R/ttestones.h.R
In jamovi/Rjamovi: The 'jamovi' Analyses
Defines functions
ttestOneS
# This file is automatically generated, you probably don't want to edit this
ttestOneSOptions <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"ttestOneSOptions",
inherit = jmvcore::Options,
public = list(
initialize = function(
vars = NULL,
students = TRUE,
bf = FALSE,
bfPrior = 0.707,
wilcoxon = FALSE,
testValue = 0,
hypothesis = "dt",
norm = FALSE,
qq = FALSE,
meanDiff = FALSE,
ci = FALSE,
ciWidth = 95,
effectSize = FALSE,
ciES = FALSE,
ciWidthES = 95,
desc = FALSE,
plots = FALSE,
miss = "perAnalysis",
mann = FALSE, ...) {
super$initialize(
package="jmv",
name="ttestOneS",
requiresData=TRUE,
...)
private$..vars <- jmvcore::OptionVariables$new(
"vars",
vars,
suggested=list(
"continuous"),
permitted=list(
"numeric"),
rejectInf=FALSE)
private$..students <- jmvcore::OptionBool$new(
"students",
students,
default=TRUE)
private$..bf <- jmvcore::OptionBool$new(
"bf",
bf,
default=FALSE)
private$..bfPrior <- jmvcore::OptionNumber$new(
"bfPrior",
bfPrior,
default=0.707,
min=0.5,
max=2)
private$..wilcoxon <- jmvcore::OptionBool$new(
"wilcoxon",
wilcoxon,
default=FALSE)
private$..testValue <- jmvcore::OptionNumber$new(
"testValue",
testValue,
default=0)
private$..hypothesis <- jmvcore::OptionList$new(
"hypothesis",
hypothesis,
options=list(
"dt",
"gt",
"lt"),
default="dt")
private$..norm <- jmvcore::OptionBool$new(
"norm",
norm,
default=FALSE)
private$..qq <- jmvcore::OptionBool$new(
"qq",
qq,
default=FALSE)
private$..meanDiff <- jmvcore::OptionBool$new(
"meanDiff",
meanDiff,
default=FALSE)
private$..ci <- jmvcore::OptionBool$new(
"ci",
ci,
default=FALSE)
private$..ciWidth <- jmvcore::OptionNumber$new(
"ciWidth",
ciWidth,
min=50,
max=99.9,
default=95)
private$..effectSize <- jmvcore::OptionBool$new(
"effectSize",
effectSize,
default=FALSE)
private$..ciES <- jmvcore::OptionBool$new(
"ciES",
ciES,
default=FALSE)
private$..ciWidthES <- jmvcore::OptionNumber$new(
"ciWidthES",
ciWidthES,
min=50,
max=99.9,
default=95)
private$..desc <- jmvcore::OptionBool$new(
"desc",
desc,
default=FALSE)
private$..plots <- jmvcore::OptionBool$new(
"plots",
plots,
default=FALSE)
private$..miss <- jmvcore::OptionList$new(
"miss",
miss,
options=list(
"perAnalysis",
"listwise"),
default="perAnalysis")
private$..mann <- jmvcore::OptionBool$new(
"mann",
mann,
default=FALSE,
hidden=TRUE)
self$.addOption(private$..vars)
self$.addOption(private$..students)
self$.addOption(private$..bf)
self$.addOption(private$..bfPrior)
self$.addOption(private$..wilcoxon)
self$.addOption(private$..testValue)
self$.addOption(private$..hypothesis)
self$.addOption(private$..norm)
self$.addOption(private$..qq)
self$.addOption(private$..meanDiff)
self$.addOption(private$..ci)
self$.addOption(private$..ciWidth)
self$.addOption(private$..effectSize)
self$.addOption(private$..ciES)
self$.addOption(private$..ciWidthES)
self$.addOption(private$..desc)
self$.addOption(private$..plots)
self$.addOption(private$..miss)
self$.addOption(private$..mann)
}),
active = list(
vars = function() private$..vars$value,
students = function() private$..students$value,
bf = function() private$..bf$value,
bfPrior = function() private$..bfPrior$value,
wilcoxon = function() private$..wilcoxon$value,
testValue = function() private$..testValue$value,
hypothesis = function() private$..hypothesis$value,
norm = function() private$..norm$value,
qq = function() private$..qq$value,
meanDiff = function() private$..meanDiff$value,
ci = function() private$..ci$value,
ciWidth = function() private$..ciWidth$value,
effectSize = function() private$..effectSize$value,
ciES = function() private$..ciES$value,
ciWidthES = function() private$..ciWidthES$value,
desc = function() private$..desc$value,
plots = function() private$..plots$value,
miss = function() private$..miss$value,
mann = function() private$..mann$value),
private = list(
..vars = NA,
..students = NA,
..bf = NA,
..bfPrior = NA,
..wilcoxon = NA,
..testValue = NA,
..hypothesis = NA,
..norm = NA,
..qq = NA,
..meanDiff = NA,
..ci = NA,
..ciWidth = NA,
..effectSize = NA,
..ciES = NA,
..ciWidthES = NA,
..desc = NA,
..plots = NA,
..miss = NA,
..mann = NA)
)
ttestOneSResults <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"ttestOneSResults",
inherit = jmvcore::Group,
active = list(
ttest = function() private$.items[["ttest"]],
normality = function() private$.items[["normality"]],
descriptives = function() private$.items[["descriptives"]],
plots = function() private$.items[["plots"]],
qq = function() private$.items[["qq"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="",
title="One Sample T-Test")
self$add(jmvcore::Table$new(
options=options,
name="ttest",
title="One Sample T-Test",
rows="(vars)",
clearWith=list(
"hypothesis",
"testValue",
"miss",
"bfPrior",
"ciWidth",
"ciWidthES"),
columns=list(
list(
`name`="var[stud]",
`title`="",
`content`="($key)",
`type`="text",
`combineBelow`=TRUE,
`visible`="(students)"),
list(
`name`="name[stud]",
`title`="",
`type`="text",
`content`="Student's t",
`visible`="(students)"),
list(
`name`="stat[stud]",
`title`="Statistic",
`type`="number",
`visible`="(students)"),
list(
`name`="err[stud]",
`title`="error %",
`type`="number",
`visible`="(students && bf)",
`content`=""),
list(
`name`="df[stud]",
`title`="df",
`type`="number",
`visible`="(students)"),
list(
`name`="p[stud]",
`title`="p",
`type`="number",
`format`="zto,pvalue",
`visible`="(students)"),
list(
`name`="md[stud]",
`title`="Mean difference",
`type`="number",
`visible`="(meanDiff && students)"),
list(
`name`="cil[stud]",
`title`="Lower",
`type`="number",
`visible`="(ci && meanDiff && students)"),
list(
`name`="ciu[stud]",
`title`="Upper",
`type`="number",
`visible`="(ci && meanDiff && students)"),
list(
`name`="esType[stud]",
`title`="",
`content`="Cohen's d",
`type`="text",
`visible`="(effectSize && students)"),
list(
`name`="es[stud]",
`title`="Effect Size",
`type`="number",
`visible`="(effectSize && students)"),
list(
`name`="ciles[stud]",
`title`="Lower",
`type`="number",
`visible`="(ciES && effectSize && students)"),
list(
`name`="ciues[stud]",
`title`="Upper",
`type`="number",
`visible`="(ciES && effectSize && students)"),
list(
`name`="var[bf]",
`title`="",
`content`="($key)",
`type`="text",
`combineBelow`=TRUE,
`visible`="(bf)"),
list(
`name`="name[bf]",
`title`="",
`type`="text",
`content`="Bayes factor\u2081\u2080",
`visible`="(bf)"),
list(
`name`="stat[bf]",
`title`="Statistic",
`type`="number",
`visible`="(bf)",
`refs`=list(
"BF",
"btt")),
list(
`name`="err[bf]",
`title`="\u00B1%",
`type`="number",
`visible`="(bf)"),
list(
`name`="df[bf]",
`title`="df",
`type`="number",
`visible`="(bf)",
`content`=""),
list(
`name`="p[bf]",
`title`="p",
`type`="number",
`format`="zto,pvalue",
`visible`="(bf)",
`content`=""),
list(
`name`="md[bf]",
`title`="Mean difference",
`type`="number",
`visible`="(meanDiff && bf)",
`content`=""),
list(
`name`="cil[bf]",
`title`="Lower",
`type`="number",
`visible`="(ci && meanDiff && bf)",
`content`=""),
list(
`name`="ciu[bf]",
`title`="Upper",
`type`="number",
`visible`="(ci && meanDiff && bf)",
`content`=""),
list(
`name`="esType[bf]",
`title`="",
`content`="",
`type`="text",
`visible`="(effectSize && bf)"),
list(
`name`="es[bf]",
`title`="Effect Size",
`type`="number",
`visible`="(effectSize && bf)",
`content`=""),
list(
`name`="ciles[bf]",
`title`="Lower",
`type`="number",
`visible`="(ciES && effectSize && bf)",
`content`=""),
list(
`name`="ciues[bf]",
`title`="Upper",
`type`="number",
`visible`="(ciES && effectSize && bf)",
`content`=""),
list(
`name`="var[wilc]",
`title`="",
`content`="($key)",
`type`="text",
`combineBelow`=TRUE,
`visible`="(wilcoxon || mann)"),
list(
`name`="name[wilc]",
`title`="",
`type`="text",
`content`="Wilcoxon W",
`visible`="(wilcoxon || mann)"),
list(
`name`="stat[wilc]",
`title`="Statistic",
`type`="number",
`visible`="(wilcoxon || mann)"),
list(
`name`="err[wilc]",
`title`="\u00B1%",
`type`="number",
`visible`="(bf && (wilcoxon || mann))",
`content`=""),
list(
`name`="p[wilc]",
`title`="p",
`type`="number",
`format`="zto,pvalue",
`visible`="(wilcoxon || mann)"),
list(
`name`="md[wilc]",
`title`="Mean difference",
`type`="number",
`visible`="(meanDiff && (wilcoxon || mann))"),
list(
`name`="cil[wilc]",
`title`="Lower",
`type`="number",
`visible`="(ci && meanDiff && (wilcoxon || mann))"),
list(
`name`="ciu[wilc]",
`title`="Upper",
`type`="number",
`visible`="(ci && meanDiff && (wilcoxon || mann))"),
list(
`name`="esType[wilc]",
`title`="",
`content`="Rank biserial correlation",
`type`="text",
`visible`="(effectSize && wilcoxon)",
`refs`="Kerby2014"),
list(
`name`="es[wilc]",
`title`="Effect Size",
`type`="number",
`visible`="(effectSize && wilcoxon)"),
list(
`name`="ciles[wilc]",
`title`="Lower",
`type`="number",
`visible`="(ciES && effectSize && (wilcoxon || mann))"),
list(
`name`="ciues[wilc]",
`title`="Upper",
`type`="number",
`visible`="(ciES && effectSize && (wilcoxon || mann))"))))
self$add(jmvcore::Table$new(
options=options,
name="normality",
title="Normality Test (Shapiro-Wilk)",
visible="(norm)",
rows="(vars)",
notes=list(
`p`="A low p-value suggests a violation of the assumption of normality"),
clearWith=list(
"miss"),
columns=list(
list(
`name`="name",
`title`="",
`content`="($key)",
`type`="text"),
list(
`name`="w",
`title`="W",
`type`="number"),
list(
`name`="p",
`type`="number",
`format`="zto,pvalue"))))
self$add(jmvcore::Table$new(
options=options,
name="descriptives",
title="Descriptives",
visible="(desc)",
rows="(vars)",
clearWith=list(
"miss"),
columns=list(
list(
`name`="name",
`title`="",
`content`="($key)",
`type`="text"),
list(
`name`="num",
`title`="N",
`type`="number"),
list(
`name`="mean",
`title`="Mean",
`type`="number"),
list(
`name`="median",
`title`="Median",
`type`="number"),
list(
`name`="sd",
`title`="SD",
`type`="number"),
list(
`name`="se",
`title`="SE",
`type`="number"))))
self$add(jmvcore::Image$new(
options=options,
name="plots",
title="Plots",
visible="(plots)",
renderFun=".desc",
clearWith=list(
"vars",
"miss",
"testValue")))
self$add(jmvcore::Array$new(
options=options,
name="qq",
title="Q-Q plots",
visible="(qq)",
items="(vars)",
clearWith=list(
"miss"),
template=jmvcore::Image$new(
options=options,
width=350,
height=300,
requiresData=TRUE,
renderFun=".qq",
clearWith=list())))}))
ttestOneSBase <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"ttestOneSBase",
inherit = jmvcore::Analysis,
public = list(
initialize = function(options, data=NULL, datasetId="", analysisId="", revision=0) {
super$initialize(
package = "jmv",
name = "ttestOneS",
version = c(1,0,0),
options = options,
results = ttestOneSResults$new(options=options),
data = data,
datasetId = datasetId,
analysisId = analysisId,
revision = revision,
pause = NULL,
completeWhenFilled = TRUE,
requiresMissings = FALSE,
weightsSupport = 'auto')
}))
#' One Sample T-Test
#'
#' The Student's One-sample t-test is used to test the null hypothesis that
#' the true mean is equal to a particular value (typically zero). A low
#' p-value suggests that the null hypothesis is not true, and therefore
#' the true mean must be different from the test value.
#'
#' The Student's One-sample t-test assumes that the data are from a normal
#' distribution -- in the case that one is unwilling to assume this, the
#' non-parametric Wilcoxon signed-rank can be used in it's place (However,
#' note that the Wilcoxon signed-rank has a slightly different null
#' hypothesis; that the *median* is equal to the test value).
#'
#'
#' @examples
#' data('ToothGrowth')
#'
#' ttestOneS(ToothGrowth, vars = vars(len, dose))
#'
#' #
#' # ONE SAMPLE T-TEST
#' #
#' # One Sample T-Test
#' # ------------------------------------------------------
#' # statistic df p
#' # ------------------------------------------------------
#' # len Student's t 19.1 59.0 < .001
#' # dose Student's t 14.4 59.0 < .001
#' # ------------------------------------------------------
#' #
#'
#' @param data the data as a data frame
#' @param vars a vector of strings naming the variables of interest in
#' \code{data}
#' @param students \code{TRUE} (default) or \code{FALSE}, perform Student's
#' t-tests
#' @param bf \code{TRUE} or \code{FALSE} (default), provide Bayes factors
#' @param bfPrior a number between 0.5 and 2.0 (default 0.707), the prior
#' width to use in calculating Bayes factors
#' @param wilcoxon \code{TRUE} or \code{FALSE} (default), perform Wilcoxon
#' signed rank tests
#' @param testValue a number specifying the value of the null hypothesis
#' @param hypothesis \code{'dt'} (default), \code{'gt'} or \code{'lt'}, the
#' alternative hypothesis; different to \code{testValue}, greater than
#' \code{testValue}, and less than \code{testValue} respectively
#' @param norm \code{TRUE} or \code{FALSE} (default), perform Shapiro-wilk
#' tests of normality
#' @param qq \code{TRUE} or \code{FALSE} (default), provide a Q-Q plot of
#' residuals
#' @param meanDiff \code{TRUE} or \code{FALSE} (default), provide means and
#' standard deviations
#' @param ci \code{TRUE} or \code{FALSE} (default), provide confidence
#' intervals for the mean difference
#' @param ciWidth a number between 50 and 99.9 (default: 95), the width of
#' confidence intervals
#' @param effectSize \code{TRUE} or \code{FALSE} (default), provide Cohen's d
#' effect sizes
#' @param ciES \code{TRUE} or \code{FALSE} (default), provide confidence
#' intervals for the effect-sizes
#' @param ciWidthES a number between 50 and 99.9 (default: 95), the width of
#' confidence intervals for the effect sizes
#' @param desc \code{TRUE} or \code{FALSE} (default), provide descriptive
#' statistics
#' @param plots \code{TRUE} or \code{FALSE} (default), provide descriptive
#' plots
#' @param miss \code{'perAnalysis'} or \code{'listwise'}, how to handle
#' missing values; \code{'perAnalysis'} excludes missing values for individual
#' dependent variables, \code{'listwise'} excludes a row from all analyses if
#' one of its entries is missing.
#' @param mann deprecated
#' @return A results object containing:
#' \tabular{llllll}{
#' \code{results$ttest} \tab \tab \tab \tab \tab a table containing the t-test results \cr
#' \code{results$normality} \tab \tab \tab \tab \tab a table containing the normality test results \cr
#' \code{results$descriptives} \tab \tab \tab \tab \tab a table containing the descriptives \cr
#' \code{results$plots} \tab \tab \tab \tab \tab an image of the descriptive plots \cr
#' \code{results$qq} \tab \tab \tab \tab \tab an array of Q-Q plots \cr
#' }
#'
#' Tables can be converted to data frames with \code{asDF} or \code{\link{as.data.frame}}. For example:
#'
#' \code{results$ttest$asDF}
#'
#' \code{as.data.frame(results$ttest)}
#'
#' @export
ttestOneS <- function(
data,
vars,
students = TRUE,
bf = FALSE,
bfPrior = 0.707,
wilcoxon = FALSE,
testValue = 0,
hypothesis = "dt",
norm = FALSE,
qq = FALSE,
meanDiff = FALSE,
ci = FALSE,
ciWidth = 95,
effectSize = FALSE,
ciES = FALSE,
ciWidthES = 95,
desc = FALSE,
plots = FALSE,
miss = "perAnalysis",
mann = FALSE) {
if ( ! requireNamespace("jmvcore", quietly=TRUE))
stop("ttestOneS requires jmvcore to be installed (restart may be required)")
if ( ! missing(vars)) vars <- jmvcore::resolveQuo(jmvcore::enquo(vars))
if (missing(data))
data <- jmvcore::marshalData(
parent.frame(),
`if`( ! missing(vars), vars, NULL))
options <- ttestOneSOptions$new(
vars = vars,
students = students,
bf = bf,
bfPrior = bfPrior,
wilcoxon = wilcoxon,
testValue = testValue,
hypothesis = hypothesis,
norm = norm,
qq = qq,
meanDiff = meanDiff,
ci = ci,
ciWidth = ciWidth,
effectSize = effectSize,
ciES = ciES,
ciWidthES = ciWidthES,
desc = desc,
plots = plots,
miss = miss,
mann = mann)
analysis <- ttestOneSClass$new(
options = options,
data = data)
analysis$run()
analysis$results
}
jamovi/Rjamovi documentation built on Jan. 17, 2025, 10:29 p.m.
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Defines functions ttestOneS
# This file is automatically generated, you probably don't want to edit this
ttestOneSOptions <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"ttestOneSOptions",
inherit = jmvcore::Options,
public = list(
initialize = function(
vars = NULL,
students = TRUE,
bf = FALSE,
bfPrior = 0.707,
wilcoxon = FALSE,
testValue = 0,
hypothesis = "dt",
norm = FALSE,
qq = FALSE,
meanDiff = FALSE,
ci = FALSE,
ciWidth = 95,
effectSize = FALSE,
ciES = FALSE,
ciWidthES = 95,
desc = FALSE,
plots = FALSE,
miss = "perAnalysis",
mann = FALSE, ...) {
super$initialize(
package="jmv",
name="ttestOneS",
requiresData=TRUE,
...)
private$..vars <- jmvcore::OptionVariables$new(
"vars",
vars,
suggested=list(
"continuous"),
permitted=list(
"numeric"),
rejectInf=FALSE)
private$..students <- jmvcore::OptionBool$new(
"students",
students,
default=TRUE)
private$..bf <- jmvcore::OptionBool$new(
"bf",
bf,
default=FALSE)
private$..bfPrior <- jmvcore::OptionNumber$new(
"bfPrior",
bfPrior,
default=0.707,
min=0.5,
max=2)
private$..wilcoxon <- jmvcore::OptionBool$new(
"wilcoxon",
wilcoxon,
default=FALSE)
private$..testValue <- jmvcore::OptionNumber$new(
"testValue",
testValue,
default=0)
private$..hypothesis <- jmvcore::OptionList$new(
"hypothesis",
hypothesis,
options=list(
"dt",
"gt",
"lt"),
default="dt")
private$..norm <- jmvcore::OptionBool$new(
"norm",
norm,
default=FALSE)
private$..qq <- jmvcore::OptionBool$new(
"qq",
qq,
default=FALSE)
private$..meanDiff <- jmvcore::OptionBool$new(
"meanDiff",
meanDiff,
default=FALSE)
private$..ci <- jmvcore::OptionBool$new(
"ci",
ci,
default=FALSE)
private$..ciWidth <- jmvcore::OptionNumber$new(
"ciWidth",
ciWidth,
min=50,
max=99.9,
default=95)
private$..effectSize <- jmvcore::OptionBool$new(
"effectSize",
effectSize,
default=FALSE)
private$..ciES <- jmvcore::OptionBool$new(
"ciES",
ciES,
default=FALSE)
private$..ciWidthES <- jmvcore::OptionNumber$new(
"ciWidthES",
ciWidthES,
min=50,
max=99.9,
default=95)
private$..desc <- jmvcore::OptionBool$new(
"desc",
desc,
default=FALSE)
private$..plots <- jmvcore::OptionBool$new(
"plots",
plots,
default=FALSE)
private$..miss <- jmvcore::OptionList$new(
"miss",
miss,
options=list(
"perAnalysis",
"listwise"),
default="perAnalysis")
private$..mann <- jmvcore::OptionBool$new(
"mann",
mann,
default=FALSE,
hidden=TRUE)
self$.addOption(private$..vars)
self$.addOption(private$..students)
self$.addOption(private$..bf)
self$.addOption(private$..bfPrior)
self$.addOption(private$..wilcoxon)
self$.addOption(private$..testValue)
self$.addOption(private$..hypothesis)
self$.addOption(private$..norm)
self$.addOption(private$..qq)
self$.addOption(private$..meanDiff)
self$.addOption(private$..ci)
self$.addOption(private$..ciWidth)
self$.addOption(private$..effectSize)
self$.addOption(private$..ciES)
self$.addOption(private$..ciWidthES)
self$.addOption(private$..desc)
self$.addOption(private$..plots)
self$.addOption(private$..miss)
self$.addOption(private$..mann)
}),
active = list(
vars = function() private$..vars$value,
students = function() private$..students$value,
bf = function() private$..bf$value,
bfPrior = function() private$..bfPrior$value,
wilcoxon = function() private$..wilcoxon$value,
testValue = function() private$..testValue$value,
hypothesis = function() private$..hypothesis$value,
norm = function() private$..norm$value,
qq = function() private$..qq$value,
meanDiff = function() private$..meanDiff$value,
ci = function() private$..ci$value,
ciWidth = function() private$..ciWidth$value,
effectSize = function() private$..effectSize$value,
ciES = function() private$..ciES$value,
ciWidthES = function() private$..ciWidthES$value,
desc = function() private$..desc$value,
plots = function() private$..plots$value,
miss = function() private$..miss$value,
mann = function() private$..mann$value),
private = list(
..vars = NA,
..students = NA,
..bf = NA,
..bfPrior = NA,
..wilcoxon = NA,
..testValue = NA,
..hypothesis = NA,
..norm = NA,
..qq = NA,
..meanDiff = NA,
..ci = NA,
..ciWidth = NA,
..effectSize = NA,
..ciES = NA,
..ciWidthES = NA,
..desc = NA,
..plots = NA,
..miss = NA,
..mann = NA)
)
ttestOneSResults <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"ttestOneSResults",
inherit = jmvcore::Group,
active = list(
ttest = function() private$.items[["ttest"]],
normality = function() private$.items[["normality"]],
descriptives = function() private$.items[["descriptives"]],
plots = function() private$.items[["plots"]],
qq = function() private$.items[["qq"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="",
title="One Sample T-Test")
self$add(jmvcore::Table$new(
options=options,
name="ttest",
title="One Sample T-Test",
rows="(vars)",
clearWith=list(
"hypothesis",
"testValue",
"miss",
"bfPrior",
"ciWidth",
"ciWidthES"),
columns=list(
list(
`name`="var[stud]",
`title`="",
`content`="($key)",
`type`="text",
`combineBelow`=TRUE,
`visible`="(students)"),
list(
`name`="name[stud]",
`title`="",
`type`="text",
`content`="Student's t",
`visible`="(students)"),
list(
`name`="stat[stud]",
`title`="Statistic",
`type`="number",
`visible`="(students)"),
list(
`name`="err[stud]",
`title`="error %",
`type`="number",
`visible`="(students && bf)",
`content`=""),
list(
`name`="df[stud]",
`title`="df",
`type`="number",
`visible`="(students)"),
list(
`name`="p[stud]",
`title`="p",
`type`="number",
`format`="zto,pvalue",
`visible`="(students)"),
list(
`name`="md[stud]",
`title`="Mean difference",
`type`="number",
`visible`="(meanDiff && students)"),
list(
`name`="cil[stud]",
`title`="Lower",
`type`="number",
`visible`="(ci && meanDiff && students)"),
list(
`name`="ciu[stud]",
`title`="Upper",
`type`="number",
`visible`="(ci && meanDiff && students)"),
list(
`name`="esType[stud]",
`title`="",
`content`="Cohen's d",
`type`="text",
`visible`="(effectSize && students)"),
list(
`name`="es[stud]",
`title`="Effect Size",
`type`="number",
`visible`="(effectSize && students)"),
list(
`name`="ciles[stud]",
`title`="Lower",
`type`="number",
`visible`="(ciES && effectSize && students)"),
list(
`name`="ciues[stud]",
`title`="Upper",
`type`="number",
`visible`="(ciES && effectSize && students)"),
list(
`name`="var[bf]",
`title`="",
`content`="($key)",
`type`="text",
`combineBelow`=TRUE,
`visible`="(bf)"),
list(
`name`="name[bf]",
`title`="",
`type`="text",
`content`="Bayes factor\u2081\u2080",
`visible`="(bf)"),
list(
`name`="stat[bf]",
`title`="Statistic",
`type`="number",
`visible`="(bf)",
`refs`=list(
"BF",
"btt")),
list(
`name`="err[bf]",
`title`="\u00B1%",
`type`="number",
`visible`="(bf)"),
list(
`name`="df[bf]",
`title`="df",
`type`="number",
`visible`="(bf)",
`content`=""),
list(
`name`="p[bf]",
`title`="p",
`type`="number",
`format`="zto,pvalue",
`visible`="(bf)",
`content`=""),
list(
`name`="md[bf]",
`title`="Mean difference",
`type`="number",
`visible`="(meanDiff && bf)",
`content`=""),
list(
`name`="cil[bf]",
`title`="Lower",
`type`="number",
`visible`="(ci && meanDiff && bf)",
`content`=""),
list(
`name`="ciu[bf]",
`title`="Upper",
`type`="number",
`visible`="(ci && meanDiff && bf)",
`content`=""),
list(
`name`="esType[bf]",
`title`="",
`content`="",
`type`="text",
`visible`="(effectSize && bf)"),
list(
`name`="es[bf]",
`title`="Effect Size",
`type`="number",
`visible`="(effectSize && bf)",
`content`=""),
list(
`name`="ciles[bf]",
`title`="Lower",
`type`="number",
`visible`="(ciES && effectSize && bf)",
`content`=""),
list(
`name`="ciues[bf]",
`title`="Upper",
`type`="number",
`visible`="(ciES && effectSize && bf)",
`content`=""),
list(
`name`="var[wilc]",
`title`="",
`content`="($key)",
`type`="text",
`combineBelow`=TRUE,
`visible`="(wilcoxon || mann)"),
list(
`name`="name[wilc]",
`title`="",
`type`="text",
`content`="Wilcoxon W",
`visible`="(wilcoxon || mann)"),
list(
`name`="stat[wilc]",
`title`="Statistic",
`type`="number",
`visible`="(wilcoxon || mann)"),
list(
`name`="err[wilc]",
`title`="\u00B1%",
`type`="number",
`visible`="(bf && (wilcoxon || mann))",
`content`=""),
list(
`name`="p[wilc]",
`title`="p",
`type`="number",
`format`="zto,pvalue",
`visible`="(wilcoxon || mann)"),
list(
`name`="md[wilc]",
`title`="Mean difference",
`type`="number",
`visible`="(meanDiff && (wilcoxon || mann))"),
list(
`name`="cil[wilc]",
`title`="Lower",
`type`="number",
`visible`="(ci && meanDiff && (wilcoxon || mann))"),
list(
`name`="ciu[wilc]",
`title`="Upper",
`type`="number",
`visible`="(ci && meanDiff && (wilcoxon || mann))"),
list(
`name`="esType[wilc]",
`title`="",
`content`="Rank biserial correlation",
`type`="text",
`visible`="(effectSize && wilcoxon)",
`refs`="Kerby2014"),
list(
`name`="es[wilc]",
`title`="Effect Size",
`type`="number",
`visible`="(effectSize && wilcoxon)"),
list(
`name`="ciles[wilc]",
`title`="Lower",
`type`="number",
`visible`="(ciES && effectSize && (wilcoxon || mann))"),
list(
`name`="ciues[wilc]",
`title`="Upper",
`type`="number",
`visible`="(ciES && effectSize && (wilcoxon || mann))"))))
self$add(jmvcore::Table$new(
options=options,
name="normality",
title="Normality Test (Shapiro-Wilk)",
visible="(norm)",
rows="(vars)",
notes=list(
`p`="A low p-value suggests a violation of the assumption of normality"),
clearWith=list(
"miss"),
columns=list(
list(
`name`="name",
`title`="",
`content`="($key)",
`type`="text"),
list(
`name`="w",
`title`="W",
`type`="number"),
list(
`name`="p",
`type`="number",
`format`="zto,pvalue"))))
self$add(jmvcore::Table$new(
options=options,
name="descriptives",
title="Descriptives",
visible="(desc)",
rows="(vars)",
clearWith=list(
"miss"),
columns=list(
list(
`name`="name",
`title`="",
`content`="($key)",
`type`="text"),
list(
`name`="num",
`title`="N",
`type`="number"),
list(
`name`="mean",
`title`="Mean",
`type`="number"),
list(
`name`="median",
`title`="Median",
`type`="number"),
list(
`name`="sd",
`title`="SD",
`type`="number"),
list(
`name`="se",
`title`="SE",
`type`="number"))))
self$add(jmvcore::Image$new(
options=options,
name="plots",
title="Plots",
visible="(plots)",
renderFun=".desc",
clearWith=list(
"vars",
"miss",
"testValue")))
self$add(jmvcore::Array$new(
options=options,
name="qq",
title="Q-Q plots",
visible="(qq)",
items="(vars)",
clearWith=list(
"miss"),
template=jmvcore::Image$new(
options=options,
width=350,
height=300,
requiresData=TRUE,
renderFun=".qq",
clearWith=list())))}))
ttestOneSBase <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"ttestOneSBase",
inherit = jmvcore::Analysis,
public = list(
initialize = function(options, data=NULL, datasetId="", analysisId="", revision=0) {
super$initialize(
package = "jmv",
name = "ttestOneS",
version = c(1,0,0),
options = options,
results = ttestOneSResults$new(options=options),
data = data,
datasetId = datasetId,
analysisId = analysisId,
revision = revision,
pause = NULL,
completeWhenFilled = TRUE,
requiresMissings = FALSE,
weightsSupport = 'auto')
}))
#' One Sample T-Test
#'
#' The Student's One-sample t-test is used to test the null hypothesis that
#' the true mean is equal to a particular value (typically zero). A low
#' p-value suggests that the null hypothesis is not true, and therefore
#' the true mean must be different from the test value.
#'
#' The Student's One-sample t-test assumes that the data are from a normal
#' distribution -- in the case that one is unwilling to assume this, the
#' non-parametric Wilcoxon signed-rank can be used in it's place (However,
#' note that the Wilcoxon signed-rank has a slightly different null
#' hypothesis; that the *median* is equal to the test value).
#'
#'
#' @examples
#' data('ToothGrowth')
#'
#' ttestOneS(ToothGrowth, vars = vars(len, dose))
#'
#' #
#' # ONE SAMPLE T-TEST
#' #
#' # One Sample T-Test
#' # ------------------------------------------------------
#' # statistic df p
#' # ------------------------------------------------------
#' # len Student's t 19.1 59.0 < .001
#' # dose Student's t 14.4 59.0 < .001
#' # ------------------------------------------------------
#' #
#'
#' @param data the data as a data frame
#' @param vars a vector of strings naming the variables of interest in
#' \code{data}
#' @param students \code{TRUE} (default) or \code{FALSE}, perform Student's
#' t-tests
#' @param bf \code{TRUE} or \code{FALSE} (default), provide Bayes factors
#' @param bfPrior a number between 0.5 and 2.0 (default 0.707), the prior
#' width to use in calculating Bayes factors
#' @param wilcoxon \code{TRUE} or \code{FALSE} (default), perform Wilcoxon
#' signed rank tests
#' @param testValue a number specifying the value of the null hypothesis
#' @param hypothesis \code{'dt'} (default), \code{'gt'} or \code{'lt'}, the
#' alternative hypothesis; different to \code{testValue}, greater than
#' \code{testValue}, and less than \code{testValue} respectively
#' @param norm \code{TRUE} or \code{FALSE} (default), perform Shapiro-wilk
#' tests of normality
#' @param qq \code{TRUE} or \code{FALSE} (default), provide a Q-Q plot of
#' residuals
#' @param meanDiff \code{TRUE} or \code{FALSE} (default), provide means and
#' standard deviations
#' @param ci \code{TRUE} or \code{FALSE} (default), provide confidence
#' intervals for the mean difference
#' @param ciWidth a number between 50 and 99.9 (default: 95), the width of
#' confidence intervals
#' @param effectSize \code{TRUE} or \code{FALSE} (default), provide Cohen's d
#' effect sizes
#' @param ciES \code{TRUE} or \code{FALSE} (default), provide confidence
#' intervals for the effect-sizes
#' @param ciWidthES a number between 50 and 99.9 (default: 95), the width of
#' confidence intervals for the effect sizes
#' @param desc \code{TRUE} or \code{FALSE} (default), provide descriptive
#' statistics
#' @param plots \code{TRUE} or \code{FALSE} (default), provide descriptive
#' plots
#' @param miss \code{'perAnalysis'} or \code{'listwise'}, how to handle
#' missing values; \code{'perAnalysis'} excludes missing values for individual
#' dependent variables, \code{'listwise'} excludes a row from all analyses if
#' one of its entries is missing.
#' @param mann deprecated
#' @return A results object containing:
#' \tabular{llllll}{
#' \code{results$ttest} \tab \tab \tab \tab \tab a table containing the t-test results \cr
#' \code{results$normality} \tab \tab \tab \tab \tab a table containing the normality test results \cr
#' \code{results$descriptives} \tab \tab \tab \tab \tab a table containing the descriptives \cr
#' \code{results$plots} \tab \tab \tab \tab \tab an image of the descriptive plots \cr
#' \code{results$qq} \tab \tab \tab \tab \tab an array of Q-Q plots \cr
#' }
#'
#' Tables can be converted to data frames with \code{asDF} or \code{\link{as.data.frame}}. For example:
#'
#' \code{results$ttest$asDF}
#'
#' \code{as.data.frame(results$ttest)}
#'
#' @export
ttestOneS <- function(
data,
vars,
students = TRUE,
bf = FALSE,
bfPrior = 0.707,
wilcoxon = FALSE,
testValue = 0,
hypothesis = "dt",
norm = FALSE,
qq = FALSE,
meanDiff = FALSE,
ci = FALSE,
ciWidth = 95,
effectSize = FALSE,
ciES = FALSE,
ciWidthES = 95,
desc = FALSE,
plots = FALSE,
miss = "perAnalysis",
mann = FALSE) {
if ( ! requireNamespace("jmvcore", quietly=TRUE))
stop("ttestOneS requires jmvcore to be installed (restart may be required)")
if ( ! missing(vars)) vars <- jmvcore::resolveQuo(jmvcore::enquo(vars))
if (missing(data))
data <- jmvcore::marshalData(
parent.frame(),
`if`( ! missing(vars), vars, NULL))
options <- ttestOneSOptions$new(
vars = vars,
students = students,
bf = bf,
bfPrior = bfPrior,
wilcoxon = wilcoxon,
testValue = testValue,
hypothesis = hypothesis,
norm = norm,
qq = qq,
meanDiff = meanDiff,
ci = ci,
ciWidth = ciWidth,
effectSize = effectSize,
ciES = ciES,
ciWidthES = ciWidthES,
desc = desc,
plots = plots,
miss = miss,
mann = mann)
analysis <- ttestOneSClass$new(
options = options,
data = data)
analysis$run()
analysis$results
}
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