R/rdesc.h.R
In jamovi/walrus: Robust Statistical Methods
Defines functions
rdesc
Documented in
rdesc
# This file is automatically generated, you probably don't want to edit this
rdescOptions <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"rdescOptions",
inherit = jmvcore::Options,
public = list(
initialize = function(
vars = NULL,
splitBy = NULL,
mean = TRUE,
trim = TRUE,
tr = 0.2,
win = FALSE,
wl = 0.2,
mest = FALSE,
bend = 1.28,
med = FALSE, ...) {
super$initialize(
package="walrus",
name="rdesc",
requiresData=TRUE,
...)
private$..vars <- jmvcore::OptionVariables$new(
"vars",
vars,
suggested=list(
"continuous"),
permitted=list(
"numeric"))
private$..splitBy <- jmvcore::OptionVariable$new(
"splitBy",
splitBy,
default=NULL,
suggested=list(
"nominal"),
permitted=list(
"factor"))
private$..mean <- jmvcore::OptionBool$new(
"mean",
mean,
default=TRUE)
private$..trim <- jmvcore::OptionBool$new(
"trim",
trim,
default=TRUE)
private$..tr <- jmvcore::OptionNumber$new(
"tr",
tr,
default=0.2,
min=0,
max=0.5)
private$..win <- jmvcore::OptionBool$new(
"win",
win,
default=FALSE)
private$..wl <- jmvcore::OptionNumber$new(
"wl",
wl,
default=0.2,
min=0,
max=0.5)
private$..mest <- jmvcore::OptionBool$new(
"mest",
mest,
default=FALSE)
private$..bend <- jmvcore::OptionNumber$new(
"bend",
bend,
default=1.28)
private$..med <- jmvcore::OptionBool$new(
"med",
med,
default=FALSE)
self$.addOption(private$..vars)
self$.addOption(private$..splitBy)
self$.addOption(private$..mean)
self$.addOption(private$..trim)
self$.addOption(private$..tr)
self$.addOption(private$..win)
self$.addOption(private$..wl)
self$.addOption(private$..mest)
self$.addOption(private$..bend)
self$.addOption(private$..med)
}),
active = list(
vars = function() private$..vars$value,
splitBy = function() private$..splitBy$value,
mean = function() private$..mean$value,
trim = function() private$..trim$value,
tr = function() private$..tr$value,
win = function() private$..win$value,
wl = function() private$..wl$value,
mest = function() private$..mest$value,
bend = function() private$..bend$value,
med = function() private$..med$value),
private = list(
..vars = NA,
..splitBy = NA,
..mean = NA,
..trim = NA,
..tr = NA,
..win = NA,
..wl = NA,
..mest = NA,
..bend = NA,
..med = NA)
)
rdescResults <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"rdescResults",
inherit = jmvcore::Group,
active = list(
table = function() private$.items[["table"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="",
title="Robust Descriptives")
self$add(jmvcore::Table$new(
options=options,
name="table",
title="Robust Descriptives",
clearWith=list(
"tr",
"wl",
"bend",
"splitBy"),
columns=list(
list(
`name`="var",
`title`="",
`type`="text",
`combineBelow`=TRUE),
list(
`name`="level",
`title`="",
`type`="text",
`visible`="(splitBy)"),
list(
`name`="s[m]",
`title`="",
`type`="text",
`content`="Mean",
`visible`="(mean)"),
list(
`name`="m[m]",
`title`="",
`visible`="(mean)"),
list(
`name`="se[m]",
`title`="SE",
`visible`="(mean)"),
list(
`name`="s[tr]",
`title`="",
`type`="text",
`content`="Trimmed mean",
`visible`="(trim)"),
list(
`name`="m[tr]",
`title`="",
`visible`="(trim)"),
list(
`name`="se[tr]",
`title`="SE",
`visible`="(trim)"),
list(
`name`="s[w]",
`title`="",
`type`="text",
`content`="Winsorized mean",
`visible`="(win)"),
list(
`name`="m[w]",
`title`="",
`visible`="(win)"),
list(
`name`="se[w]",
`title`="SE",
`visible`="(win)"),
list(
`name`="s[est]",
`title`="",
`type`="text",
`content`="M-estimator",
`visible`="(mest)"),
list(
`name`="m[est]",
`title`="",
`visible`="(mest)"),
list(
`name`="se[est]",
`title`="SE",
`visible`="(mest)"),
list(
`name`="s[med]",
`title`="",
`type`="text",
`content`="Median",
`visible`="(med)"),
list(
`name`="m[med]",
`title`="",
`visible`="(med)"),
list(
`name`="se[med]",
`title`="SE",
`visible`="(med)"))))}))
rdescBase <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"rdescBase",
inherit = jmvcore::Analysis,
public = list(
initialize = function(options, data=NULL, datasetId="", analysisId="", revision=0) {
super$initialize(
package = "walrus",
name = "rdesc",
version = c(1,0,0),
options = options,
results = rdescResults$new(options=options),
data = data,
datasetId = datasetId,
analysisId = analysisId,
revision = revision,
pause = NULL,
completeWhenFilled = FALSE,
requiresMissings = FALSE)
}))
#' Robust Descriptives
#'
#' Robust Descriptives
#'
#' @examples
#'
#' data('eurosoccer', package='WRS2')
#'
#' SpainGermany <- subset(eurosoccer, eurosoccer$League == 'Spain' | eurosoccer$League == 'Germany')
#' SpainGermany <- droplevels(SpainGermany)
#'
#' walrus::rdesc(
#' data = SpainGermany,
#' vars = "GoalsGame",
#' splitBy = "League",
#' med = TRUE)
#'
#' #
#' # ROBUST DESCRIPTIVES
#' #
#' # Robust Descriptives
#' # ----------------------------------------------------------
#' # SE
#' # ----------------------------------------------------------
#' # GoalsGame Germany Mean 1.46 0.105
#' # Trimmed mean 1.45 0.1341
#' # Median 1.43 0.1599
#' #
#' # Spain Mean 1.45 0.101
#' # Trimmed mean 1.33 0.0601
#' # Median 1.30 0.0766
#' # ----------------------------------------------------------
#' #
#'
#' @param data the data as a data frame
#' @param vars a vector of strings naming the variables in \code{data} of
#' interest
#' @param splitBy a string naming the variable in \code{data} to split the
#' data by
#' @param mean \code{TRUE} (default) or \code{FALSE}, provide a 'normal'
#' arithmetic mean
#' @param trim \code{TRUE} (default) or \code{FALSE}, provide a trimmed mean
#' @param tr a number between 0 and 0.5 (default: 0.2); the proportion of
#' measurements to trim from each end when producing trimmed means
#' @param win \code{TRUE} or \code{FALSE} (default), provide a 'Winsorized'
#' mean
#' @param wl a number between 0 and 0.5 (default: 0.2); the level of
#' 'winsorizing' when producing winsorized means
#' @param mest \code{TRUE} or \code{FALSE} (default), provide an 'M-estimated'
#' value
#' @param bend a number (default: 1.28), the bending constant to use when
#' using M-estimators
#' @param med \code{TRUE} or \code{FALSE} (default), provide medians
#' @return A results object containing:
#' \tabular{llllll}{
#' \code{results$table} \tab \tab \tab \tab \tab the table of descriptives \cr
#' }
#'
#' Tables can be converted to data frames with \code{asDF} or \code{\link{as.data.frame}}. For example:
#'
#' \code{results$table$asDF}
#'
#' \code{as.data.frame(results$table)}
#'
#' @export
rdesc <- function(
data,
vars,
splitBy = NULL,
mean = TRUE,
trim = TRUE,
tr = 0.2,
win = FALSE,
wl = 0.2,
mest = FALSE,
bend = 1.28,
med = FALSE) {
if ( ! requireNamespace("jmvcore", quietly=TRUE))
stop("rdesc requires jmvcore to be installed (restart may be required)")
if ( ! missing(vars)) vars <- jmvcore::resolveQuo(jmvcore::enquo(vars))
if ( ! missing(splitBy)) splitBy <- jmvcore::resolveQuo(jmvcore::enquo(splitBy))
if (missing(data))
data <- jmvcore::marshalData(
parent.frame(),
`if`( ! missing(vars), vars, NULL),
`if`( ! missing(splitBy), splitBy, NULL))
for (v in splitBy) if (v %in% names(data)) data[[v]] <- as.factor(data[[v]])
options <- rdescOptions$new(
vars = vars,
splitBy = splitBy,
mean = mean,
trim = trim,
tr = tr,
win = win,
wl = wl,
mest = mest,
bend = bend,
med = med)
analysis <- rdescClass$new(
options = options,
data = data)
analysis$run()
analysis$results
}
jamovi/walrus documentation built on July 21, 2023, 7:31 p.m.
R Package Documentation
Browse R Packages
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Defines functions rdesc
Documented in rdesc
# This file is automatically generated, you probably don't want to edit this
rdescOptions <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"rdescOptions",
inherit = jmvcore::Options,
public = list(
initialize = function(
vars = NULL,
splitBy = NULL,
mean = TRUE,
trim = TRUE,
tr = 0.2,
win = FALSE,
wl = 0.2,
mest = FALSE,
bend = 1.28,
med = FALSE, ...) {
super$initialize(
package="walrus",
name="rdesc",
requiresData=TRUE,
...)
private$..vars <- jmvcore::OptionVariables$new(
"vars",
vars,
suggested=list(
"continuous"),
permitted=list(
"numeric"))
private$..splitBy <- jmvcore::OptionVariable$new(
"splitBy",
splitBy,
default=NULL,
suggested=list(
"nominal"),
permitted=list(
"factor"))
private$..mean <- jmvcore::OptionBool$new(
"mean",
mean,
default=TRUE)
private$..trim <- jmvcore::OptionBool$new(
"trim",
trim,
default=TRUE)
private$..tr <- jmvcore::OptionNumber$new(
"tr",
tr,
default=0.2,
min=0,
max=0.5)
private$..win <- jmvcore::OptionBool$new(
"win",
win,
default=FALSE)
private$..wl <- jmvcore::OptionNumber$new(
"wl",
wl,
default=0.2,
min=0,
max=0.5)
private$..mest <- jmvcore::OptionBool$new(
"mest",
mest,
default=FALSE)
private$..bend <- jmvcore::OptionNumber$new(
"bend",
bend,
default=1.28)
private$..med <- jmvcore::OptionBool$new(
"med",
med,
default=FALSE)
self$.addOption(private$..vars)
self$.addOption(private$..splitBy)
self$.addOption(private$..mean)
self$.addOption(private$..trim)
self$.addOption(private$..tr)
self$.addOption(private$..win)
self$.addOption(private$..wl)
self$.addOption(private$..mest)
self$.addOption(private$..bend)
self$.addOption(private$..med)
}),
active = list(
vars = function() private$..vars$value,
splitBy = function() private$..splitBy$value,
mean = function() private$..mean$value,
trim = function() private$..trim$value,
tr = function() private$..tr$value,
win = function() private$..win$value,
wl = function() private$..wl$value,
mest = function() private$..mest$value,
bend = function() private$..bend$value,
med = function() private$..med$value),
private = list(
..vars = NA,
..splitBy = NA,
..mean = NA,
..trim = NA,
..tr = NA,
..win = NA,
..wl = NA,
..mest = NA,
..bend = NA,
..med = NA)
)
rdescResults <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"rdescResults",
inherit = jmvcore::Group,
active = list(
table = function() private$.items[["table"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="",
title="Robust Descriptives")
self$add(jmvcore::Table$new(
options=options,
name="table",
title="Robust Descriptives",
clearWith=list(
"tr",
"wl",
"bend",
"splitBy"),
columns=list(
list(
`name`="var",
`title`="",
`type`="text",
`combineBelow`=TRUE),
list(
`name`="level",
`title`="",
`type`="text",
`visible`="(splitBy)"),
list(
`name`="s[m]",
`title`="",
`type`="text",
`content`="Mean",
`visible`="(mean)"),
list(
`name`="m[m]",
`title`="",
`visible`="(mean)"),
list(
`name`="se[m]",
`title`="SE",
`visible`="(mean)"),
list(
`name`="s[tr]",
`title`="",
`type`="text",
`content`="Trimmed mean",
`visible`="(trim)"),
list(
`name`="m[tr]",
`title`="",
`visible`="(trim)"),
list(
`name`="se[tr]",
`title`="SE",
`visible`="(trim)"),
list(
`name`="s[w]",
`title`="",
`type`="text",
`content`="Winsorized mean",
`visible`="(win)"),
list(
`name`="m[w]",
`title`="",
`visible`="(win)"),
list(
`name`="se[w]",
`title`="SE",
`visible`="(win)"),
list(
`name`="s[est]",
`title`="",
`type`="text",
`content`="M-estimator",
`visible`="(mest)"),
list(
`name`="m[est]",
`title`="",
`visible`="(mest)"),
list(
`name`="se[est]",
`title`="SE",
`visible`="(mest)"),
list(
`name`="s[med]",
`title`="",
`type`="text",
`content`="Median",
`visible`="(med)"),
list(
`name`="m[med]",
`title`="",
`visible`="(med)"),
list(
`name`="se[med]",
`title`="SE",
`visible`="(med)"))))}))
rdescBase <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"rdescBase",
inherit = jmvcore::Analysis,
public = list(
initialize = function(options, data=NULL, datasetId="", analysisId="", revision=0) {
super$initialize(
package = "walrus",
name = "rdesc",
version = c(1,0,0),
options = options,
results = rdescResults$new(options=options),
data = data,
datasetId = datasetId,
analysisId = analysisId,
revision = revision,
pause = NULL,
completeWhenFilled = FALSE,
requiresMissings = FALSE)
}))
#' Robust Descriptives
#'
#' Robust Descriptives
#'
#' @examples
#'
#' data('eurosoccer', package='WRS2')
#'
#' SpainGermany <- subset(eurosoccer, eurosoccer$League == 'Spain' | eurosoccer$League == 'Germany')
#' SpainGermany <- droplevels(SpainGermany)
#'
#' walrus::rdesc(
#' data = SpainGermany,
#' vars = "GoalsGame",
#' splitBy = "League",
#' med = TRUE)
#'
#' #
#' # ROBUST DESCRIPTIVES
#' #
#' # Robust Descriptives
#' # ----------------------------------------------------------
#' # SE
#' # ----------------------------------------------------------
#' # GoalsGame Germany Mean 1.46 0.105
#' # Trimmed mean 1.45 0.1341
#' # Median 1.43 0.1599
#' #
#' # Spain Mean 1.45 0.101
#' # Trimmed mean 1.33 0.0601
#' # Median 1.30 0.0766
#' # ----------------------------------------------------------
#' #
#'
#' @param data the data as a data frame
#' @param vars a vector of strings naming the variables in \code{data} of
#' interest
#' @param splitBy a string naming the variable in \code{data} to split the
#' data by
#' @param mean \code{TRUE} (default) or \code{FALSE}, provide a 'normal'
#' arithmetic mean
#' @param trim \code{TRUE} (default) or \code{FALSE}, provide a trimmed mean
#' @param tr a number between 0 and 0.5 (default: 0.2); the proportion of
#' measurements to trim from each end when producing trimmed means
#' @param win \code{TRUE} or \code{FALSE} (default), provide a 'Winsorized'
#' mean
#' @param wl a number between 0 and 0.5 (default: 0.2); the level of
#' 'winsorizing' when producing winsorized means
#' @param mest \code{TRUE} or \code{FALSE} (default), provide an 'M-estimated'
#' value
#' @param bend a number (default: 1.28), the bending constant to use when
#' using M-estimators
#' @param med \code{TRUE} or \code{FALSE} (default), provide medians
#' @return A results object containing:
#' \tabular{llllll}{
#' \code{results$table} \tab \tab \tab \tab \tab the table of descriptives \cr
#' }
#'
#' Tables can be converted to data frames with \code{asDF} or \code{\link{as.data.frame}}. For example:
#'
#' \code{results$table$asDF}
#'
#' \code{as.data.frame(results$table)}
#'
#' @export
rdesc <- function(
data,
vars,
splitBy = NULL,
mean = TRUE,
trim = TRUE,
tr = 0.2,
win = FALSE,
wl = 0.2,
mest = FALSE,
bend = 1.28,
med = FALSE) {
if ( ! requireNamespace("jmvcore", quietly=TRUE))
stop("rdesc requires jmvcore to be installed (restart may be required)")
if ( ! missing(vars)) vars <- jmvcore::resolveQuo(jmvcore::enquo(vars))
if ( ! missing(splitBy)) splitBy <- jmvcore::resolveQuo(jmvcore::enquo(splitBy))
if (missing(data))
data <- jmvcore::marshalData(
parent.frame(),
`if`( ! missing(vars), vars, NULL),
`if`( ! missing(splitBy), splitBy, NULL))
for (v in splitBy) if (v %in% names(data)) data[[v]] <- as.factor(data[[v]])
options <- rdescOptions$new(
vars = vars,
splitBy = splitBy,
mean = mean,
trim = trim,
tr = tr,
win = win,
wl = wl,
mest = mest,
bend = bend,
med = med)
analysis <- rdescClass$new(
options = options,
data = data)
analysis$run()
analysis$results
}
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