R/rttestis.h.R
In jamovi/walrus: Robust Statistical Methods
Defines functions
rttestIS
Documented in
rttestIS
# This file is automatically generated, you probably don't want to edit this
rttestISOptions <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"rttestISOptions",
inherit = jmvcore::Options,
public = list(
initialize = function(
deps = NULL,
group = NULL,
yuen = TRUE,
tr = 0.2,
mest = FALSE,
method = "mom",
yuenbt = FALSE,
nboot = 599,
md = FALSE,
ci = FALSE,
es = FALSE,
esci = FALSE, ...) {
super$initialize(
package="walrus",
name="rttestIS",
requiresData=TRUE,
...)
private$..deps <- jmvcore::OptionVariables$new(
"deps",
deps,
suggested=list(
"continuous"),
permitted=list(
"numeric"))
private$..group <- jmvcore::OptionVariable$new(
"group",
group,
suggested=list(
"nominal"),
permitted=list(
"factor"))
private$..yuen <- jmvcore::OptionBool$new(
"yuen",
yuen,
default=TRUE)
private$..tr <- jmvcore::OptionNumber$new(
"tr",
tr,
default=0.2,
min=0,
max=0.5)
private$..mest <- jmvcore::OptionBool$new(
"mest",
mest,
default=FALSE)
private$..method <- jmvcore::OptionList$new(
"method",
method,
options=list(
"onestep",
"mom",
"median",
"mean"),
default="mom")
private$..yuenbt <- jmvcore::OptionBool$new(
"yuenbt",
yuenbt,
default=FALSE)
private$..nboot <- jmvcore::OptionInteger$new(
"nboot",
nboot,
min=0,
default=599)
private$..md <- jmvcore::OptionBool$new(
"md",
md,
default=FALSE)
private$..ci <- jmvcore::OptionBool$new(
"ci",
ci,
default=FALSE)
private$..es <- jmvcore::OptionBool$new(
"es",
es,
default=FALSE)
private$..esci <- jmvcore::OptionBool$new(
"esci",
esci,
default=FALSE)
self$.addOption(private$..deps)
self$.addOption(private$..group)
self$.addOption(private$..yuen)
self$.addOption(private$..tr)
self$.addOption(private$..mest)
self$.addOption(private$..method)
self$.addOption(private$..yuenbt)
self$.addOption(private$..nboot)
self$.addOption(private$..md)
self$.addOption(private$..ci)
self$.addOption(private$..es)
self$.addOption(private$..esci)
}),
active = list(
deps = function() private$..deps$value,
group = function() private$..group$value,
yuen = function() private$..yuen$value,
tr = function() private$..tr$value,
mest = function() private$..mest$value,
method = function() private$..method$value,
yuenbt = function() private$..yuenbt$value,
nboot = function() private$..nboot$value,
md = function() private$..md$value,
ci = function() private$..ci$value,
es = function() private$..es$value,
esci = function() private$..esci$value),
private = list(
..deps = NA,
..group = NA,
..yuen = NA,
..tr = NA,
..mest = NA,
..method = NA,
..yuenbt = NA,
..nboot = NA,
..md = NA,
..ci = NA,
..es = NA,
..esci = NA)
)
rttestISResults <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"rttestISResults",
inherit = jmvcore::Group,
active = list(
ttest = function() private$.items[["ttest"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="",
title="Robust Independent Samples T-Test")
self$add(jmvcore::Table$new(
options=options,
name="ttest",
title="Robust Independent Samples T-Test",
rows="(deps)",
clearWith=list(
"group",
"method",
"tr",
"nboot"),
columns=list(
list(
`name`="var",
`title`="",
`type`="text",
`content`="($key)"),
list(
`name`="test[yuen]",
`title`="",
`type`="text",
`content`="Yuen's test",
`visible`="(yuen)"),
list(
`name`="t[yuen]",
`title`="t",
`type`="number",
`visible`="(yuen)"),
list(
`name`="df[yuen]",
`title`="df",
`type`="number",
`visible`="(yuen)"),
list(
`name`="p[yuen]",
`title`="p",
`type`="number",
`format`="zto,pvalue",
`visible`="(yuen)"),
list(
`name`="md[yuen]",
`title`="Mean diff",
`type`="number",
`visible`="(yuen && md)"),
list(
`name`="cil[yuen]",
`superTitle`="95% Confidence Interval",
`title`="Lower",
`type`="number",
`visible`="(yuen && ci)"),
list(
`name`="ciu[yuen]",
`superTitle`="95% Confidence Interval",
`title`="Upper",
`type`="number",
`visible`="(yuen && ci)"),
list(
`name`="es[yuen]",
`title`="\u03BE",
`type`="number",
`visible`="(yuen && es)"),
list(
`name`="escil[yuen]",
`superTitle`="95% \u03BE Confidence Interval",
`title`="Lower",
`type`="number",
`visible`="(yuen && esci)"),
list(
`name`="esciu[yuen]",
`superTitle`="95% \u03BE Confidence Interval",
`title`="Upper",
`type`="number",
`visible`="(yuen && esci)"),
list(
`name`="test[yuenbt]",
`title`="",
`type`="text",
`content`="Yuen's bootstrapped",
`visible`="(yuen && yuenbt)"),
list(
`name`="t[yuenbt]",
`title`="t",
`type`="number",
`visible`="(yuen && yuenbt)"),
list(
`name`="df[yuenbt]",
`title`="df",
`type`="number",
`visible`="(yuen && yuenbt)"),
list(
`name`="p[yuenbt]",
`title`="p",
`type`="number",
`format`="zto,pvalue",
`visible`="(yuen && yuenbt)"),
list(
`name`="test[mest]",
`title`="",
`type`="text",
`content`="M-estimator",
`visible`="(mest)"),
list(
`name`="t[mest]",
`title`="t",
`type`="number",
`visible`="(mest)"),
list(
`name`="df[mest]",
`title`="df",
`type`="number",
`visible`="(mest)"),
list(
`name`="p[mest]",
`title`="p",
`type`="number",
`format`="zto,pvalue",
`visible`="(mest)"))))}))
rttestISBase <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"rttestISBase",
inherit = jmvcore::Analysis,
public = list(
initialize = function(options, data=NULL, datasetId="", analysisId="", revision=0) {
super$initialize(
package = "walrus",
name = "rttestIS",
version = c(1,0,0),
options = options,
results = rttestISResults$new(options=options),
data = data,
datasetId = datasetId,
analysisId = analysisId,
revision = revision,
pause = NULL,
completeWhenFilled = TRUE,
requiresMissings = FALSE,
weightsSupport = 'auto')
}))
#' Robust Independent Samples T-Test
#'
#' Robust Independent Samples T-Test
#'
#' @examples
#' data('eurosoccer', package='WRS2')
#'
#' SpainGermany <- subset(eurosoccer, eurosoccer$League == 'Spain' | eurosoccer$League == 'Germany')
#' SpainGermany <- droplevels(SpainGermany)
#'
#' rttestIS(SpainGermany,
#' dep = 'GoalsScored',
#' group = 'League',
#' yuen = TRUE,
#' mest = TRUE)
#'
#' #
#' # ROBUST INDEPENDENT SAMPLES T-TEST
#' #
#' # Robust Independent Samples T-Test
#' # ---------------------------------------------------------
#' # t df p
#' # ---------------------------------------------------------
#' # GoalsScored Yuen's test 0.297 17.3 0.770
#' # M-estimator -0.933 0.993
#' # ---------------------------------------------------------
#' #
#'
#' @param data the data as a data frame
#' @param deps a vector of strings naming the dependent variables in
#' \code{data}
#' @param group a string naming the grouping variable in \code{data}; must
#' have 2 levels
#' @param yuen \code{TRUE} (default) or \code{FALSE}, use the Yuen's trim
#' method
#' @param tr a number between 0 and 0.5, (default: 0.2), the proportion of
#' measurements to trim from each end, when using the trim and bootstrap
#' methods
#' @param mest \code{TRUE} or \code{FALSE} (default), use an M-estimator
#' @param method \code{'onestep'}, \code{'mom'} (default) or \code{'median'},
#' the M-estimator to use; One-step, Modified one-step or Median respectively
#' @param yuenbt \code{TRUE} or \code{FALSE} (default), use the Yuen's
#' bootstrap method
#' @param nboot a number (default: 599) specifying the number of bootstrap
#' samples to use when using the bootstrap method
#' @param md \code{TRUE} or \code{FALSE} (default), provide the mean
#' difference
#' @param ci \code{TRUE} or \code{FALSE} (default), provide a 95\% confidence
#' interval on the mean difference
#' @param es \code{TRUE} or \code{FALSE} (default), provide the effect-size
#' @param esci \code{TRUE} or \code{FALSE} (default), provide a 95\%
#' confidence interval on the effect-size
#' @return A results object containing:
#' \tabular{llllll}{
#' \code{results$ttest} \tab \tab \tab \tab \tab the table of t-test results \cr
#' }
#'
#' Tables can be converted to data frames with \code{asDF} or \code{\link{as.data.frame}}. For example:
#'
#' \code{results$ttest$asDF}
#'
#' \code{as.data.frame(results$ttest)}
#'
#' @export
rttestIS <- function(
data,
deps,
group,
yuen = TRUE,
tr = 0.2,
mest = FALSE,
method = "mom",
yuenbt = FALSE,
nboot = 599,
md = FALSE,
ci = FALSE,
es = FALSE,
esci = FALSE) {
if ( ! requireNamespace("jmvcore", quietly=TRUE))
stop("rttestIS requires jmvcore to be installed (restart may be required)")
if ( ! missing(deps)) deps <- jmvcore::resolveQuo(jmvcore::enquo(deps))
if ( ! missing(group)) group <- jmvcore::resolveQuo(jmvcore::enquo(group))
if (missing(data))
data <- jmvcore::marshalData(
parent.frame(),
`if`( ! missing(deps), deps, NULL),
`if`( ! missing(group), group, NULL))
for (v in group) if (v %in% names(data)) data[[v]] <- as.factor(data[[v]])
options <- rttestISOptions$new(
deps = deps,
group = group,
yuen = yuen,
tr = tr,
mest = mest,
method = method,
yuenbt = yuenbt,
nboot = nboot,
md = md,
ci = ci,
es = es,
esci = esci)
analysis <- rttestISClass$new(
options = options,
data = data)
analysis$run()
analysis$results
}
jamovi/walrus documentation built on July 21, 2023, 7:31 p.m.
R Package Documentation
Browse R Packages
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Defines functions rttestIS
Documented in rttestIS
# This file is automatically generated, you probably don't want to edit this
rttestISOptions <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"rttestISOptions",
inherit = jmvcore::Options,
public = list(
initialize = function(
deps = NULL,
group = NULL,
yuen = TRUE,
tr = 0.2,
mest = FALSE,
method = "mom",
yuenbt = FALSE,
nboot = 599,
md = FALSE,
ci = FALSE,
es = FALSE,
esci = FALSE, ...) {
super$initialize(
package="walrus",
name="rttestIS",
requiresData=TRUE,
...)
private$..deps <- jmvcore::OptionVariables$new(
"deps",
deps,
suggested=list(
"continuous"),
permitted=list(
"numeric"))
private$..group <- jmvcore::OptionVariable$new(
"group",
group,
suggested=list(
"nominal"),
permitted=list(
"factor"))
private$..yuen <- jmvcore::OptionBool$new(
"yuen",
yuen,
default=TRUE)
private$..tr <- jmvcore::OptionNumber$new(
"tr",
tr,
default=0.2,
min=0,
max=0.5)
private$..mest <- jmvcore::OptionBool$new(
"mest",
mest,
default=FALSE)
private$..method <- jmvcore::OptionList$new(
"method",
method,
options=list(
"onestep",
"mom",
"median",
"mean"),
default="mom")
private$..yuenbt <- jmvcore::OptionBool$new(
"yuenbt",
yuenbt,
default=FALSE)
private$..nboot <- jmvcore::OptionInteger$new(
"nboot",
nboot,
min=0,
default=599)
private$..md <- jmvcore::OptionBool$new(
"md",
md,
default=FALSE)
private$..ci <- jmvcore::OptionBool$new(
"ci",
ci,
default=FALSE)
private$..es <- jmvcore::OptionBool$new(
"es",
es,
default=FALSE)
private$..esci <- jmvcore::OptionBool$new(
"esci",
esci,
default=FALSE)
self$.addOption(private$..deps)
self$.addOption(private$..group)
self$.addOption(private$..yuen)
self$.addOption(private$..tr)
self$.addOption(private$..mest)
self$.addOption(private$..method)
self$.addOption(private$..yuenbt)
self$.addOption(private$..nboot)
self$.addOption(private$..md)
self$.addOption(private$..ci)
self$.addOption(private$..es)
self$.addOption(private$..esci)
}),
active = list(
deps = function() private$..deps$value,
group = function() private$..group$value,
yuen = function() private$..yuen$value,
tr = function() private$..tr$value,
mest = function() private$..mest$value,
method = function() private$..method$value,
yuenbt = function() private$..yuenbt$value,
nboot = function() private$..nboot$value,
md = function() private$..md$value,
ci = function() private$..ci$value,
es = function() private$..es$value,
esci = function() private$..esci$value),
private = list(
..deps = NA,
..group = NA,
..yuen = NA,
..tr = NA,
..mest = NA,
..method = NA,
..yuenbt = NA,
..nboot = NA,
..md = NA,
..ci = NA,
..es = NA,
..esci = NA)
)
rttestISResults <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"rttestISResults",
inherit = jmvcore::Group,
active = list(
ttest = function() private$.items[["ttest"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="",
title="Robust Independent Samples T-Test")
self$add(jmvcore::Table$new(
options=options,
name="ttest",
title="Robust Independent Samples T-Test",
rows="(deps)",
clearWith=list(
"group",
"method",
"tr",
"nboot"),
columns=list(
list(
`name`="var",
`title`="",
`type`="text",
`content`="($key)"),
list(
`name`="test[yuen]",
`title`="",
`type`="text",
`content`="Yuen's test",
`visible`="(yuen)"),
list(
`name`="t[yuen]",
`title`="t",
`type`="number",
`visible`="(yuen)"),
list(
`name`="df[yuen]",
`title`="df",
`type`="number",
`visible`="(yuen)"),
list(
`name`="p[yuen]",
`title`="p",
`type`="number",
`format`="zto,pvalue",
`visible`="(yuen)"),
list(
`name`="md[yuen]",
`title`="Mean diff",
`type`="number",
`visible`="(yuen && md)"),
list(
`name`="cil[yuen]",
`superTitle`="95% Confidence Interval",
`title`="Lower",
`type`="number",
`visible`="(yuen && ci)"),
list(
`name`="ciu[yuen]",
`superTitle`="95% Confidence Interval",
`title`="Upper",
`type`="number",
`visible`="(yuen && ci)"),
list(
`name`="es[yuen]",
`title`="\u03BE",
`type`="number",
`visible`="(yuen && es)"),
list(
`name`="escil[yuen]",
`superTitle`="95% \u03BE Confidence Interval",
`title`="Lower",
`type`="number",
`visible`="(yuen && esci)"),
list(
`name`="esciu[yuen]",
`superTitle`="95% \u03BE Confidence Interval",
`title`="Upper",
`type`="number",
`visible`="(yuen && esci)"),
list(
`name`="test[yuenbt]",
`title`="",
`type`="text",
`content`="Yuen's bootstrapped",
`visible`="(yuen && yuenbt)"),
list(
`name`="t[yuenbt]",
`title`="t",
`type`="number",
`visible`="(yuen && yuenbt)"),
list(
`name`="df[yuenbt]",
`title`="df",
`type`="number",
`visible`="(yuen && yuenbt)"),
list(
`name`="p[yuenbt]",
`title`="p",
`type`="number",
`format`="zto,pvalue",
`visible`="(yuen && yuenbt)"),
list(
`name`="test[mest]",
`title`="",
`type`="text",
`content`="M-estimator",
`visible`="(mest)"),
list(
`name`="t[mest]",
`title`="t",
`type`="number",
`visible`="(mest)"),
list(
`name`="df[mest]",
`title`="df",
`type`="number",
`visible`="(mest)"),
list(
`name`="p[mest]",
`title`="p",
`type`="number",
`format`="zto,pvalue",
`visible`="(mest)"))))}))
rttestISBase <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"rttestISBase",
inherit = jmvcore::Analysis,
public = list(
initialize = function(options, data=NULL, datasetId="", analysisId="", revision=0) {
super$initialize(
package = "walrus",
name = "rttestIS",
version = c(1,0,0),
options = options,
results = rttestISResults$new(options=options),
data = data,
datasetId = datasetId,
analysisId = analysisId,
revision = revision,
pause = NULL,
completeWhenFilled = TRUE,
requiresMissings = FALSE,
weightsSupport = 'auto')
}))
#' Robust Independent Samples T-Test
#'
#' Robust Independent Samples T-Test
#'
#' @examples
#' data('eurosoccer', package='WRS2')
#'
#' SpainGermany <- subset(eurosoccer, eurosoccer$League == 'Spain' | eurosoccer$League == 'Germany')
#' SpainGermany <- droplevels(SpainGermany)
#'
#' rttestIS(SpainGermany,
#' dep = 'GoalsScored',
#' group = 'League',
#' yuen = TRUE,
#' mest = TRUE)
#'
#' #
#' # ROBUST INDEPENDENT SAMPLES T-TEST
#' #
#' # Robust Independent Samples T-Test
#' # ---------------------------------------------------------
#' # t df p
#' # ---------------------------------------------------------
#' # GoalsScored Yuen's test 0.297 17.3 0.770
#' # M-estimator -0.933 0.993
#' # ---------------------------------------------------------
#' #
#'
#' @param data the data as a data frame
#' @param deps a vector of strings naming the dependent variables in
#' \code{data}
#' @param group a string naming the grouping variable in \code{data}; must
#' have 2 levels
#' @param yuen \code{TRUE} (default) or \code{FALSE}, use the Yuen's trim
#' method
#' @param tr a number between 0 and 0.5, (default: 0.2), the proportion of
#' measurements to trim from each end, when using the trim and bootstrap
#' methods
#' @param mest \code{TRUE} or \code{FALSE} (default), use an M-estimator
#' @param method \code{'onestep'}, \code{'mom'} (default) or \code{'median'},
#' the M-estimator to use; One-step, Modified one-step or Median respectively
#' @param yuenbt \code{TRUE} or \code{FALSE} (default), use the Yuen's
#' bootstrap method
#' @param nboot a number (default: 599) specifying the number of bootstrap
#' samples to use when using the bootstrap method
#' @param md \code{TRUE} or \code{FALSE} (default), provide the mean
#' difference
#' @param ci \code{TRUE} or \code{FALSE} (default), provide a 95\% confidence
#' interval on the mean difference
#' @param es \code{TRUE} or \code{FALSE} (default), provide the effect-size
#' @param esci \code{TRUE} or \code{FALSE} (default), provide a 95\%
#' confidence interval on the effect-size
#' @return A results object containing:
#' \tabular{llllll}{
#' \code{results$ttest} \tab \tab \tab \tab \tab the table of t-test results \cr
#' }
#'
#' Tables can be converted to data frames with \code{asDF} or \code{\link{as.data.frame}}. For example:
#'
#' \code{results$ttest$asDF}
#'
#' \code{as.data.frame(results$ttest)}
#'
#' @export
rttestIS <- function(
data,
deps,
group,
yuen = TRUE,
tr = 0.2,
mest = FALSE,
method = "mom",
yuenbt = FALSE,
nboot = 599,
md = FALSE,
ci = FALSE,
es = FALSE,
esci = FALSE) {
if ( ! requireNamespace("jmvcore", quietly=TRUE))
stop("rttestIS requires jmvcore to be installed (restart may be required)")
if ( ! missing(deps)) deps <- jmvcore::resolveQuo(jmvcore::enquo(deps))
if ( ! missing(group)) group <- jmvcore::resolveQuo(jmvcore::enquo(group))
if (missing(data))
data <- jmvcore::marshalData(
parent.frame(),
`if`( ! missing(deps), deps, NULL),
`if`( ! missing(group), group, NULL))
for (v in group) if (v %in% names(data)) data[[v]] <- as.factor(data[[v]])
options <- rttestISOptions$new(
deps = deps,
group = group,
yuen = yuen,
tr = tr,
mest = mest,
method = method,
yuenbt = yuenbt,
nboot = nboot,
md = md,
ci = ci,
es = es,
esci = esci)
analysis <- rttestISClass$new(
options = options,
data = data)
analysis$run()
analysis$results
}
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