added Freeman et al. (2010) data

Thanks to Andrew Heathcote

DESCRIPTION

@@ -43,11 +43,12 @@ URL: https://github.com/singmann/afex
 License: GPL (>=3)
 Encoding: UTF-8
 VignetteBuilder: knitr
-Authors@R: c(person(given="Henrik", family="Singmann", role=c("aut", "cre"), email="singmann+afex@gmail.com"),
-              person(given="Ben", family="Bolker", role=c("aut")), person(given="Jake", family="Westfall", role=c("aut")),
-              person(given="Frederik", family="Aust", role=c("aut")), person(given="Søren", family="Højsgaard",
-              role=c("ctb")), person(given="John", family="Fox", role=c("ctb")), person(given="Michael A.",
-              family="Lawrence", role=c("ctb")), person(given="Ulf", family="Mertens", role=c("ctb")) )
-Version: 0.17-0
-Date: 2016-04-12
+Authors@R: c(person(given="Henrik", family="Singmann", role=c("aut", "cre"),
+            email="singmann+afex@gmail.com"), person(given="Ben", family="Bolker", role=c("aut")),
+            person(given="Jake", family="Westfall", role=c("aut")), person(given="Frederik", family="Aust",
+            role=c("aut")), person(given="Søren", family="Højsgaard", role=c("ctb")), person(given="John",
+            family="Fox", role=c("ctb")), person(given="Michael A.", family="Lawrence", role=c("ctb")),
+            person(given="Ulf", family="Mertens", role=c("ctb")) )
+Version: 0.17-1
+Date: 2016-04-27
 RoxygenNote: 5.0.1

R/afex-package.R

@@ -3,8 +3,8 @@
 #' \tabular{ll}{
 #' Package: \tab afex\cr
 #' Type: \tab Package\cr
-#' Version: \tab 0.17-0\cr
-#' Date: \tab 2016-04-12\cr
+#' Version: \tab 0.17-1\cr
+#' Date: \tab 2016-04-27\cr
 #' Depends: \tab R (>= 3.1.0), lme4 (>= 1.1-8), reshape2, lsmeans (>= 2.17)\cr
 #' Encoding: \tab UTF-8\cr
 #' License: \tab GPL (>=3)\cr

R/fhch2010-data.R

@@ -0,0 +1,35 @@
+#' Data from Freeman, Heathcote, Chalmers, & Hockley (2010)
+#'
+#' Lexical decision and word naming latencies for 300 words and 300 nonwords presented in Freeman, Heathcote, Chalmers, and Hockley (2010). The study had one between-subjects factors, \code{"task"} with two levels (\code{"naming"} or \code{"lexdec"}), and four within-subjects factors: \code{"stimulus"} type with two levels (\code{"word"} or \code{"nonword"}), word \code{"density"} and word \code{"frequency"} each with two levels (\code{"low"} and \code{"high"}) and stimulus \code{"length"} with three levels (4, 5, and 6).
+#' 
+#'  In the lexical-decision condition (N = 25), subjects indicated whether each item was a word or a nonword, by pressing either the left (labeled word) or right (labeled nonword) outermost button on a 6-button response pad. The next study item appeared immediately after the lexical decision response was given. In the naming condition (N = 20), subjects were asked to name each item aloud, and items remained on screen for 3 s. Naming time was recorded by a voice key.
+#' 
+#' Items consisted of 300 words, 75 in each set making up a factorial combination of high and low density and frequency, and 300 nonwords, with equal numbers of 4, 5, and 6 letter items in each set.
+#' 
+#'
+#' @docType data
+#' @keywords dataset
+#' @name fhch2010
+#' @usage fhch2010
+#' @format A \code{data.frame} with 13,222 obs. of 9 variables:
+#' \describe{
+#'  \item{id}{participant id, \code{factor}}
+#'  \item{task}{\code{factor} with two levels indicating which task was performed: \code{"naming"} or \code{"lexdec"}}
+#'  \item{stimulus}{\code{factor} indicating whether the shown stimulus was a \code{"word"} or \code{"nonword"}}
+#'  \item{density}{\code{factor} indicating the neighborhood density of presented items with two levels: \code{"low"} and \code{"high"}. Density is defined as the number of words that differ from a base word by one letter or phoneme.}
+#'  \item{frequency}{\code{factor} indicating the word frequency of presented items with two levels: \code{"low"} (i.e., words that occur less often in natural language) and \code{"high"} (i.e., words that occur more often in natural language).}
+#'  \item{length}{\code{factor} with 3 levels (4, 5, or 6) indicating the number of characters of presented stimuli.}
+#'  \item{item}{\code{factor} with 600 levels: 300 words and 300 nonwords}
+#'  \item{rt}{response time in seconds}
+#'  \item{log_rt}{natural logarithm of response time in seconds}
+#'  \item{correct}{boolean indicating whether or not the response in the lexical decision task was correct or incorrect (incorrect responses of the naming task are not part of the data).}
+#' }
+#' @source Freeman, E., Heathcote, A., Chalmers, K., & Hockley, W. (2010). Item effects in recognition memory for words. Journal of Memory and Language, 62(1), 1-18. http://doi.org/10.1016/j.jml.2009.09.004
+#'
+#' @encoding UTF-8
+#'
+#' @example examples/examples.fhch2010.R
+NULL
+
+
+

dev.R

@@ -34,7 +34,7 @@ R.libs <- "./packages/library"
 closeAllConnections()
 roxy.package(
 	pck.source.dir = pkg.src.dir,
-	pck.version = "0.17-0",
+	pck.version = "0.17-1",
 	pck.description = data.frame(
 		Package = "afex",
 		Type = "Package",

examples/examples.fhch2010.R

@@ -0,0 +1,19 @@
+
+data("fhch2010")
+str(fhch2010)
+
+a1 <- aov_ez("id", "log_rt", fhch2010, between = "task", within = c("density", "frequency", "length", "stimulus"))
+nice(a1)
+
+lsmip(a1, frequency~length|task+stimulus)
+
+lsmip(a1, frequency~density|task+stimulus)
+
+
+a2 <- aov_ez("id", "rt", fhch2010, between = "task", within = c("density", "frequency", "length", "stimulus"))
+nice(a2)
+
+lsmip(a2, frequency~length|task+stimulus)
+
+lsmip(a2, frequency~density|task+stimulus)
+