main goal of the psycho package is to provide tools for psychol
 License: MIT + file LICENSE
 Encoding: UTF-8
 LazyData: true
-RoxygenNote: 6.1.0
+RoxygenNote: 6.1.1
 Depends: 
-    R (>= 3.4.0)
+    R (>= 3.5.0)
 Imports:
     methods,
     dplyr,
@@ -49,7 +49,6 @@ Imports:
     MuMIn,
     lme4,
     lmerTest,
-    coda,
     emmeans (>= 1.2.2),
     broom,
     tibble,
@@ -64,5 +63,6 @@ Suggests:
     testthat,
     covr,
     plotly,
-    GPArotation
+    GPArotation,
+    blavaan (>= 0.3.4)
 VignetteBuilder: knitr
diff --git a/NAMESPACE b/NAMESPACE
@@ -3,23 +3,29 @@
 S3method(analyze,anova)
 S3method(analyze,aov)
 S3method(analyze,aovlist)
+S3method(analyze,blavaan)
 S3method(analyze,fa)
 S3method(analyze,glm)
 S3method(analyze,glmerMod)
 S3method(analyze,htest)
 S3method(analyze,lavaan)
 S3method(analyze,lm)
 S3method(analyze,lmerModLmerTest)
+S3method(analyze,principal)
 S3method(analyze,stanreg)
 S3method(as.data.frame,density)
+S3method(find_best_model,lavaan)
 S3method(find_best_model,lmerModLmerTest)
 S3method(find_best_model,stanreg)
 S3method(find_combinations,formula)
 S3method(get_R2,glm)
 S3method(get_R2,lm)
 S3method(get_R2,merMod)
 S3method(get_R2,stanreg)
+S3method(get_contrasts,glm)
 S3method(get_contrasts,glmerMod)
+S3method(get_contrasts,lm)
+S3method(get_contrasts,lmerMod)
 S3method(get_contrasts,lmerModLmerTest)
 S3method(get_contrasts,stanreg)
 S3method(get_data,lm)
@@ -31,16 +37,27 @@ S3method(get_formula,lm)
 S3method(get_formula,lmerMod)
 S3method(get_formula,lmerModLmerTest)
 S3method(get_formula,stanreg)
+S3method(get_graph,fa)
+S3method(get_graph,lavaan)
+S3method(get_graph,psychobject_correlation)
 S3method(get_info,glm)
 S3method(get_info,glmerMod)
 S3method(get_info,lm)
 S3method(get_info,lmerMod)
 S3method(get_info,lmerModLmerTest)
 S3method(get_info,stanreg)
+S3method(get_means,glm)
+S3method(get_means,glmerMod)
+S3method(get_means,lm)
+S3method(get_means,lmerMod)
+S3method(get_means,lmerModLmerTest)
+S3method(get_means,stanreg)
 S3method(get_predicted,glm)
 S3method(get_predicted,lm)
 S3method(get_predicted,merMod)
 S3method(get_predicted,stanreg)
+S3method(interpret_lavaan,blavaan)
+S3method(interpret_lavaan,lavaan)
 S3method(is.mixed,stanreg)
 S3method(plot,psychobject)
 S3method(print,psychobject)
@@ -63,6 +80,7 @@ export(analyze)
 export(assess)
 export(bayes_cor)
 export(bayes_cor.test)
+export(cite_packages)
 export(correlation)
 export(crawford.test)
 export(crawford.test.freq)
@@ -71,6 +89,8 @@ export(create_intervals)
 export(dprime)
 export(find_best_model)
 export(find_combinations)
+export(find_distance_cluster)
+export(find_highest_density_point)
 export(find_matching_string)
 export(find_random_effects)
 export(find_season)
@@ -85,15 +105,19 @@ export(get_cfa_model)
 export(get_contrasts)
 export(get_data)
 export(get_formula)
+export(get_graph)
 export(get_info)
 export(get_loadings_max)
+export(get_means)
 export(get_predicted)
+export(golden)
 export(interpret_R2)
 export(interpret_R2_posterior)
 export(interpret_RMSEA)
 export(interpret_bf)
 export(interpret_d)
 export(interpret_d_posterior)
+export(interpret_lavaan)
 export(interpret_odds)
 export(interpret_odds_posterior)
 export(interpret_omega_sq)
@@ -117,14 +141,14 @@ export(power_analysis)
 export(probs_to_odds)
 export(refdata)
 export(remove_empty_cols)
+export(remove_outliers)
 export(reorder_matrix)
 export(rnorm_perfect)
 export(rope)
 export(simulate_data_regression)
 export(standardize)
 export(values)
 import(broom)
-import(coda)
 import(dplyr)
 import(ggcorrplot)
 import(ggplot2)

diff --git a/NEWS.md b/NEWS.md
@@ -1,6 +1,12 @@
 # Current Dev
 
+
+
+
+# [0.4.0](https://github.com/neuropsychology/psycho.R/releases/tag/0.4.0) (2018-06-11)
+
 ### Breaking changes
+- Major release, lots of undocumented breaking changes.)
 - Changed `hdi` to `HDI`
 - Removed Mean and SD from summary in `bayes_cor.test`
 ### New functions / parameters

diff --git a/R/analyze.R b/R/analyze.R
@@ -6,15 +6,17 @@
 #'  \item{\link[=analyze.lmerModLmerTest]{analyze.merModLmerTest}}
 #'  \item{\link[=analyze.glmerMod]{analyze.glmerMod}}
 #'  \item{\link[=analyze.lm]{analyze.lm}}
-#'  \item{\link[=analyze.lm]{analyze.glm}}
+#'  \item{\link[=analyze.glm]{analyze.glm}}
 #'  }
 #'  \itemize{
 #'  \item{\link[=analyze.htest]{analyze.htest}}
 #'  \item{\link[=analyze.aov]{analyze.aov}}
 #'  }
 #' \itemize{
 #'  \item{\link[=analyze.fa]{analyze.fa}}
-#'  \item{\link[=analyze.fa]{analyze.lavaan}}
+#'  \item{\link[=analyze.principal]{analyze.principal}}
+#'  \item{\link[=analyze.lavaan]{analyze.lavaan}}
+#'  \item{\link[=analyze.blavaan]{analyze.blavaan}}
 #'  }
 #'
 #' @param x object to analyze.

diff --git a/R/analyze.anova.R b/R/analyze.anova.R
@@ -11,30 +11,29 @@
 #' @examples
 #' \dontrun{
 #' library(psycho)
-#'
+#' 
 #' df <- psycho::affective
-#'
+#' 
 #' x <- aov(df$Tolerating ~ df$Salary)
 #' x <- aov(df$Tolerating ~ df$Salary * df$Sex)
-#'
+#' 
 #' x <- anova(lm(df$Tolerating ~ df$Salary * df$Sex))
-#'
-#'
+#' 
+#' 
 #' summary(analyze(x))
 #' print(analyze(x))
-#'
+#' 
 #' df <- psycho::emotion %>%
 #'   mutate(Recall = ifelse(Recall == TRUE, 1, 0)) %>%
 #'   group_by(Participant_ID, Emotion_Condition) %>%
 #'   summarise(Recall = sum(Recall) / n())
-#'
-#' x <- aov(Recall ~ Emotion_Condition + Error(Participant_ID), data=df)
-#' x <- anova(lmerTest::lmer(Recall ~ Emotion_Condition + (1|Participant_ID), data=df))
+#' 
+#' x <- aov(Recall ~ Emotion_Condition + Error(Participant_ID), data = df)
+#' x <- anova(lmerTest::lmer(Recall ~ Emotion_Condition + (1 | Participant_ID), data = df))
 #' analyze(x)
 #' summary(x)
 #' }
-#'
-#'
+#' 
 #' @references
 #' \itemize{
 #'  \item{Levine, T. R., & Hullett, C. R. (2002). Eta squared, partial eta squared, and misreporting of effect size in communication research. Human Communication Research, 28(4), 612-625.}
@@ -48,7 +47,7 @@
 #' @import broom
 #'
 #' @export
-analyze.aov <- function(x, effsize_rules="field2013", ...) {
+analyze.aov <- function(x, effsize_rules = "field2013", ...) {
   if (!"aov" %in% class(x)) {
     if (!"Residuals" %in% row.names(x)) {
       if (!is.null(x$Within)) {
@@ -289,20 +288,19 @@ analyze.aovlist <- analyze.aov
 #'
 #' @examples
 #' library(psycho)
-#'
+#' 
 #' df <- psycho::affective
-#'
+#' 
 #' x <- aov(df$Tolerating ~ df$Salary)
 #' x <- aov(df$Tolerating ~ df$Salary * df$Sex)
-#'
+#' 
 #' omega_sq(x)
-#'
 #' @seealso http://stats.stackexchange.com/a/126520
 #'
 #' @author Arnoud Plantinga
 #' @importFrom stringr str_trim
 #' @export
-omega_sq <- function(x, partial=TRUE) {
+omega_sq <- function(x, partial = TRUE) {
   if ("aov" %in% class(x)) {
     summary_aov <- summary(x)[[1]]
   } else {