spellcheck and docs rebuild

mjskay · Mar 20, 2020 · 8edc520 · 8edc520
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diff --git a/.Rbuildignore b/.Rbuildignore
@@ -14,3 +14,4 @@
 ^figure$
 ^cache$
 ^cran-comments.md$
+^inst/WORDLIST$
diff --git a/DESCRIPTION b/DESCRIPTION
@@ -35,8 +35,9 @@ Suggests:
     stringi,
     DescTools
 License: GPL (>= 2)
+Language: en-US
 BugReports: https://github.com/mjskay/ARTool/issues/new
 URL: https://github.com/mjskay/ARTool
 VignetteBuilder: knitr
-RoxygenNote: 6.1.1
+RoxygenNote: 7.1.0
 Encoding: UTF-8
diff --git a/NEWS.md b/NEWS.md
@@ -4,6 +4,9 @@ Minor changes:
 
 * Forward-compatible fix for tests needed for when `stringsAsFactors` default
   becomes `FALSE` (in R 4).
+
+Bug fixes:
+
 * Fix for a bug in alignment that occurs with high-order interactions (4+)
   (thanks to Hidekazu Kaneko).
 
@@ -19,59 +22,59 @@ Minor changes:
 
 Minor changes:
 
-* Replace `lsmeans` with `emmeans` in code and docs due to lsmeans being deprecated
+* Replace `lsmeans` with `emmeans` in code and docs due to `lsmeans` being deprecated
 * Use `psych::d.ci` for Cohen's _d_ CIs in effect size vignette
 
 
 # ARTool 0.10.4
 
 Minor changes:
 
-* Reference phia vignette using function call instead of non-canonical URL
+* Reference `phia` vignette using function call instead of non-canonical URL
 * Cautionary note about standardized effect sizes in effect size vignette
-* Added testInteractions example as alternative in contrasts vignette
+* Added `testInteractions()` example as alternative in contrasts vignette
 
-Bugfixes:
+Bug fixes:
 
-* Dependency fixes for failed test at testthat/test.artlm.R:35 (our use of lsmeans in that
-test requires some additional packages only declared as "suggests" in lsmeans, so now
-we "suggest" them as well).
+* Dependency fixes for failed test at `testthat/test.artlm.R:35` (our use of `lsmeans()` in that
+test requires some additional packages only declared as "Suggests" in `lsmeans`, so now
+we "Suggest" them as well).
 
 
 # ARTool 0.10.1
 
 New features:
 
 * New vignette describing effect size estimates
-* Using lsmeans interactions argument instead of phia for interaction contrasts vignette
+* Using `lsmeans()` interactions argument instead of `phia` for interaction contrasts vignette
 
-Bugfixes:
+Bug fixes:
 
-* Require R >= 3.2 and lsmeans >= 2.22 to fix some bugs in earlier versions
+* Require R >= 3.2 and `lsmeans` >= 2.22 to fix some bugs in earlier versions
 
 
 # ARTool 0.10.0
 
 New features:
 
-* Support for Error() terms in model formulas (resulting models are run using aov())
+* Support for `Error()` terms in model formulas (resulting models are run using `aov()`)
 * Checks for numeric variables passed into formulas that may cause incorrect results (if the user intended data to be treated as categorical)
 * More detailed ANOVA tables
 * New vignette describing contrast tests, particularly for interactions (vignette("art-contrasts"))
 
-Bugfixes:
+Bug fixes:
 
 * Formulas now correctly support arbitrary expressions as terms (rather than just column names).
 
 
 # ARTool 0.9.5
 
-Testing fix for changes in upcoming version of lsmeans: round lsmeans p value tests to 5 decimal places to accommodate changes to Tukey adjustment
+Testing fix for changes in upcoming version of `lsmeans`: round `lsmeans` p value tests to 5 decimal places to accommodate changes to Tukey adjustment
 
 
 # ARTool 0.9.4
 
-Minor changes to testing based on updated version of testthat (0.10.0):
+Minor changes to testing based on updated version of `testthat` (0.10.0):
 
-* More closely follow recommended testthat usage
-* Skip tests requiring lsmeans if it is not installed
+* More closely follow recommended `testthat` usage
+* Skip tests requiring `lsmeans` if it is not installed
diff --git a/R/data.R b/R/data.R
@@ -1,15 +1,15 @@
 # documentation of datasets
-# 
+#
 # Author: mjskay
 ###############################################################################
 
 
 #' Aligned Rank Transformed Version of Higgins1990Table1
-#' 
+#'
 #' The ART version of \code{\link{Higgins1990Table1}} as produced by the
 #' original ARTool, used to test the correctness of \code{\link{art}} output.
-#' 
-#' 
+#'
+#'
 #' @name Higgins1990Table1.art
 #' @docType data
 #' @format A data frame with 36 observations on the following 10 variables.
@@ -33,20 +33,20 @@ NULL
 
 
 #' Synthetic 3x3 Factorial Randomized Experiment
-#' 
+#'
 #' Synthetic data from a balanced 3x3 factorial experiment with main effects,
 #' no interaction, and independent and identically distributed (i.i.d.) Normal
 #' errors.
-#' 
-#' 
+#'
+#'
 #' @name Higgins1990Table1
 #' @docType data
 #' @format A data frame with 36 observations on the following 4 variables.
-#' \describe{ 
+#' \describe{
 #'      \item{Subject}{a factor with levels \code{"s1"} .. \code{"s36"}}
 #'      \item{Row}{a factor with levels \code{"r1"} .. \code{"r3"}}
 #'      \item{Column}{a factor with levels \code{"c1"} .. \code{"c3"}}
-#'      \item{Response}{a numeric vector} 
+#'      \item{Response}{a numeric vector}
 #' }
 #' @seealso \code{\link{art}}, \code{\link{anova.art}}.
 #' @source Higgins, J. J., Blair, R. C. and Tashtoush, S. (1990). The aligned
@@ -55,40 +55,40 @@ NULL
 #' 185-195.
 #' @keywords datasets
 #' @examples
-#' 
+#'
 #' data(Higgins1990Table1)
-#' 
+#'
 #' ## run aligned-rank transform and ANOVA on the data
-#' ## Note: because there is only one observation per Subject 
-#' ## in this dataset, we do not need to include Subject as 
-#' ## a grouping term in this formula. Indeed, if we did, 
+#' ## Note: because there is only one observation per Subject
+#' ## in this dataset, we do not need to include Subject as
+#' ## a grouping term in this formula. Indeed, if we did,
 #' ## lmer would complain when we attempt the ANOVA.
 #' m <- art(Response ~ Row*Column, data=Higgins1990Table1)
 #' anova(m)
-#' 
+#'
 NULL
 
 
 #' Aligned Rank Transformed Version of Higgins1990Table5
-#' 
+#'
 #' The ART version of \code{\link{Higgins1990Table5}} as produced by the
 #' original ARTool, used to test the correctness of \code{\link{art}} output.
-#' 
-#' 
+#'
+#'
 #' @name Higgins1990Table5.art
 #' @docType data
 #' @format A data frame with 48 observations on the following 10 variables.
 #' \describe{
 #'      \item{Tray}{a factor with levels \code{"t1"} .. \code{"t12"}}
 #'      \item{Moisture}{a factor with levels \code{"m1"} .. \code{"m4"}}
-#'      \item{Fertilizer}{a factor with levels \code{"f1"} .. \code{"f4"}} 
+#'      \item{Fertilizer}{a factor with levels \code{"f1"} .. \code{"f4"}}
 #'      \item{DryMatter}{a numeric vector}
 #'      \item{aligned.DryMatter..for.Moisture}{a numeric vector}
 #'      \item{aligned.DryMatter..for.Fertilizer}{a numeric vector}
 #'      \item{aligned.DryMatter..for.Moisture.Fertilizer}{a numeric vector}
 #'      \item{ART.DryMatter..for.Moisture}{a numeric vector}
 #'      \item{ART.DryMatter..for.Fertilizer}{a numeric vector}
-#'      \item{ART.DryMatter..for.Moisture.Fertilizer}{a numeric vector} 
+#'      \item{ART.DryMatter..for.Moisture.Fertilizer}{a numeric vector}
 #' }
 #' @seealso \code{\link{Higgins1990Table5}}, \code{\link{art}}.
 #' @source Wobbrock, J. O., Findlater, L., Gergle, D., and Higgins, J. J.
@@ -99,25 +99,25 @@ NULL
 
 #' Split-plot Experiment Examining Effect of Moisture and Fertilizer on Dry
 #' Matter in Peat Pots
-#' 
+#'
 #' This dataset comes from a split-plot experiment examining \code{Tray}s of 4
 #' peat pots each. \code{Moisture} was varied between \code{Tray}s (i.e. it was
 #' the whole-plot treatment) and \code{Fertilizer} was varied within
 #' \code{Tray}s (i.e. it was the sub-plot treatment). The outcome measure was
 #' \code{DryMatter}.
-#' 
+#'
 #' This dataset, originally from Milliken & Johnson (1984), is reproduced here
 #' from Higgins \emph{et al.} (1990).
-#' 
-#' 
+#'
+#'
 #' @name Higgins1990Table5
 #' @docType data
 #' @format A data frame with 48 observations on the following 4 variables.
-#' \describe{ 
+#' \describe{
 #'      \item{Tray}{a factor with levels \code{"t1"} .. \code{"t12"}}
 #'      \item{Moisture}{a factor with levels \code{"m1"} .. \code{"m4"}}
-#'      \item{Fertilizer}{a factor with levels \code{"f1"} .. \code{"f4"}} 
-#'      \item{DryMatter}{a numeric vector} 
+#'      \item{Fertilizer}{a factor with levels \code{"f1"} .. \code{"f4"}}
+#'      \item{DryMatter}{a numeric vector}
 #' }
 #' @seealso See \code{\link{art}} for a more complete example. See also
 #' \code{\link{anova.art}}.
@@ -129,29 +129,29 @@ NULL
 #' Vol I: Designed Experiments}. Van Nostrand Reinhold Company, New York.
 #' @keywords datasets
 #' @examples
-#' 
+#'
 #' data(Higgins1990Table5)
-#' 		
+#'
 #' ## run aligned-rank transform and ANOVA on the data
 #' m <- art(DryMatter ~ Moisture*Fertilizer + (1|Tray), data=Higgins1990Table5)
 #' anova(m)
-#' 
+#'
 NULL
 
 
 #' Aligned Rank Transformed Version of HigginsABC
-#' 
+#'
 #' The ART version of \code{\link{HigginsABC}} as produced by the original
 #' ARTool, used to test the correctness of \code{\link{art}} output.
-#' 
-#' 
+#'
+#'
 #' @name HigginsABC.art
 #' @docType data
 #' @format A data frame with 16 observations on the following 19 variables.
-#' \describe{ 
-#'      \item{Subject}{a factor with levels \code{"s1"} .. \code{"s8"}} 
-#'      \item{A}{a factor with levels \code{"a1"} \code{"a2"}} 
-#'      \item{B}{a factor with levels \code{"b1"} \code{"b2"}} 
+#' \describe{
+#'      \item{Subject}{a factor with levels \code{"s1"} .. \code{"s8"}}
+#'      \item{A}{a factor with levels \code{"a1"} \code{"a2"}}
+#'      \item{B}{a factor with levels \code{"b1"} \code{"b2"}}
 #'      \item{C}{a factor with levels \code{"c1"} \code{"c2"}}
 #'      \item{Y}{a numeric vector}
 #'      \item{aligned.Y..for.A}{a numeric vector}
@@ -161,8 +161,8 @@ NULL
 #'      \item{aligned.Y..for.A.C}{a numeric vector}
 #'      \item{aligned.Y..for.B.C}{a numeric vector}
 #'      \item{aligned.Y..for.A.B.C}{a numeric vector}
-#'      \item{ART.Y..for.A}{a numeric vector} 
-#'      \item{ART.Y..for.B}{a numeric vector} 
+#'      \item{ART.Y..for.A}{a numeric vector}
+#'      \item{ART.Y..for.B}{a numeric vector}
 #'      \item{ART.Y..for.A.B}{a numeric vector}
 #'      \item{ART.Y..for.C}{a numeric vector}
 #'      \item{ART.Y..for.A.C}{a numeric vector}
@@ -177,21 +177,21 @@ NULL
 
 
 #' Synthetic 2x2x2 Mixed Design Experiment
-#' 
+#'
 #' Synthetic data from an experiment with two between-\code{Subject}s factors
 #' (\code{A} and \code{B}) having two levels each and one
 #' within-\code{Subject}s factor (\code{C}) with two levels.
-#' 
-#' 
+#'
+#'
 #' @name HigginsABC
 #' @docType data
 #' @format A data frame with 16 observations on the following 5 variables.
-#' \describe{ 
-#'      \item{Subject}{a factor with levels \code{"s1"} .. \code{"s8"}} 
-#'      \item{A}{a factor with levels \code{"a1"} \code{"a2"}} 
-#'      \item{B}{a factor with levels \code{"b1"} \code{"b2"}} 
+#' \describe{
+#'      \item{Subject}{a factor with levels \code{"s1"} .. \code{"s8"}}
+#'      \item{A}{a factor with levels \code{"a1"} \code{"a2"}}
+#'      \item{B}{a factor with levels \code{"b1"} \code{"b2"}}
 #'      \item{C}{a factor with levels \code{"c1"} \code{"c2"}}
-#'      \item{Y}{a numeric vector} 
+#'      \item{Y}{a numeric vector}
 #' }
 #' @seealso \code{\link{art}}, \code{\link{anova.art}}.
 #' @source Wobbrock, J. O., Findlater, L., Gergle, D., and Higgins, J. J.
@@ -200,7 +200,7 @@ NULL
 #' @examples
 #' \dontrun{
 #' data(HigginsABC, HigginsABC.art, package="ARTool")
-#' 
+#'
 #' ## run aligned-rank transform and ANOVA on the data
 #' m <- art(Y ~ A*B*C + Error(Subject), data=HigginsABC)
 #' anova(m)
@@ -209,10 +209,10 @@ NULL
 
 
 #' Synthetic Data Used in the Contrast Test Vignette
-#' 
+#'
 #' See (\code{vignette("art-contrasts")} for a description of this data.
-#' 
-#' 
+#'
+#'
 #' @name InteractionTestData
 #' @docType data
 #' @seealso \code{\link{art}}, \code{\link{anova.art}}.
@@ -222,4 +222,4 @@ NULL
 #' ## see this vignette
 #' vignette("art-contrasts")
 #' }
-NULL
+NULL
diff --git a/README.Rmd b/README.Rmd
@@ -53,7 +53,7 @@ devtools::install_github("mjskay/ARTool")
 
 The general approach to using ART is to transform your data using `art` , verify
 the ART procedure is appropriate to the dataset using `summary` , and then run an
-anova on the transformed data using `anova` .
+ANOVA on the transformed data using `anova` .
 
 First, let us load some example data:
 
@@ -155,6 +155,6 @@ DOI: [10.5281/zenodo.594511](http://dx.doi.org/10.5281/zenodo.594511).
 Wobbrock J, Findlater L, Gergle D and Higgins J (2011). "The Aligned
 Rank Transform for Nonparametric Factorial Analyses Using Only ANOVA
 Procedures." In _Proceedings of the ACM Conference on Human Factors in
-Computing Systems (CHI '11)_, Vancouver, British Columbia (May 7-12, 2011). 
+Computing Systems (CHI 2011)_, Vancouver, British Columbia (May 7-12, 2011). 
 New York: ACM Press, pp. 143-146. <http://depts.washington.edu/aimgroup/proj/art/>.
 DOI: [10.1145/1978942.1978963](http://dx.doi.org/10.1145/1978942.1978963).