more cran check updates

.Rbuildignore

@@ -1,7 +1,5 @@
 ^.*\.Rproj$
 ^\.Rproj\.user$
-^build/js
-^build/R*
 ^.*\.jmo
 ^.*\.pdf
 ^data-raw$

DESCRIPTION

@@ -4,14 +4,14 @@ Title: Estimation Statistics with Confidence Intervals
 Version: 1.0.2
 Author: Robert J Calin-Jageman
 Maintainer: Robert J Calin-Jageman <rcalinjageman@dom.edu>
-Description: An r package and jamovi module for the estimation approach 
+Description: An r package and 'jamovi' module for the estimation approach 
     to inferential statistics, the approach which emphasizes effect sizes, 
     interval estimates, and meta-analysis. Nearly all functions
-    are based on statpsych or metafor.  This package is still under active
+    are based on 'statpsych' or 'metafor'.  This package is still under active
     development, and breaking changes are likely, especially with the
     plot and hypothesis test functions.  If you need a stable and
     production-ready approach for confidence intervals, use
-    statpsych.  Please Post issues, bugs, and feature requests 
+    'statpsych'.  Please Post issues, bugs, and feature requests 
     to <https://github.com/rcalinjageman/esci>.
 License: GPL-3
 Encoding: UTF-8

R/estimate_mdiff_2x2_between.R

@@ -1,8 +1,7 @@
 #' Estimates for a 2x2 between-subjects design with a continuous outcome
 #' variable
 #'
-#' @description
-#' \loadmathjax
+#' @description \loadmathjax
 #' `estimate_mdiff_2x2_between` is suitable for a 2x2 between-subjects design
 #' with a continuous outcome variable.  It estimates each main effect, the
 #' simple effects for the first factor, and the interaction.  It can express

R/estimate_mdiff_2x2_mixed.R

@@ -1,8 +1,7 @@
 #' Estimates for a 2x2 mixed factorial design with a continuous outcome
 #' variable
 #'
-#' @description
-#' \loadmathjax
+#' @description \loadmathjax
 #' `estimate_mdiff_2x2_mixed` is suitable for a 2x2 mixed-factorial design
 #' with a continuous outcome variable.  It estimates each main effect, the
 #' simple effects for the repeated-measures factor, and the interaction.

R/estimate_mdiff_ind_contrast.R

@@ -1,8 +1,7 @@
 #' Estimates for a multi-group design with a continuous outcome
 #' variable
 #'
-#' @description
-#' \loadmathjax
+#' @description \loadmathjax
 #' `estimate_mdiff_ind_contrast` is suitable for a multi-group design
 #' (between subjects) with a continuous outcome variable.  It accepts
 #' a user-defined set of contrast weights that allows estimation of any

R/estimate_mdiff_one.R

@@ -1,8 +1,7 @@
 #' Estimates for a single-group design with a continuous outcome
 #' variable compared to a reference or population value
 #'
-#' @description
-#' \loadmathjax
+#' @description \loadmathjax
 #' `estimate_mdiff_one` is suitable for a single-group design
 #' with a continuous outcome variable that is compared to a reference
 #' or population value.  It can express estimates as mean differences,

R/estimate_mdiff_paired.R

@@ -2,8 +2,7 @@
 #' variable
 #'
 #'
-#' @description
-#' \loadmathjax
+#' @description \loadmathjax
 #' `estimate_mdiff_paired` is suitable for a simple paired design
 #' with a continuous outcome variable.  It provides estimates and CIs for the
 #' population mean difference between the repeated measures, the standardized

R/estimate_mdiff_two.R

@@ -1,8 +1,7 @@
 #' Estimates for a two-group study with a continuous outcome variable
 #'
 #'
-#' @description
-#' \loadmathjax
+#' @description \loadmathjax
 #' `estimate_mdiff_two` is suitable for a simple two-group design
 #' with a continuous outcome variable.  It provides estimates and CIs for the
 #' population mean difference between the repeated measures, the standardized

R/estimate_pdiff_ind_contrast.R

@@ -1,8 +1,7 @@
 #' Estimates for a multi-group study with a categorical outcome
 #' variable
 #'
-#' @description
-#' \loadmathjax
+#' @description \loadmathjax
 #' `estimate_pdiff_ind_contrast` is suitable for a multi-group design
 #' (between subjects) with a categorical outcome variable.  It accepts
 #' a user-defined set of contrast weights that allows estimation of any

R/estimate_pdiff_one.R

@@ -1,8 +1,7 @@
 #' Estimates for a single-group design with a categorical outcome
 #' variable compared to a reference or population value.
 #'
-#' @description
-#' \loadmathjax
+#' @description \loadmathjax
 #' `estimate_pdiff_one` is suitable for a single-group design
 #' (between subjects) with a categorical outcome variable.  It calculates
 #' the effect sizes with respect to a reference or population proportion

R/estimate_pdiff_paired.R

@@ -1,8 +1,7 @@
 #' Estimates for a repeated-measures study with two measures of a categorical
 #' variable
 #'
-#' @description
-#' \loadmathjax
+#' @description \loadmathjax
 #' `estimate_pdiff_paired` is suitable for a simple paired design
 #' with a categorical outcome variable.  It provides estimates and CIs for the
 #' population proportion difference between the repeated measures.  You can

R/estimate_pdiff_two.R

@@ -1,8 +1,7 @@
 #' Estimates for a two-group study with a categorical outcome variable
 #'
 #'
-#' @description
-#' \loadmathjax
+#' @description \loadmathjax
 #' `estimate_pdiff_two` is suitable for a simple two-group design
 #' with a categorical outcome variable.  It provides estimates and CIs for the
 #' difference in proportions between the two groups, the odds ratio, and phi.

R/estimate_rdiff_two.R

@@ -2,8 +2,7 @@
 #' two continuous outcome variables
 #'
 #'
-#' @description
-#' \loadmathjax
+#' @description \loadmathjax
 #' `estimate_rdiff_two` is suitable for a simple two-group design
 #' with two continuous outcome variables where you want to estimate the
 #' difference in the strength of the relationship between the two groups.

docs/pkgdown.yml

@@ -2,7 +2,7 @@ pandoc: 3.1.1
 pkgdown: 2.0.7
 pkgdown_sha: ~
 articles: {}
-last_built: 2024-03-11T15:48Z
+last_built: 2024-03-12T14:02Z
 urls:
   reference: https://rcalinjageman.github.io/esci/reference
   article: https://rcalinjageman.github.io/esci/articles