Merge pull request #45 from neuropsychology/0.2.0

0.2.0_CRAN

.travis.yml

@@ -1,29 +1,26 @@
 language: r
 sudo: false
 
-r_binary_packages:
-  - methods
-  - psych
-  - MASS
-  - nFactors
-  - qgraph
-  - lmerTest
-  - MuMIn
-  - ggcorrplot
-  - ppcor
+r_build_args: '--no-build-vignettes'
+r_check_args: '--ignore-vignettes'
+
 
 # Using the package cache to store R package dependencies can significantly
 # speed up build times and is recommended for most builds.
-cache:
-  - apt
-  - packages
+cache: packages
+
+r:
+  - release
+  - devel
+
 
 warnings_are_errors: true
 
 r_packages:
   - covr
   - lintr
-
+
+
 after_success:
   - Rscript -e 'library(covr); codecov()'
 #  - Rscript -e 'devtools::install();lintr::lint_package()'

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: psycho
 Type: Package
 Title: Efficient and Publishing-Oriented Workflow for Psychological Science
-Version: 0.1.9
+Version: 0.2.0
 Authors@R: c(
     person("Dominique", 
         "Makowski", 
@@ -28,11 +28,11 @@ Encoding: UTF-8
 LazyData: true
 RoxygenNote: 6.0.1
 Depends: 
-    R (>= 3.1.0)
+    R (>= 3.4.0)
 Imports:
     methods,
-    ggplot2,
     dplyr,
+    ggplot2,
     tidyr,
     stringr,
     purrr,
@@ -47,12 +47,17 @@ Imports:
     lmerTest,
     coda,
     emmeans,
-    broom
+    broom,
+    tibble,
+    DescTools,
+    pbkrtest,
+    BayesFactor
 Suggests:
     knitr,
     rmarkdown,
     testthat,
     covr,
     lme4,
-    plotly
+    plotly,
+    loo (>= 2.0.0)
 VignetteBuilder: knitr

NAMESPACE

@@ -1,14 +1,17 @@
 # Generated by roxygen2: do not edit by hand
 
 S3method(analyze,glmerMod)
-S3method(analyze,merMod)
-S3method(analyze,merModLmerTest)
+S3method(analyze,lm)
+S3method(analyze,lmerModLmerTest)
 S3method(analyze,stanreg)
 S3method(find_best_model,merModLmerTest)
 S3method(find_best_model,stanreg)
 S3method(find_combinations,formula)
+S3method(get_contrasts,glmerMod)
+S3method(get_contrasts,lmerModLmerTest)
 S3method(get_contrasts,stanreg)
 S3method(get_predicted,stanreg)
+S3method(is.mixed,stanreg)
 S3method(plot,psychobject)
 S3method(print,psychobject)
 S3method(summary,psychobject)
@@ -27,14 +30,19 @@ export(format_string)
 export(get_contrasts)
 export(get_predicted)
 export(hdi)
+export(interpret_bf)
 export(interpret_d)
 export(interpret_d_posterior)
+export(is.mixed)
 export(is.psychobject)
 export(is.standardized)
 export(mellenbergh.test)
 export(mpe)
 export(n_factors)
 export(odds_to_probs)
+export(overlap)
+export(power_analysis)
+export(probs_to_odds)
 export(standardize)
 export(values)
 import(coda)
@@ -46,20 +54,23 @@ import(ppcor)
 import(purrr)
 import(rstanarm)
 import(tidyr)
+importFrom(DescTools,AUC)
 importFrom(MASS,ginv)
 importFrom(MASS,mvrnorm)
 importFrom(MuMIn,r.squaredGLMM)
 importFrom(MuMIn,std.coef)
 importFrom(broom,tidy)
+importFrom(dplyr,bind_cols)
 importFrom(emmeans,emmeans)
 importFrom(ggplot2,element_text)
 importFrom(ggplot2,theme)
 importFrom(graphics,pairs)
-importFrom(methods,slot)
 importFrom(nFactors,moreStats)
 importFrom(nFactors,nScree)
 importFrom(psych,VSS)
 importFrom(psych,corr.test)
+importFrom(purrr,discard)
+importFrom(purrr,keep)
 importFrom(qgraph,cor_auto)
 importFrom(rstanarm,bayes_R2)
 importFrom(rstanarm,kfold)
@@ -68,20 +79,27 @@ importFrom(stats,as.formula)
 importFrom(stats,confint)
 importFrom(stats,cor)
 importFrom(stats,cov)
+importFrom(stats,density)
 importFrom(stats,dnorm)
 importFrom(stats,ecdf)
+importFrom(stats,family)
+importFrom(stats,formula)
 importFrom(stats,mad)
 importFrom(stats,median)
+importFrom(stats,model.frame)
+importFrom(stats,model.matrix)
 importFrom(stats,na.omit)
 importFrom(stats,p.adjust)
 importFrom(stats,pnorm)
 importFrom(stats,pt)
 importFrom(stats,qnorm)
 importFrom(stats,quantile)
+importFrom(stats,rnorm)
 importFrom(stats,sd)
 importFrom(stats,terms)
 importFrom(stats,update)
 importFrom(stringr,str_to_title)
+importFrom(tibble,rownames_to_column)
 importFrom(utils,combn)
 importFrom(utils,head)
 importFrom(utils,tail)

NEWS.md

@@ -1,9 +1,26 @@
 # Current Dev
 
 ### Breaking changes
+- Set default overlap parameter to TRUE in `analyze.stanreg` 
+- Remove support of lmerMod objects (linear mixed models must be fitted with lmerTest)
+- Refactored get_predicted.stanreg
+- Changed organization of `values` in analyzed models
 - Added `subset` parameter in `standardize`
 - Changed order of parameters in `dprime`
 ### New functions / parameters
+- Added `print` for `n_factors`
+- Added `overlap` (experimental) parameter to analyze.stanreg as a different index of effect existence
+- Added `overlap` function
+- Added `power_analysis` function.
+- Added `analyze.lm` for lm objects.
+- Added `interpret_bf` for bayes factor interpretation
+- Added `probs_to_odds`
+- Added confidence intervals (CI) to analyze for lmerTest models
+- Refactored `odds_to_probs`
+- Added ìs.mixed.stanreg`
+- Added `keep_iterations` in `get_predicted.stanreg` (and demonstration of how to plot them in vignettes)
+- Added `emotion` dataset
+- Added get_contrasts methods for lme4 objects
 - Added prior info in `analyze.stanreg`
 - Added (exposed) `interpret_d_posterior` for Bayesian size effect interpretation
 - Added `find_combinations` function

R/analyze.R

@@ -1,6 +1,12 @@
 #' Analyze objects.
 #'
-#' Analyze objects.
+#' Analyze objects. See the documentation for your object's class:
+#' \itemize{
+#'  \item{\link[=analyze.stanreg]{analyze.stanreg}}
+#'  \item{\link[=analyze.lmerModLmerTest]{analyze.merModLmerTest}}
+#'  \item{\link[=analyze.glmerMod]{analyze.glmerMod}}
+#'  \item{\link[=analyze.lm]{analyze.lm}}
+#'  }
 #'
 #' @param x object to analyze.
 #' @param ... Arguments passed to or from other methods.

R/analyze.glmerMod.R

@@ -9,11 +9,12 @@
 #'
 #' @examples
 #' library(psycho)
-#' require(lme4)
+#' library(lme4)
 #' fit <- lme4::glmer(vs ~ mpg + (1|cyl), data=mtcars, family="binomial")
 #'
 #' results <- analyze(fit)
 #' summary(results)
+#' print(results)
 #'
 #' @author \href{https://dominiquemakowski.github.io/}{Dominique Makowski}
 #'
@@ -29,13 +30,17 @@ analyze.glmerMod <- function(x, ...) {
   # -------------
   fit <- x
 
+  predictors <- all.vars(as.formula(fit@call$formula))
+  outcome <- predictors[[1]]
+  predictors <- tail(predictors, -1)
+
   R2m <- MuMIn::r.squaredGLMM(fit)["R2m"]
   R2c <- MuMIn::r.squaredGLMM(fit)["R2c"]
 
 
   # Summary
   # -------------
-  fitsum <- data.frame(lmerTest::summary(fit)$coefficients)
+  fitsum <- data.frame(summary(fit)$coefficients)
 
   fitsum$Variable <- rownames(fitsum)
   fitsum$Coef <- fitsum$Estimate
@@ -54,22 +59,32 @@ analyze.glmerMod <- function(x, ...) {
   # Values
   # -------------
   # Initialize empty values
-  values <- list()
-  values$R2m <- R2m
-  values$R2c <- R2c
+  values <- list(model = list(), effects = list())
+  values$model$R2m <- R2m
+  values$model$R2c <- R2c
 
   # Loop over all variables
   for (varname in varnames) {
-    text <- paste(
-      "The effect of ", varname, " was [NOT] significant (beta = ",
+    if (fitsum[varname, "p"] < .1) {
+      significance <- ""
+    } else {
+      significance <- "not"
+    }
+
+
+    text <- paste0(
+      "The effect of ",
+      varname,
+      " is ",
+      significance,
+      " significant (beta = ",
       format_digit(fitsum[varname, "Coef"], 2), ", SE = ",
       format_digit(fitsum[varname, "SE"], 2), ", z = ",
       format_digit(fitsum[varname, "z"], 2), ", p ",
-      format_p(fitsum[varname, "p"]), ").",
-      sep = ""
+      format_p(fitsum[varname, "p"]), ")."
     )
 
-    values[[varname]] <- list(
+    values$effects[[varname]] <- list(
       Coef = fitsum[varname, "Coef"],
       SE = fitsum[varname, "SE"],
       z = fitsum[varname, "z"],
@@ -82,20 +97,23 @@ analyze.glmerMod <- function(x, ...) {
 
   # Text
   # -------------
-  text <- c(paste(
-    "The overall model predicting ... successfully converged ",
+  text <- c(paste0(
+    "The overall model predicting ",
+    outcome,
+    " (formula = ",
+    format(fit@call$formula),
+    ") successfully converged",
     "and explained ",
     format_digit(R2c * 100, 2), "% of the variance of the",
     " endogen (the conditional R2). ",
     "The variance explained by the fixed effects was of ",
     format_digit(R2m * 100, 2), "% (the marginal R2) and the ",
     "one explained by the random effects of ",
-    format_digit((R2c - R2m) * 100, 2), "%.",
-    sep = ""
+    format_digit((R2c - R2m) * 100, 2), "%."
   ))
 
   for (varname in varnames) {
-    text <- c(text, paste("   -", values[[varname]]$Text))
+    text <- c(text, paste("   -", values$effects[[varname]]$Text))
   }