spelling fixes

R/anova.art.R

@@ -1,35 +1,35 @@
 # ANOVAs for art objects
-# 
+#
 # Author: mjskay
 ###############################################################################
 
 
 #' Aligned Rank Transform Analysis of Variance
-#' 
+#'
 #' Conduct analyses of variance on aligned rank transformed data.
-#' 
+#'
 #' This function runs several ANOVAs: one for each fixed effect term in the
 #' model \code{object}. In each ANOVA, the independent variables are the same,
 #' but the response is aligned by a different fixed effect term (if response is
 #' "aligned") or aligned and ranked by that fixed effect term (if response is
 #' "art"). These models are generated using \code{\link{artlm}}.
-#' 
+#'
 #' From each model, only the relevant output rows are kept (unless
 #' \code{all.rows} is \code{TRUE}, in which case all rows are kept).
-#' 
+#'
 #' When \code{response} is \code{"art"} (the default), only one row is kept
 #' from each ANOVA: the row corresponding to fixed effect term the response was
 #' aligned and ranked by. These results represent nonparametric tests of
 #' significance for the effect of each term on the original response variable.
-#' 
+#'
 #' When \code{response} is \code{"aligned"}, all rows \emph{except} the row
 #' corresponding to the fixed effect term the response was aligned by are kept.
 #' If the ART procedure is appropriate for this data, these tests should have
 #' all effects "stripped out", and have an F value of ~0. If that is not the
 #' case, another analysis should be considered. This diagnostic is tested by
 #' \code{\link{summary.art}} and a warning generated if the F values are not
 #' all approximately 0.
-#' 
+#'
 #' @name anova.art
 #' @rdname anova.art
 #' @aliases anova.art print.anova.art
@@ -55,9 +55,9 @@
 #' (\code{FALSE}), shows only the rows that are relevant depending on the type
 #' of \code{response}.
 #' @param x An object of class \code{\link{art}}.
-#' @param verbose When \code{TRUE}, sums of squares and reisdual sum of squares
-#' in addition to degrees of freedom are printed in some Anova types (e.g.
-#' repeated measures Anovas). Default \code{FALSE}, for brevity.
+#' @param verbose When \code{TRUE}, sums of squares and residual sum of squares
+#' in addition to degrees of freedom are printed in some ANOVA types (e.g.
+#' repeated measures ANOVAs). Default \code{FALSE}, for brevity.
 #' @param digits Digits of output in printed table; see \code{\link{print}}.
 #' @param \dots Additional arguments passed to \code{\link{Anova}} or
 #' \code{\link{anova}} by \code{anova.art} or to \code{\link{print}} by
@@ -72,91 +72,91 @@
 #' Human Factors in Computing Systems (CHI '11)}.  Vancouver, British Columbia
 #' (May 7-12, 2011). New York: ACM Press, pp. 143-146.
 #' @keywords nonparametric
-#' 
+#'
 #' @export
-anova.art = function(object, 
+anova.art = function(object,
     response=c("art", "aligned"),
-    type=c("III", "II", "I", 3, 2, 1), 
+    type=c("III", "II", "I", 3, 2, 1),
     factor.contrasts="contr.sum",
-    test=c("F", "Chisq"),  
+    test=c("F", "Chisq"),
     all.rows=FALSE,
     ...
 ) {
     #sensible names for generic parameters
     m = object
-    
+
     #match enum arguments
     response = match.arg(response)
     type = as.character(type)
     type = match.arg(type)
     test = match.arg(test)
-    
+
     #get transformed responses based on response type requested
-    responses = switch(response, 
-        aligned=m$aligned, 
+    responses = switch(response,
+        aligned=m$aligned,
         art=m$aligned.ranks)
-    
+
     #determine anova type to use
     type = if (type %in% c(1,"I")) "I"
     else if (type %in% c(2,"II")) "II"
     else if (type %in% c(3,"III")) "III"
-        
+
     #are we going to need to show the term we aligned by
     #for each row of the output?
     show.aligned.by.term = response == "aligned" || all.rows
-    
+
     #run linear models and anovas
     df = m$data
     anovas = NULL
-    table.description = "" 
+    table.description = ""
     for (j in 1:ncol(responses)) {	#can't use ldply here because it appears to drop row names when binding rows
         aligned.by.term = colnames(responses)[[j]]
-        
+
         #get linear model
         m.l = artlm(m, aligned.by.term, response=response, factor.contrasts=factor.contrasts)
-        
-        #run anova and extract desired results 
+
+        #run anova and extract desired results
         anova.j = flat.anova(m.l, type=type, test=test, ...)
         if (j == 1) table.description = attr(anova.j, "description")
-        
+
         #extract desired result rows from anova
         #for art, this is the one row correponding to the effect we aligned and ranked by
-        #for aligned, this is every effect *except* the one we aligned and ranked by 
+        #for aligned, this is every effect *except* the one we aligned and ranked by
         if (!all.rows) {
             include.row = anova.j$Term == aligned.by.term
             if (response == "aligned") include.row = !include.row
             anova.j = anova.j[include.row,]
         }
-        
+
         #Add "Aligned By" column when needed to disambiguate
-        if (nrow(anova.j) > 0) {	
-            #if only one fixed effect we can get no rows here, e.g. if response="aligned" 
+        if (nrow(anova.j) > 0) {
+            #if only one fixed effect we can get no rows here, e.g. if response="aligned"
             #and all.rows=FALSE, so the above guard is necessary
             if (show.aligned.by.term) {
                 anova.j = cbind(anova.j[,1,drop=FALSE], `Aligned By`=aligned.by.term, anova.j[,-1,drop=FALSE])
             }
         }
-        
+
         anovas = rbind(anovas, anova.j)
     }
-    
+
     #fill in the rest of the anova table metadata and return
     class(anovas) = c("anova.art", "anova", "data.frame")
-    attr(anovas, "model") = 
-        if (m$n.grouping.terms > 0) "lmer" 
-        else if (m$n.error.terms > 0) "aov" 
+    attr(anovas, "model") =
+        if (m$n.grouping.terms > 0) "lmer"
+        else if (m$n.error.terms > 0) "aov"
         else "lm"
     attr(anovas, "table.description") = table.description
     attr(anovas, "response") = response
     attr(anovas, "response.term") = colnames(m$cell.means)[1]
-    anovas	
+    anovas
 }
 
 ### Generate p stars for a vector of p values
 #' @importFrom stats symnum
 p.stars = function(p.values) {
-    unclass(symnum(p.values, corr = FALSE, na = FALSE, cutpoints = c(0, 
-                            0.001, 0.01, 0.05, 0.1, 1), symbols = c("***", "**", 
+    unclass(symnum(p.values, corr = FALSE, na = FALSE, cutpoints = c(0,
+                            0.001, 0.01, 0.05, 0.1, 1), symbols = c("***", "**",
                             "*", ".", " ")))
 }
 
@@ -173,7 +173,7 @@ print.anova.art = function(x, verbose=FALSE, digits=5, ...) {
         lmer = "Mixed Effects (lmer)\n",
     ))
     cat(sep="", "Response: ", attr(x, "response"), "(", attr(x, "response.term"), ")\n\n")
-    
+
     #format p values
     p.col = last(which(grepl("^(P|Pr)\\(", names(x))))
     stars.legend = if (!is.na(p.col)) {
@@ -193,13 +193,13 @@ print.anova.art = function(x, verbose=FALSE, digits=5, ...) {
     #abbreviate columns
     if (!is.null(x$Error)) x$Error %<>% abbreviate(5)
     if (!is.null(x$`Aligned By`)) x$`Aligned By` %<>% abbreviate(10)
-    
-    #drop "Sum Sq" (etc) columns when not doing verbose output 
+
+    #drop "Sum Sq" (etc) columns when not doing verbose output
     if (!verbose) x %<>% select(everything(), -contains("Sum Sq"), -contains("Mean Sq"))
-    
+
     #print table
     print.data.frame(x, digits=digits, ...)
-    
+
     #print legend
     if (!is.null(stars.legend)) {
         cat("---\nSignif. codes:  ", stars.legend, "\n")

R/art.R

@@ -41,9 +41,9 @@
 #' terms (but not both). Should be a formula with a single response variable
 #' (left-hand side) and one or more terms with all interactions on the
 #' right-hand side, e.g. \code{y ~ x} or \code{y ~ a*b*c} or \code{y ~ a + b +
-#' b:c}. If you want to run a mixed effects Anova on the transformed data using
+#' b:c}. If you want to run a mixed effects ANOVA on the transformed data using
 #' \code{\link{lmer}}, you can include grouping terms, as in \code{y ~ a*b*c +
-#' (1|d)}.  If you want to run a repeated measures Anova using
+#' (1|d)}.  If you want to run a repeated measures ANOVA using
 #' \code{\link{aov}}, you can include error terms, as in \code{y ~ a*b*c +
 #' Error(d)}. See 'Details'.
 #' @param data An optional data frame containing the variables in the model.