Merge pull request #163 from IndrajeetPatil/master

address CRAN comments

DESCRIPTION

@@ -68,6 +68,5 @@ VignetteBuilder:
     knitr
 Encoding: UTF-8
 Language: en-US
-LazyData: true
 RoxygenNote: 7.1.1.9001
 Config/testthat/edition: 3

R/cor_test.R

@@ -45,8 +45,8 @@
 #'   redundant. Nonetheless, it is an easy option to increase the robustness of the
 #'   correlation as well as flexible way to obtain Bayesian or multilevel
 #'   Spearman-like rank correlations.
-#' @param robust Old name for \code{ranktransform}. Will be removed in subsequent 
-#'   versions, so better to use \code{ranktransform} which is more explicit about 
+#' @param robust Old name for \code{ranktransform}. Will be removed in subsequent
+#'   versions, so better to use \code{ranktransform} which is more explicit about
 #'   what it does.
 #' @param winsorize Another way of making the correlation more "robust" (i.e.,
 #'   limiting the impact of extreme values). Can be either \code{FALSE} or a
@@ -138,7 +138,7 @@ cor_test <- function(data,
                      ...) {
 
   # Deprecation warnings
-  if(!is.null(robust)) {
+  if (!is.null(robust)) {
     warning("The 'robust' argument is deprecated in favour of 'ranktransform' (more explicit). Please use the latter instead to remove this warning.")
     ranktransform <- robust
   }

R/correlation.R

@@ -252,7 +252,7 @@ correlation <- function(data,
                         ...) {
 
   # Deprecation warnings
-  if(!is.null(robust)) {
+  if (!is.null(robust)) {
     warning("The 'robust' argument is deprecated in favour of 'ranktransform' (more explicit). Please use the latter instead to remove this warning.")
     ranktransform <- robust
   }

cran-comments.md

@@ -7,6 +7,8 @@
 
 0 errors | 0 warnings | 0 note
 
+ * Fixes `NOTE`s and `WARNING`s in `R CMD CHECK` for last released version.
+
 ## revdepcheck results
 
 We checked 4 reverse dependencies, comparing R CMD check results across CRAN and

inst/WORDLIST

@@ -62,6 +62,7 @@ dichotomously
 doi
 easystats
 et
+favour
 favours
 fieller
 frac
@@ -82,7 +83,6 @@ pracma
 ressembles
 rmarkdown
 semipartial
-severly
 spearman
 tetrachoric
 th

tests/testthat/test-display_print_matrix.R

@@ -1,4 +1,4 @@
-if (require("testthat") && require("gt")  && require("dplyr")) {
+if (require("testthat") && require("gt") && require("dplyr")) {
 
   # display and print method works - markdown -----------------------------
 

vignettes/multilevel.Rmd

@@ -19,8 +19,9 @@ bibliography: bibliography.bib
 
 This vignette can be cited as:
 
-Makowski, D., Ben-Shachar, M. S., Patil, I., & Lüdecke, D. (2019). Methods
-and Algorithms for Correlation Analysis in R. _Journal of Open Source Software_, _5_(51), 2306. doi:10.21105/joss.02306
+```{r cite}
+citation("correlation")
+```
 
 ---
 
@@ -102,8 +103,7 @@ ggplot(data, aes(x = V1, y = V2)) +
 ```
 
 Mmh, interesting. It seems like, for each subject, the relationship is
-different. The negative general trend seems to be created by **differences
-between the groups** and could be spurious!
+different. The (global) negative trend seems to be an artifact of **differences between the groups** and could be spurious!
 
 **Multilevel *(as in multi-group)* ** correlations allow us to account for
 **differences between groups**. It is based on a partialization of the group,

vignettes/types.Rmd

@@ -42,16 +42,17 @@ if (!requireNamespace("see", quietly = TRUE) ||
 
 This vignette can be cited as:
 
-Makowski, D., Ben-Shachar, M. S., Patil, I., & Lüdecke, D. (2019). Methods
-and Algorithms for Correlation Analysis in R. _Journal of Open Source Software_, _5_(51), 2306. doi:10.21105/joss.02306
+```{r cite}
+citation("correlation")
+```
 
 ---
 
 ## Different Methods for Correlations
 
 Correlations tests are arguably one of the most commonly used statistical
 procedures, and are used as a basis in many applications such as exploratory
-data analysis, structural modelling, data engineering etc. In this context, we
+data analysis, structural modeling, data engineering, etc. In this context, we
 present **correlation**, a toolbox for the R language [@Rteam] and part of the
 [**easystats**](https://github.com/easystats/easystats) collection, focused on
 correlation analysis. Its goal is to be lightweight, easy to use, and allows for
@@ -130,7 +131,7 @@ binary variable is assumed to have an underlying continuity. For example,
 anxiety level can be measured on a continuous scale, but can be classified
 dichotomously as high/low.
 
-- **Winsorized correlation**: Correlation of variables that have been formerly
+- **Winsorized correlation**: Correlation of variables that have been
 Winsorized, i.e., transformed by limiting extreme values to reduce the effect of
 possibly spurious outliers.
 
@@ -141,7 +142,7 @@ distributed continuous latent variables, from two observed ordinal variables.
 applicable when both observed variables are dichotomous.
 
 - **Partial correlation**: Correlation between two variables after adjusting for
-the (linear) the effect of one or more variables. The correlation test is here
+the (linear) effect of one or more variables. The correlation test is 
 run after having partialized the dataset, independently from it. In other words,
 it considers partialization as an independent step generating a different
 dataset, rather than belonging to the same model. This is why some discrepancies
@@ -154,7 +155,7 @@ $$r_{xy.z} = r_{e_{x.z},e_{y.z}}$$
 
 - **Multilevel correlation**: Multilevel correlations are a special case of
 partial correlations where the variable to be adjusted for is a factor and is
-included as a random effect in a mixed model.
+included as a random effect in a mixed-effects model.
 
 ## Comparison