diff --git a/.Rbuildignore b/.Rbuildignore index 27cb7e0..a9e292e 100755 --- a/.Rbuildignore +++ b/.Rbuildignore @@ -14,3 +14,4 @@ ^figure$ ^cache$ ^cran-comments.md$ +^inst/WORDLIST$ diff --git a/DESCRIPTION b/DESCRIPTION index 440767b..2c186d5 100755 --- 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 index c0aa957..86815bc 100755 --- 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). @@ -19,7 +22,7 @@ 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 @@ -27,15 +30,15 @@ Minor changes: 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 @@ -43,35 +46,35 @@ we "suggest" them as well). 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 index f27d0fa..5446b45 100755 --- 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 \ No newline at end of file +NULL diff --git a/README.Rmd b/README.Rmd index b2e8071..4d2aa8b 100755 --- 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. . DOI: [10.1145/1978942.1978963](http://dx.doi.org/10.1145/1978942.1978963). diff --git a/README.md b/README.md index 17cb295..1454a8f 100755 --- a/README.md +++ b/README.md @@ -4,13 +4,15 @@ ARTool: R Package for the Aligned Rank Transform for Nonparametric Factorial ANO [![Build Status](https://travis-ci.org/mjskay/ARTool.png?branch=master)](https://travis-ci.org/mjskay/ARTool) [![CRAN\_Status\_Badge](http://www.r-pkg.org/badges/version/ARTool)](https://CRAN.R-project.org/package=ARTool) -[![GPL >= +[![GPL \>= 2](https://img.shields.io/badge/GPL-%E2%89%A52-brightgreen.svg)](https://cran.r-project.org/web/licenses/GPL-3) [![DOI](https://zenodo.org/badge/19809/mjskay/ARTool.svg)](https://zenodo.org/badge/latestdoi/19809/mjskay/ARTool) [![DOI](https://img.shields.io/badge/DOI-10.1145%2F1978942.1978963-blue.svg)](http://dx.doi.org/10.1145/1978942.1978963) -*Matthew Kay, University of Washington *
*Jacob O. -Wobbrock, University of Washington * +*Matthew Kay, University of Washington +*
+*Jacob O. Wobbrock, University of Washington +* ARTool is an R package implementing the Aligned Rank Transform for conducting nonparametric analyses of variance on factorial models. This @@ -56,7 +58,7 @@ Example 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` . +, and then run an ANOVA on the transformed data using `anova` . First, let us load some example data: @@ -140,7 +142,7 @@ summary(m) ## 0 0 0 0 0 0 We see that the columns sums of aligned responses and the F values of -ANOVAs on aligned responses not of interest are all ~0, indicating that +ANOVAs on aligned responses not of interest are all \~0, indicating that the alignment correctly “stripped out” effects not of interest. Thus, we can apply the ANOVA on the transformed data. @@ -210,22 +212,24 @@ Problems -------- Should you encounter any issues with this package, contact Matthew Kay -(). If you have found a bug, please file it +(). +If you have found a bug, please file it [here](https://github.com/mjskay/ARTool/issues/new) with minimal code to reproduce the issue. Citations --------- -Kay M and Wobbrock J (2019). *ARTool: Aligned Rank Transform for -Nonparametric Factorial ANOVAs*. R package version 0.10.6.9000, -. DOI: -[10.5281/zenodo.594511](http://dx.doi.org/10.5281/zenodo.594511). +Kay M and Wobbrock J (2020). *ARTool: Aligned Rank Transform for +Nonparametric Factorial ANOVAs*. R package version 0.10.7, +https://github.com/mjskay/ARTool. +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, +Computing Systems (CHI 2011)*, Vancouver, British Columbia (May 7-12, 2011). New York: ACM Press, pp. 143-146. -. DOI: +http://depts.washington.edu/aimgroup/proj/art/. +DOI: [10.1145/1978942.1978963](http://dx.doi.org/10.1145/1978942.1978963). diff --git a/inst/WORDLIST b/inst/WORDLIST new file mode 100644 index 0000000..f354160 --- /dev/null +++ b/inst/WORDLIST @@ -0,0 +1,25 @@ +ACM +aimgroup +et al +depts +DOI +edu +Findlater +Gergle +github +Kaneko +Milliken +mjskay +Nostrand +Hidekazu +homoscedasticity +http +https +interpretable +zenodo +washington +Tashtoush +pre +ish +proj +HigginsABC diff --git a/man/Higgins1990Table1.Rd b/man/Higgins1990Table1.Rd index 34612f7..6ec865e 100755 --- a/man/Higgins1990Table1.Rd +++ b/man/Higgins1990Table1.Rd @@ -4,13 +4,15 @@ \name{Higgins1990Table1} \alias{Higgins1990Table1} \title{Synthetic 3x3 Factorial Randomized Experiment} -\format{A data frame with 36 observations on the following 4 variables. -\describe{ +\format{ +A data frame with 36 observations on the following 4 variables. +\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} +} +} \source{ Higgins, J. J., Blair, R. C. and Tashtoush, S. (1990). The aligned rank transform procedure. \emph{Proceedings of the Conference on Applied @@ -27,9 +29,9 @@ errors. 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) diff --git a/man/Higgins1990Table1.art.Rd b/man/Higgins1990Table1.art.Rd index 33081f5..de46d34 100755 --- a/man/Higgins1990Table1.art.Rd +++ b/man/Higgins1990Table1.art.Rd @@ -4,7 +4,8 @@ \name{Higgins1990Table1.art} \alias{Higgins1990Table1.art} \title{Aligned Rank Transformed Version of Higgins1990Table1} -\format{A data frame with 36 observations on the following 10 variables. +\format{ +A data frame with 36 observations on the following 10 variables. \describe{ \item{Subject}{a factor with levels \code{"s1"} .. \code{"s36"}} \item{Row}{a factor with levels \code{"r1"} .. \code{"r3"}} @@ -16,7 +17,8 @@ \item{ART.Response..for.Row}{a numeric vector} \item{ART.Response..for.Column}{a numeric vector} \item{ART.Response..for.Row.Column}{a numeric vector} -}} +} +} \source{ Wobbrock, J. O., Findlater, L., Gergle, D., and Higgins, J. J. \emph{ARTool}. \url{http://depts.washington.edu/aimgroup/proj/art/}. diff --git a/man/Higgins1990Table5.Rd b/man/Higgins1990Table5.Rd index 2e5f5e7..6c6811f 100755 --- a/man/Higgins1990Table5.Rd +++ b/man/Higgins1990Table5.Rd @@ -5,13 +5,15 @@ \alias{Higgins1990Table5} \title{Split-plot Experiment Examining Effect of Moisture and Fertilizer on Dry Matter in Peat Pots} -\format{A data frame with 48 observations on the following 4 variables. -\describe{ +\format{ +A data frame with 48 observations on the following 4 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{DryMatter}{a numeric vector} -}} + \item{Fertilizer}{a factor with levels \code{"f1"} .. \code{"f4"}} + \item{DryMatter}{a numeric vector} +} +} \source{ Milliken, G.A., Johnson, D.E. (1984). \emph{Analysis of Messy Data Vol I: Designed Experiments}. Van Nostrand Reinhold Company, New York. @@ -30,7 +32,7 @@ from Higgins \emph{et al.} (1990). \examples{ data(Higgins1990Table5) - + ## run aligned-rank transform and ANOVA on the data m <- art(DryMatter ~ Moisture*Fertilizer + (1|Tray), data=Higgins1990Table5) anova(m) diff --git a/man/Higgins1990Table5.art.Rd b/man/Higgins1990Table5.art.Rd index 0b3cca6..11abed3 100755 --- a/man/Higgins1990Table5.art.Rd +++ b/man/Higgins1990Table5.art.Rd @@ -4,19 +4,21 @@ \name{Higgins1990Table5.art} \alias{Higgins1990Table5.art} \title{Aligned Rank Transformed Version of Higgins1990Table5} -\format{A data frame with 48 observations on the following 10 variables. +\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} +} +} \source{ Wobbrock, J. O., Findlater, L., Gergle, D., and Higgins, J. J. \emph{ARTool}. \url{http://depts.washington.edu/aimgroup/proj/art/}. diff --git a/man/HigginsABC.Rd b/man/HigginsABC.Rd index a872f2b..7b6dc59 100755 --- a/man/HigginsABC.Rd +++ b/man/HigginsABC.Rd @@ -4,14 +4,16 @@ \name{HigginsABC} \alias{HigginsABC} \title{Synthetic 2x2x2 Mixed Design Experiment} -\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"}} +\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"}} \item{C}{a factor with levels \code{"c1"} \code{"c2"}} - \item{Y}{a numeric vector} -}} + \item{Y}{a numeric vector} +} +} \source{ Wobbrock, J. O., Findlater, L., Gergle, D., and Higgins, J. J. \emph{ARTool}. \url{http://depts.washington.edu/aimgroup/proj/art/}. diff --git a/man/HigginsABC.art.Rd b/man/HigginsABC.art.Rd index d90a2a4..7741655 100755 --- a/man/HigginsABC.art.Rd +++ b/man/HigginsABC.art.Rd @@ -4,11 +4,12 @@ \name{HigginsABC.art} \alias{HigginsABC.art} \title{Aligned Rank Transformed Version of HigginsABC} -\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"}} +\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"}} \item{C}{a factor with levels \code{"c1"} \code{"c2"}} \item{Y}{a numeric vector} \item{aligned.Y..for.A}{a numeric vector} @@ -18,14 +19,15 @@ \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} \item{ART.Y..for.B.C}{a numeric vector} \item{ART.Y..for.A.B.C}{a numeric vector} -}} +} +} \source{ Wobbrock, J. O., Findlater, L., Gergle, D., and Higgins, J. J. \emph{ARTool}. \url{http://depts.washington.edu/aimgroup/proj/art/}. diff --git a/man/anova.art.Rd b/man/anova.art.Rd index 0fbdcbc..4ffabf9 100755 --- a/man/anova.art.Rd +++ b/man/anova.art.Rd @@ -5,9 +5,15 @@ \alias{print.anova.art} \title{Aligned Rank Transform Analysis of Variance} \usage{ -\method{anova}{art}(object, response = c("art", "aligned"), - type = c("III", "II", "I", 3, 2, 1), factor.contrasts = "contr.sum", - test = c("F", "Chisq"), all.rows = FALSE, ...) +\method{anova}{art}( + object, + response = c("art", "aligned"), + type = c("III", "II", "I", 3, 2, 1), + factor.contrasts = "contr.sum", + test = c("F", "Chisq"), + all.rows = FALSE, + ... +) \method{print}{anova.art}(x, verbose = FALSE, digits = 5, ...) } diff --git a/man/art.Rd b/man/art.Rd index 5f5cd5a..2ff1726 100755 --- a/man/art.Rd +++ b/man/art.Rd @@ -4,9 +4,12 @@ \alias{art} \title{Aligned Rank Transform} \usage{ -art(formula, data, +art( + formula, + data, rank.comparison.digits = -floor(log10(.Machine$double.eps^0.5)), - check.errors.are.factors = TRUE) + check.errors.are.factors = TRUE +) } \arguments{ \item{formula}{A factorial formula with optional grouping terms or error diff --git a/man/artlm.Rd b/man/artlm.Rd index a1f9aeb..9e33f75 100755 --- a/man/artlm.Rd +++ b/man/artlm.Rd @@ -4,8 +4,13 @@ \alias{artlm} \title{Per-Term Linear Model from Aligned Rank Transformed Data} \usage{ -artlm(m, term, response = c("art", "aligned"), - factor.contrasts = "contr.sum", ...) +artlm( + m, + term, + response = c("art", "aligned"), + factor.contrasts = "contr.sum", + ... +) } \arguments{ \item{m}{An object of class \code{\link{art}}.} diff --git a/vignettes/art-contrasts.Rmd b/vignettes/art-contrasts.Rmd index 8d3de74..4da90d3 100755 --- a/vignettes/art-contrasts.Rmd +++ b/vignettes/art-contrasts.Rmd @@ -192,7 +192,7 @@ which if we interpret in the same way as the linear model is obviously incorrect The key here is to understand that ART is reporting differences with the main effects subtracted out. That is, the `A,C - A,D` effect is something like the difference between this combination of levels if we first -subtracted out the effect of `C - D`. We can see this if we take the ART estimate for `C - D` in the emmeans for `X2` above (`-123.13`) and the +subtracted out the effect of `C - D`. We can see this if we take the ART estimate for `C - D` in the `emmeans` output for `X2` above (`-123.13`) and the ART estimate for `A,C - A,D` (`125.12`) here, we can get approximate an estimate of the difference (`-123.13 + 125.12 == 1.99`) that is consistent with the expected 0 (given the SE here).