R/ttestis.h.R
In jamovi/jmv: The 'jamovi' Analyses
Defines functions
ttestIS
# This file is automatically generated, you probably don't want to edit this
ttestISOptions <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"ttestISOptions",
inherit = jmvcore::Options,
public = list(
initialize = function(
vars = NULL,
group = NULL,
students = TRUE,
bf = FALSE,
bfPrior = 0.707,
welchs = FALSE,
mann = FALSE,
hypothesis = "different",
norm = FALSE,
qq = FALSE,
eqv = FALSE,
meanDiff = FALSE,
ci = FALSE,
ciWidth = 95,
effectSize = FALSE,
ciES = FALSE,
ciWidthES = 95,
desc = FALSE,
plots = FALSE,
miss = "perAnalysis", ...) {
super$initialize(
package="jmv",
name="ttestIS",
requiresData=TRUE,
...)
private$..vars <- jmvcore::OptionVariables$new(
"vars",
vars,
suggested=list(
"continuous"),
permitted=list(
"numeric"),
rejectInf=FALSE)
private$..group <- jmvcore::OptionVariable$new(
"group",
group,
suggested=list(
"nominal",
"ordinal"),
permitted=list(
"factor"))
private$..students <- jmvcore::OptionBool$new(
"students",
students,
default=TRUE)
private$..bf <- jmvcore::OptionBool$new(
"bf",
bf,
default=FALSE)
private$..bfPrior <- jmvcore::OptionNumber$new(
"bfPrior",
bfPrior,
default=0.707,
min=0.01,
max=2)
private$..welchs <- jmvcore::OptionBool$new(
"welchs",
welchs,
default=FALSE)
private$..mann <- jmvcore::OptionBool$new(
"mann",
mann,
default=FALSE)
private$..hypothesis <- jmvcore::OptionList$new(
"hypothesis",
hypothesis,
options=list(
"different",
"oneGreater",
"twoGreater"),
default="different")
private$..norm <- jmvcore::OptionBool$new(
"norm",
norm,
default=FALSE)
private$..qq <- jmvcore::OptionBool$new(
"qq",
qq,
default=FALSE)
private$..eqv <- jmvcore::OptionBool$new(
"eqv",
eqv,
default=FALSE)
private$..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$new(
"miss",
miss,
options=list(
"perAnalysis",
"listwise"),
default="perAnalysis")
self$.addOption(private$..vars)
self$.addOption(private$..group)
self$.addOption(private$..students)
self$.addOption(private$..bf)
self$.addOption(private$..bfPrior)
self$.addOption(private$..welchs)
self$.addOption(private$..mann)
self$.addOption(private$..hypothesis)
self$.addOption(private$..norm)
self$.addOption(private$..qq)
self$.addOption(private$..eqv)
self$.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$..miss)
}),
active = list(
vars = function() private$..vars$value,
group = function() private$..group$value,
students = function() private$..students$value,
bf = function() private$..bf$value,
bfPrior = function() private$..bfPrior$value,
welchs = function() private$..welchs$value,
mann = function() private$..mann$value,
hypothesis = function() private$..hypothesis$value,
norm = function() private$..norm$value,
qq = function() private$..qq$value,
eqv = function() private$..eqv$value,
meanDiff = function() private$..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$value),
private = list(
..vars = NA,
..group = NA,
..students = NA,
..bf = NA,
..bfPrior = NA,
..welchs = NA,
..mann = NA,
..hypothesis = NA,
..norm = NA,
..qq = NA,
..eqv = NA,
..meanDiff = NA,
..ci = NA,
..ciWidth = NA,
..effectSize = NA,
..ciES = NA,
..ciWidthES = NA,
..desc = NA,
..plots = NA,
..miss = NA)
)
ttestISResults <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"ttestISResults",
inherit = jmvcore::Group,
active = list(
ttest = function() private$.items[["ttest"]],
assum = function() private$.items[["assum"]],
desc = function() private$.items[["desc"]],
plots = function() private$.items[["plots"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="",
title="Independent Samples T-Test")
self$add(jmvcore::Table$new(
options=options,
name="ttest",
title="Independent Samples T-Test",
rows="(vars)",
clearWith=list(
"group",
"hypothesis",
"ciWidth",
"miss",
"bfPrior",
"ciWidthES"),
columns=list(
list(
`name`="var[stud]",
`title`="",
`content`="($key)",
`type`="text",
`combineBelow`=TRUE,
`visible`="(students)"),
list(
`name`="name[stud]",
`title`="",
`type`="text",
`content`="Student's t",
`visible`="(students)"),
list(
`name`="stat[stud]",
`title`="Statistic",
`type`="number",
`visible`="(students)"),
list(
`name`="err[stud]",
`title`="error %",
`type`="number",
`visible`="(students && bf)",
`content`=""),
list(
`name`="df[stud]",
`title`="df",
`type`="number",
`visible`="(students)"),
list(
`name`="p[stud]",
`title`="p",
`type`="number",
`format`="zto,pvalue",
`visible`="(students)"),
list(
`name`="md[stud]",
`title`="Mean difference",
`type`="number",
`visible`="(meanDiff && students)"),
list(
`name`="sed[stud]",
`title`="SE difference",
`type`="number",
`visible`="(meanDiff && students)"),
list(
`name`="cil[stud]",
`title`="Lower",
`type`="number",
`visible`="(ci && meanDiff && students)"),
list(
`name`="ciu[stud]",
`title`="Upper",
`type`="number",
`visible`="(ci && meanDiff && students)"),
list(
`name`="esType[stud]",
`title`="",
`content`="Cohen's d",
`type`="text",
`visible`="(effectSize && students)"),
list(
`name`="es[stud]",
`title`="Effect Size",
`type`="number",
`visible`="(effectSize && students)"),
list(
`name`="ciles[stud]",
`title`="Lower",
`type`="number",
`visible`="(ciES && effectSize && students)"),
list(
`name`="ciues[stud]",
`title`="Upper",
`type`="number",
`visible`="(ciES && effectSize && students)"),
list(
`name`="var[bf]",
`title`="",
`content`="($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`="sed[bf]",
`title`="SE 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[welc]",
`title`="",
`content`="($key)",
`type`="text",
`combineBelow`=TRUE,
`visible`="(welchs)"),
list(
`name`="name[welc]",
`title`="",
`type`="text",
`content`="Welch's t",
`visible`="(welchs)"),
list(
`name`="stat[welc]",
`title`="Statistic",
`visible`="(welchs)"),
list(
`name`="err[welc]",
`title`="\u00B1%",
`type`="number",
`visible`="(welchs && bf)",
`content`=""),
list(
`name`="df[welc]",
`title`="df",
`type`="number",
`visible`="(welchs)"),
list(
`name`="p[welc]",
`title`="p",
`type`="number",
`format`="zto,pvalue",
`visible`="(welchs)"),
list(
`name`="md[welc]",
`title`="Mean difference",
`type`="number",
`visible`="(meanDiff && welchs)"),
list(
`name`="sed[welc]",
`title`="SE difference",
`type`="number",
`visible`="(meanDiff && welchs)"),
list(
`name`="cil[welc]",
`title`="Lower",
`type`="number",
`visible`="(ci && meanDiff && welchs)"),
list(
`name`="ciu[welc]",
`title`="Upper",
`type`="number",
`visible`="(ci && meanDiff && welchs)"),
list(
`name`="esType[welc]",
`title`="",
`content`="Cohen's d",
`type`="text",
`visible`="(effectSize && welchs)"),
list(
`name`="es[welc]",
`title`="Effect Size",
`type`="number",
`visible`="(effectSize && welchs)"),
list(
`name`="ciles[welc]",
`title`="Lower",
`type`="number",
`visible`="(ciES && effectSize && welchs)"),
list(
`name`="ciues[welc]",
`title`="Upper",
`type`="number",
`visible`="(ciES && effectSize && welchs)"),
list(
`name`="var[mann]",
`title`="",
`content`="($key)",
`type`="text",
`combineBelow`=TRUE,
`visible`="(mann)"),
list(
`name`="name[mann]",
`title`="",
`type`="text",
`content`="Mann-Whitney U",
`visible`="(mann)"),
list(
`name`="stat[mann]",
`title`="Statistic",
`content`=".",
`visible`="(mann)"),
list(
`name`="err[mann]",
`title`="\u00B1%",
`type`="number",
`visible`="(mann && bf)",
`content`=""),
list(
`name`="p[mann]",
`title`="p",
`type`="number",
`format`="zto,pvalue",
`visible`="(mann)"),
list(
`name`="md[mann]",
`title`="Mean difference",
`type`="number",
`visible`="(meanDiff && mann)"),
list(
`name`="sed[mann]",
`title`="SE difference",
`type`="number",
`visible`="(meanDiff && mann)"),
list(
`name`="cil[mann]",
`title`="Lower",
`type`="number",
`visible`="(ci && meanDiff && mann)"),
list(
`name`="ciu[mann]",
`title`="Upper",
`type`="number",
`visible`="(ci && meanDiff && mann)"),
list(
`name`="esType[mann]",
`title`="",
`content`="Rank biserial correlation",
`type`="text",
`visible`="(effectSize && mann)",
`refs`="Kerby2014"),
list(
`name`="es[mann]",
`title`="Effect Size",
`type`="number",
`visible`="(effectSize && mann)"),
list(
`name`="ciles[mann]",
`title`="Lower",
`type`="number",
`visible`="(ciES && effectSize && mann)"),
list(
`name`="ciues[mann]",
`title`="Upper",
`type`="number",
`visible`="(ciES && effectSize && mann)"))))
self$add(R6::R6Class(
inherit = jmvcore::Group,
active = list(
norm = function() private$.items[["norm"]],
eqv = function() private$.items[["eqv"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="assum",
title="Assumptions")
self$add(jmvcore::Table$new(
options=options,
name="norm",
title="Normality Test (Shapiro-Wilk)",
visible="(norm)",
rows="(vars)",
clearWith=list(
"miss",
"group"),
notes=list(
`p`="A low p-value suggests a violation of the assumption of normality"),
columns=list(
list(
`name`="name",
`title`="",
`content`="($key)",
`type`="text"),
list(
`name`="w",
`title`="W",
`type`="number"),
list(
`name`="p",
`title`="p",
`type`="number",
`format`="zto,pvalue"))))
self$add(jmvcore::Table$new(
options=options,
name="eqv",
title="Homogeneity of Variances Test (Levene's)",
visible="(eqv)",
rows="(vars)",
clearWith=list(
"group",
"miss"),
notes=list(
`p`="A low p-value suggests a violation of the assumption of equal variances"),
refs="car",
columns=list(
list(
`name`="name",
`title`="",
`content`="($key)",
`type`="text"),
list(
`name`="f",
`title`="F",
`type`="number"),
list(
`name`="df",
`type`="number"),
list(
`name`="df2",
`type`="number"),
list(
`name`="p",
`type`="number",
`format`="zto,pvalue"))))}))$new(options=options))
self$add(jmvcore::Table$new(
options=options,
name="desc",
title="Group Descriptives",
visible="(desc)",
rows="(vars)",
clearWith=list(
"group",
"miss"),
columns=list(
list(
`name`="dep",
`title`="",
`content`="($key)",
`type`="text"),
list(
`name`="group[1]",
`title`="Group",
`type`="text"),
list(
`name`="num[1]",
`title`="N",
`type`="integer"),
list(
`name`="mean[1]",
`title`="Mean",
`type`="number"),
list(
`name`="med[1]",
`title`="Median",
`type`="number"),
list(
`name`="sd[1]",
`title`="SD",
`type`="number"),
list(
`name`="se[1]",
`title`="SE",
`type`="number"),
list(
`name`="group[2]",
`title`="Group",
`type`="text"),
list(
`name`="num[2]",
`title`="N",
`type`="integer"),
list(
`name`="mean[2]",
`title`="Mean",
`type`="number"),
list(
`name`="med[2]",
`title`="Median",
`type`="number"),
list(
`name`="sd[2]",
`title`="SD",
`type`="number"),
list(
`name`="se[2]",
`title`="SE",
`type`="number"))))
self$add(jmvcore::Array$new(
options=options,
name="plots",
title="Plots",
items="(vars)",
clearWith=list(
"group",
"miss",
"ciWidth"),
template=R6::R6Class(
inherit = jmvcore::Group,
active = list(
desc = function() private$.items[["desc"]],
qq = function() private$.items[["qq"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="undefined",
title="$key")
self$add(jmvcore::Image$new(
options=options,
name="desc",
visible="(plots)",
renderFun=".desc",
clearWith=list()))
self$add(jmvcore::Image$new(
options=options,
name="qq",
width=350,
height=300,
requiresData=TRUE,
visible="(qq)",
renderFun=".qq",
clearWith=list()))}))$new(options=options)))}))
ttestISBase <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"ttestISBase",
inherit = jmvcore::Analysis,
public = list(
initialize = function(options, data=NULL, datasetId="", analysisId="", revision=0) {
super$initialize(
package = "jmv",
name = "ttestIS",
version = c(1,0,0),
options = options,
results = ttestISResults$new(options=options),
data = data,
datasetId = datasetId,
analysisId = analysisId,
revision = revision,
pause = NULL,
completeWhenFilled = TRUE,
requiresMissings = FALSE,
weightsSupport = 'auto')
}))
#' Independent Samples T-Test
#'
#' The Student's Independent samples t-test (sometimes called a two-samples
#' t-test) is used to test the null hypothesis that two groups have the
#' same mean. A low p-value suggests that the null hypothesis is not true,
#' and therefore the group means are different.
#'
#' The Student's independent t-test assumes that the data from each group
#' are from a normal distribution, and that the variances of these groups
#' are equal. If unwilling to assume the groups have equal variances, the
#' Welch's t-test can be used in it's place. If one is additionally
#' unwilling to assume the data from each group are from a normal
#' distribution, the non-parametric Mann-Whitney U test can be used instead
#' (However, note that the Mann-Whitney U test has a slightly different
#' null hypothesis; that the distributions of each group is equal).
#'
#'
#' @examples
#' data('ToothGrowth')
#'
#' ttestIS(formula = len ~ supp, data = ToothGrowth)
#'
#' #
#' # INDEPENDENT SAMPLES T-TEST
#' #
#' # Independent Samples T-Test
#' # ----------------------------------------------------
#' # statistic df p
#' # ----------------------------------------------------
#' # len Student's t 1.92 58.0 0.060
#' # ----------------------------------------------------
#' #
#'
#' @param data the data as a data frame
#' @param vars the dependent variables (not necessary when using a formula,
#' see the examples)
#' @param group the grouping variable with two levels (not necessary when
#' using a formula, see the examples)
#' @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 0.01 and 2 (default 0.707), the prior width
#' to use in calculating Bayes factors
#' @param welchs \code{TRUE} or \code{FALSE} (default), perform Welch's
#' t-tests
#' @param mann \code{TRUE} or \code{FALSE} (default), perform Mann-Whitney U
#' tests
#' @param hypothesis \code{'different'} (default), \code{'oneGreater'} or
#' \code{'twoGreater'}, the alternative hypothesis; group 1 different to group
#' 2, group 1 greater than group 2, and group 2 greater than group 1
#' respectively
#' @param norm \code{TRUE} or \code{FALSE} (default), perform Shapiro-Wilk
#' tests of normality
#' @param qq \code{TRUE} or \code{FALSE} (default), provide Q-Q plots of
#' residuals
#' @param eqv \code{TRUE} or \code{FALSE} (default), perform Levene's tests
#' for homogeneity of variances
#' @param meanDiff \code{TRUE} or \code{FALSE} (default), provide means and
#' standard errors
#' @param ci \code{TRUE} or \code{FALSE} (default), provide confidence
#' intervals
#' @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 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 formula (optional) the formula to use, see the examples
#' @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$assum$norm} \tab \tab \tab \tab \tab a table containing the normality tests \cr
#' \code{results$assum$eqv} \tab \tab \tab \tab \tab a table containing the homogeneity of variances tests \cr
#' \code{results$desc} \tab \tab \tab \tab \tab a table containing the group descriptives \cr
#' \code{results$plots} \tab \tab \tab \tab \tab an array of groups of 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$ttest)}
#'
#' @export
ttestIS <- function(
data,
vars,
group,
students = TRUE,
bf = FALSE,
bfPrior = 0.707,
welchs = FALSE,
mann = FALSE,
hypothesis = "different",
norm = FALSE,
qq = FALSE,
eqv = FALSE,
meanDiff = FALSE,
ci = FALSE,
ciWidth = 95,
effectSize = FALSE,
ciES = FALSE,
ciWidthES = 95,
desc = FALSE,
plots = FALSE,
miss = "perAnalysis",
formula) {
if ( ! requireNamespace("jmvcore", quietly=TRUE))
stop("ttestIS requires jmvcore to be installed (restart may be required)")
if ( ! missing(formula)) {
if (missing(vars))
vars <- jmvcore::marshalFormula(
formula=formula,
data=`if`( ! missing(data), data, NULL),
from="lhs",
required=TRUE)
if (missing(group))
group <- jmvcore::marshalFormula(
formula=formula,
data=`if`( ! missing(data), data, NULL),
from="rhs",
subset="1")
}
if ( ! missing(vars)) vars <- jmvcore::resolveQuo(jmvcore::enquo(vars))
if ( ! missing(group)) group <- jmvcore::resolveQuo(jmvcore::enquo(group))
if (missing(data))
data <- jmvcore::marshalData(
parent.frame(),
`if`( ! missing(vars), vars, NULL),
`if`( ! missing(group), group, NULL))
for (v in group) if (v %in% names(data)) data[[v]] <- as.factor(data[[v]])
options <- ttestISOptions$new(
vars = vars,
group = group,
students = students,
bf = bf,
bfPrior = bfPrior,
welchs = welchs,
mann = mann,
hypothesis = hypothesis,
norm = norm,
qq = qq,
eqv = eqv,
meanDiff = meanDiff,
ci = ci,
ciWidth = ciWidth,
effectSize = effectSize,
ciES = ciES,
ciWidthES = ciWidthES,
desc = desc,
plots = plots,
miss = miss)
analysis <- ttestISClass$new(
options = options,
data = data)
analysis$run()
analysis$results
}
jamovi/jmv documentation built on Jan. 17, 2025, 10:31 p.m.
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Defines functions ttestIS
# This file is automatically generated, you probably don't want to edit this
ttestISOptions <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"ttestISOptions",
inherit = jmvcore::Options,
public = list(
initialize = function(
vars = NULL,
group = NULL,
students = TRUE,
bf = FALSE,
bfPrior = 0.707,
welchs = FALSE,
mann = FALSE,
hypothesis = "different",
norm = FALSE,
qq = FALSE,
eqv = FALSE,
meanDiff = FALSE,
ci = FALSE,
ciWidth = 95,
effectSize = FALSE,
ciES = FALSE,
ciWidthES = 95,
desc = FALSE,
plots = FALSE,
miss = "perAnalysis", ...) {
super$initialize(
package="jmv",
name="ttestIS",
requiresData=TRUE,
...)
private$..vars <- jmvcore::OptionVariables$new(
"vars",
vars,
suggested=list(
"continuous"),
permitted=list(
"numeric"),
rejectInf=FALSE)
private$..group <- jmvcore::OptionVariable$new(
"group",
group,
suggested=list(
"nominal",
"ordinal"),
permitted=list(
"factor"))
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=0.01,
max=2)
private$..welchs <- jmvcore::OptionBool$new(
"welchs",
welchs,
default=FALSE)
private$..mann <- jmvcore::OptionBool$new(
"mann",
mann,
default=FALSE)
private$..hypothesis <- jmvcore::OptionList$new(
"hypothesis",
hypothesis,
options=list(
"different",
"oneGreater",
"twoGreater"),
default="different")
private$..norm <- jmvcore::OptionBool$new(
"norm",
norm,
default=FALSE)
private$..qq <- jmvcore::OptionBool$new(
"qq",
qq,
default=FALSE)
private$..eqv <- jmvcore::OptionBool$new(
"eqv",
eqv,
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")
self$.addOption(private$..vars)
self$.addOption(private$..group)
self$.addOption(private$..students)
self$.addOption(private$..bf)
self$.addOption(private$..bfPrior)
self$.addOption(private$..welchs)
self$.addOption(private$..mann)
self$.addOption(private$..hypothesis)
self$.addOption(private$..norm)
self$.addOption(private$..qq)
self$.addOption(private$..eqv)
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)
}),
active = list(
vars = function() private$..vars$value,
group = function() private$..group$value,
students = function() private$..students$value,
bf = function() private$..bf$value,
bfPrior = function() private$..bfPrior$value,
welchs = function() private$..welchs$value,
mann = function() private$..mann$value,
hypothesis = function() private$..hypothesis$value,
norm = function() private$..norm$value,
qq = function() private$..qq$value,
eqv = function() private$..eqv$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),
private = list(
..vars = NA,
..group = NA,
..students = NA,
..bf = NA,
..bfPrior = NA,
..welchs = NA,
..mann = NA,
..hypothesis = NA,
..norm = NA,
..qq = NA,
..eqv = NA,
..meanDiff = NA,
..ci = NA,
..ciWidth = NA,
..effectSize = NA,
..ciES = NA,
..ciWidthES = NA,
..desc = NA,
..plots = NA,
..miss = NA)
)
ttestISResults <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"ttestISResults",
inherit = jmvcore::Group,
active = list(
ttest = function() private$.items[["ttest"]],
assum = function() private$.items[["assum"]],
desc = function() private$.items[["desc"]],
plots = function() private$.items[["plots"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="",
title="Independent Samples T-Test")
self$add(jmvcore::Table$new(
options=options,
name="ttest",
title="Independent Samples T-Test",
rows="(vars)",
clearWith=list(
"group",
"hypothesis",
"ciWidth",
"miss",
"bfPrior",
"ciWidthES"),
columns=list(
list(
`name`="var[stud]",
`title`="",
`content`="($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`="sed[stud]",
`title`="SE 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`="($key)",
`type`="text",
`combineBelow`=TRUE,
`visible`="(bf)"),
list(
`name`="name[bf]",
`title`="",
`type`="text",
`content`="Bayes factor\u2081\u2080",
`visible`="(bf)"),
list(
`name`="stat[bf]",
`title`="Statistic",
`type`="number",
`visible`="(bf)",
`refs`=list(
"BF",
"btt")),
list(
`name`="err[bf]",
`title`="\u00B1%",
`type`="number",
`visible`="(bf)"),
list(
`name`="df[bf]",
`title`="df",
`type`="number",
`visible`="(bf)",
`content`=""),
list(
`name`="p[bf]",
`title`="p",
`type`="number",
`format`="zto,pvalue",
`visible`="(bf)",
`content`=""),
list(
`name`="md[bf]",
`title`="Mean difference",
`type`="number",
`visible`="(meanDiff && bf)",
`content`=""),
list(
`name`="sed[bf]",
`title`="SE difference",
`type`="number",
`visible`="(meanDiff && bf)",
`content`=""),
list(
`name`="cil[bf]",
`title`="Lower",
`type`="number",
`visible`="(ci && meanDiff && bf)",
`content`=""),
list(
`name`="ciu[bf]",
`title`="Upper",
`type`="number",
`visible`="(ci && meanDiff && bf)",
`content`=""),
list(
`name`="esType[bf]",
`title`="",
`content`="",
`type`="text",
`visible`="(effectSize && bf)"),
list(
`name`="es[bf]",
`title`="Effect Size",
`type`="number",
`visible`="(effectSize && bf)",
`content`=""),
list(
`name`="ciles[bf]",
`title`="Lower",
`type`="number",
`visible`="(ciES && effectSize && bf)",
`content`=""),
list(
`name`="ciues[bf]",
`title`="Upper",
`type`="number",
`visible`="(ciES && effectSize && bf)",
`content`=""),
list(
`name`="var[welc]",
`title`="",
`content`="($key)",
`type`="text",
`combineBelow`=TRUE,
`visible`="(welchs)"),
list(
`name`="name[welc]",
`title`="",
`type`="text",
`content`="Welch's t",
`visible`="(welchs)"),
list(
`name`="stat[welc]",
`title`="Statistic",
`visible`="(welchs)"),
list(
`name`="err[welc]",
`title`="\u00B1%",
`type`="number",
`visible`="(welchs && bf)",
`content`=""),
list(
`name`="df[welc]",
`title`="df",
`type`="number",
`visible`="(welchs)"),
list(
`name`="p[welc]",
`title`="p",
`type`="number",
`format`="zto,pvalue",
`visible`="(welchs)"),
list(
`name`="md[welc]",
`title`="Mean difference",
`type`="number",
`visible`="(meanDiff && welchs)"),
list(
`name`="sed[welc]",
`title`="SE difference",
`type`="number",
`visible`="(meanDiff && welchs)"),
list(
`name`="cil[welc]",
`title`="Lower",
`type`="number",
`visible`="(ci && meanDiff && welchs)"),
list(
`name`="ciu[welc]",
`title`="Upper",
`type`="number",
`visible`="(ci && meanDiff && welchs)"),
list(
`name`="esType[welc]",
`title`="",
`content`="Cohen's d",
`type`="text",
`visible`="(effectSize && welchs)"),
list(
`name`="es[welc]",
`title`="Effect Size",
`type`="number",
`visible`="(effectSize && welchs)"),
list(
`name`="ciles[welc]",
`title`="Lower",
`type`="number",
`visible`="(ciES && effectSize && welchs)"),
list(
`name`="ciues[welc]",
`title`="Upper",
`type`="number",
`visible`="(ciES && effectSize && welchs)"),
list(
`name`="var[mann]",
`title`="",
`content`="($key)",
`type`="text",
`combineBelow`=TRUE,
`visible`="(mann)"),
list(
`name`="name[mann]",
`title`="",
`type`="text",
`content`="Mann-Whitney U",
`visible`="(mann)"),
list(
`name`="stat[mann]",
`title`="Statistic",
`content`=".",
`visible`="(mann)"),
list(
`name`="err[mann]",
`title`="\u00B1%",
`type`="number",
`visible`="(mann && bf)",
`content`=""),
list(
`name`="p[mann]",
`title`="p",
`type`="number",
`format`="zto,pvalue",
`visible`="(mann)"),
list(
`name`="md[mann]",
`title`="Mean difference",
`type`="number",
`visible`="(meanDiff && mann)"),
list(
`name`="sed[mann]",
`title`="SE difference",
`type`="number",
`visible`="(meanDiff && mann)"),
list(
`name`="cil[mann]",
`title`="Lower",
`type`="number",
`visible`="(ci && meanDiff && mann)"),
list(
`name`="ciu[mann]",
`title`="Upper",
`type`="number",
`visible`="(ci && meanDiff && mann)"),
list(
`name`="esType[mann]",
`title`="",
`content`="Rank biserial correlation",
`type`="text",
`visible`="(effectSize && mann)",
`refs`="Kerby2014"),
list(
`name`="es[mann]",
`title`="Effect Size",
`type`="number",
`visible`="(effectSize && mann)"),
list(
`name`="ciles[mann]",
`title`="Lower",
`type`="number",
`visible`="(ciES && effectSize && mann)"),
list(
`name`="ciues[mann]",
`title`="Upper",
`type`="number",
`visible`="(ciES && effectSize && mann)"))))
self$add(R6::R6Class(
inherit = jmvcore::Group,
active = list(
norm = function() private$.items[["norm"]],
eqv = function() private$.items[["eqv"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="assum",
title="Assumptions")
self$add(jmvcore::Table$new(
options=options,
name="norm",
title="Normality Test (Shapiro-Wilk)",
visible="(norm)",
rows="(vars)",
clearWith=list(
"miss",
"group"),
notes=list(
`p`="A low p-value suggests a violation of the assumption of normality"),
columns=list(
list(
`name`="name",
`title`="",
`content`="($key)",
`type`="text"),
list(
`name`="w",
`title`="W",
`type`="number"),
list(
`name`="p",
`title`="p",
`type`="number",
`format`="zto,pvalue"))))
self$add(jmvcore::Table$new(
options=options,
name="eqv",
title="Homogeneity of Variances Test (Levene's)",
visible="(eqv)",
rows="(vars)",
clearWith=list(
"group",
"miss"),
notes=list(
`p`="A low p-value suggests a violation of the assumption of equal variances"),
refs="car",
columns=list(
list(
`name`="name",
`title`="",
`content`="($key)",
`type`="text"),
list(
`name`="f",
`title`="F",
`type`="number"),
list(
`name`="df",
`type`="number"),
list(
`name`="df2",
`type`="number"),
list(
`name`="p",
`type`="number",
`format`="zto,pvalue"))))}))$new(options=options))
self$add(jmvcore::Table$new(
options=options,
name="desc",
title="Group Descriptives",
visible="(desc)",
rows="(vars)",
clearWith=list(
"group",
"miss"),
columns=list(
list(
`name`="dep",
`title`="",
`content`="($key)",
`type`="text"),
list(
`name`="group[1]",
`title`="Group",
`type`="text"),
list(
`name`="num[1]",
`title`="N",
`type`="integer"),
list(
`name`="mean[1]",
`title`="Mean",
`type`="number"),
list(
`name`="med[1]",
`title`="Median",
`type`="number"),
list(
`name`="sd[1]",
`title`="SD",
`type`="number"),
list(
`name`="se[1]",
`title`="SE",
`type`="number"),
list(
`name`="group[2]",
`title`="Group",
`type`="text"),
list(
`name`="num[2]",
`title`="N",
`type`="integer"),
list(
`name`="mean[2]",
`title`="Mean",
`type`="number"),
list(
`name`="med[2]",
`title`="Median",
`type`="number"),
list(
`name`="sd[2]",
`title`="SD",
`type`="number"),
list(
`name`="se[2]",
`title`="SE",
`type`="number"))))
self$add(jmvcore::Array$new(
options=options,
name="plots",
title="Plots",
items="(vars)",
clearWith=list(
"group",
"miss",
"ciWidth"),
template=R6::R6Class(
inherit = jmvcore::Group,
active = list(
desc = function() private$.items[["desc"]],
qq = function() private$.items[["qq"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="undefined",
title="$key")
self$add(jmvcore::Image$new(
options=options,
name="desc",
visible="(plots)",
renderFun=".desc",
clearWith=list()))
self$add(jmvcore::Image$new(
options=options,
name="qq",
width=350,
height=300,
requiresData=TRUE,
visible="(qq)",
renderFun=".qq",
clearWith=list()))}))$new(options=options)))}))
ttestISBase <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"ttestISBase",
inherit = jmvcore::Analysis,
public = list(
initialize = function(options, data=NULL, datasetId="", analysisId="", revision=0) {
super$initialize(
package = "jmv",
name = "ttestIS",
version = c(1,0,0),
options = options,
results = ttestISResults$new(options=options),
data = data,
datasetId = datasetId,
analysisId = analysisId,
revision = revision,
pause = NULL,
completeWhenFilled = TRUE,
requiresMissings = FALSE,
weightsSupport = 'auto')
}))
#' Independent Samples T-Test
#'
#' The Student's Independent samples t-test (sometimes called a two-samples
#' t-test) is used to test the null hypothesis that two groups have the
#' same mean. A low p-value suggests that the null hypothesis is not true,
#' and therefore the group means are different.
#'
#' The Student's independent t-test assumes that the data from each group
#' are from a normal distribution, and that the variances of these groups
#' are equal. If unwilling to assume the groups have equal variances, the
#' Welch's t-test can be used in it's place. If one is additionally
#' unwilling to assume the data from each group are from a normal
#' distribution, the non-parametric Mann-Whitney U test can be used instead
#' (However, note that the Mann-Whitney U test has a slightly different
#' null hypothesis; that the distributions of each group is equal).
#'
#'
#' @examples
#' data('ToothGrowth')
#'
#' ttestIS(formula = len ~ supp, data = ToothGrowth)
#'
#' #
#' # INDEPENDENT SAMPLES T-TEST
#' #
#' # Independent Samples T-Test
#' # ----------------------------------------------------
#' # statistic df p
#' # ----------------------------------------------------
#' # len Student's t 1.92 58.0 0.060
#' # ----------------------------------------------------
#' #
#'
#' @param data the data as a data frame
#' @param vars the dependent variables (not necessary when using a formula,
#' see the examples)
#' @param group the grouping variable with two levels (not necessary when
#' using a formula, see the examples)
#' @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 0.01 and 2 (default 0.707), the prior width
#' to use in calculating Bayes factors
#' @param welchs \code{TRUE} or \code{FALSE} (default), perform Welch's
#' t-tests
#' @param mann \code{TRUE} or \code{FALSE} (default), perform Mann-Whitney U
#' tests
#' @param hypothesis \code{'different'} (default), \code{'oneGreater'} or
#' \code{'twoGreater'}, the alternative hypothesis; group 1 different to group
#' 2, group 1 greater than group 2, and group 2 greater than group 1
#' respectively
#' @param norm \code{TRUE} or \code{FALSE} (default), perform Shapiro-Wilk
#' tests of normality
#' @param qq \code{TRUE} or \code{FALSE} (default), provide Q-Q plots of
#' residuals
#' @param eqv \code{TRUE} or \code{FALSE} (default), perform Levene's tests
#' for homogeneity of variances
#' @param meanDiff \code{TRUE} or \code{FALSE} (default), provide means and
#' standard errors
#' @param ci \code{TRUE} or \code{FALSE} (default), provide confidence
#' intervals
#' @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 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 formula (optional) the formula to use, see the examples
#' @return A results object containing:
#' \tabular{llllll}{
#' \code{results$ttest} \tab \tab \tab \tab \tab a table containing the t-test results \cr
#' \code{results$assum$norm} \tab \tab \tab \tab \tab a table containing the normality tests \cr
#' \code{results$assum$eqv} \tab \tab \tab \tab \tab a table containing the homogeneity of variances tests \cr
#' \code{results$desc} \tab \tab \tab \tab \tab a table containing the group descriptives \cr
#' \code{results$plots} \tab \tab \tab \tab \tab an array of groups of plots \cr
#' }
#'
#' Tables can be converted to data frames with \code{asDF} or \code{\link{as.data.frame}}. For example:
#'
#' \code{results$ttest$asDF}
#'
#' \code{as.data.frame(results$ttest)}
#'
#' @export
ttestIS <- function(
data,
vars,
group,
students = TRUE,
bf = FALSE,
bfPrior = 0.707,
welchs = FALSE,
mann = FALSE,
hypothesis = "different",
norm = FALSE,
qq = FALSE,
eqv = FALSE,
meanDiff = FALSE,
ci = FALSE,
ciWidth = 95,
effectSize = FALSE,
ciES = FALSE,
ciWidthES = 95,
desc = FALSE,
plots = FALSE,
miss = "perAnalysis",
formula) {
if ( ! requireNamespace("jmvcore", quietly=TRUE))
stop("ttestIS requires jmvcore to be installed (restart may be required)")
if ( ! missing(formula)) {
if (missing(vars))
vars <- jmvcore::marshalFormula(
formula=formula,
data=`if`( ! missing(data), data, NULL),
from="lhs",
required=TRUE)
if (missing(group))
group <- jmvcore::marshalFormula(
formula=formula,
data=`if`( ! missing(data), data, NULL),
from="rhs",
subset="1")
}
if ( ! missing(vars)) vars <- jmvcore::resolveQuo(jmvcore::enquo(vars))
if ( ! missing(group)) group <- jmvcore::resolveQuo(jmvcore::enquo(group))
if (missing(data))
data <- jmvcore::marshalData(
parent.frame(),
`if`( ! missing(vars), vars, NULL),
`if`( ! missing(group), group, NULL))
for (v in group) if (v %in% names(data)) data[[v]] <- as.factor(data[[v]])
options <- ttestISOptions$new(
vars = vars,
group = group,
students = students,
bf = bf,
bfPrior = bfPrior,
welchs = welchs,
mann = mann,
hypothesis = hypothesis,
norm = norm,
qq = qq,
eqv = eqv,
meanDiff = meanDiff,
ci = ci,
ciWidth = ciWidth,
effectSize = effectSize,
ciES = ciES,
ciWidthES = ciWidthES,
desc = desc,
plots = plots,
miss = miss)
analysis <- ttestISClass$new(
options = options,
data = data)
analysis$run()
analysis$results
}
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