R/ranova.h.R
In jamovi/walrus: Robust Statistical Methods
Defines functions
ranova
Documented in
ranova
# This file is automatically generated, you probably don't want to edit this
ranovaOptions <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"ranovaOptions",
inherit = jmvcore::Options,
public = list(
initialize = function(
dep = NULL,
factors = NULL,
method = "trim",
tr = 0.2,
est = "mom",
nboot = 599,
dist = "proj",
ph = FALSE, ...) {
super$initialize(
package="walrus",
name="ranova",
requiresData=TRUE,
...)
private$..dep <- jmvcore::OptionVariable$new(
"dep",
dep,
suggested=list(
"continuous"),
permitted=list(
"numeric"))
private$..factors <- jmvcore::OptionVariables$new(
"factors",
factors,
suggested=list(
"nominal",
"ordinal"),
permitted=list(
"factor"),
default=NULL)
private$..method <- jmvcore::OptionList$new(
"method",
method,
options=list(
"median",
"trim",
"boot"),
default="trim")
private$..tr <- jmvcore::OptionNumber$new(
"tr",
tr,
min=0,
max=0.5,
default=0.2)
private$..est <- jmvcore::OptionList$new(
"est",
est,
options=list(
"onestep",
"mom",
"median"),
default="mom")
private$..nboot <- jmvcore::OptionInteger$new(
"nboot",
nboot,
min=0,
default=599)
private$..dist <- jmvcore::OptionList$new(
"dist",
dist,
options=list(
"maha",
"proj"),
default="proj")
private$..ph <- jmvcore::OptionBool$new(
"ph",
ph,
default=FALSE)
self$.addOption(private$..dep)
self$.addOption(private$..factors)
self$.addOption(private$..method)
self$.addOption(private$..tr)
self$.addOption(private$..est)
self$.addOption(private$..nboot)
self$.addOption(private$..dist)
self$.addOption(private$..ph)
}),
active = list(
dep = function() private$..dep$value,
factors = function() private$..factors$value,
method = function() private$..method$value,
tr = function() private$..tr$value,
est = function() private$..est$value,
nboot = function() private$..nboot$value,
dist = function() private$..dist$value,
ph = function() private$..ph$value),
private = list(
..dep = NA,
..factors = NA,
..method = NA,
..tr = NA,
..est = NA,
..nboot = NA,
..dist = NA,
..ph = NA)
)
ranovaResults <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"ranovaResults",
inherit = jmvcore::Group,
active = list(
main = function() private$.items[["main"]],
phs = function() private$.items[["phs"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="",
title="Robust ANOVA")
self$add(jmvcore::Table$new(
options=options,
name="main",
title="Robust ANOVA",
clearWith=list(
"dep",
"factors",
"method",
"nboot",
"tr",
"est",
"dist"),
columns=list(
list(
`name`="name",
`title`="",
`type`="text"),
list(
`name`="s",
`title`="F",
`type`="number"),
list(
`name`="critval",
`title`="Critical value",
`type`="number",
`visible`=FALSE),
list(
`name`="df1",
`title`="df1",
`type`="number",
`visible`=FALSE),
list(
`name`="df2",
`title`="df2",
`type`="number",
`visible`=FALSE),
list(
`name`="p",
`title`="p",
`type`="number",
`format`="zto,pvalue"),
list(
`name`="expvar",
`title`="Variance explained",
`type`="number",
`visible`=FALSE),
list(
`name`="es",
`title`="ES",
`type`="number",
`visible`=FALSE),
list(
`name`="escil",
`title`="Lower",
`superTitle`="Bootstrap CI",
`type`="number",
`visible`=FALSE),
list(
`name`="esciu",
`title`="Upper",
`superTitle`="Bootstrap CI",
`type`="number",
`visible`=FALSE))))
self$add(jmvcore::Array$new(
options=options,
name="phs",
title="Post Hoc Tests",
items=7,
template=jmvcore::Table$new(
options=options,
name="ph",
title="",
visible=FALSE,
clearWith=list(
"dep",
"factors",
"method",
"nboot",
"tr",
"est",
"dist"),
columns=list(
list(
`name`="v1",
`title`="",
`type`="text",
`combineBelow`=TRUE),
list(
`name`="v2",
`title`="",
`type`="text"),
list(
`name`="psi",
`title`="psi-hat",
`type`="number"),
list(
`name`="p",
`title`="p",
`type`="number",
`format`="zto,pvalue"),
list(
`name`="adjp",
`title`="adj.p",
`type`="number",
`format`="zto,pvalue",
`visible`=FALSE),
list(
`name`="cil",
`title`="Lower",
`superTitle`="95% Confidence interval",
`type`="number"),
list(
`name`="ciu",
`title`="Upper",
`superTitle`="95% Confidence interval",
`type`="number")))))}))
ranovaBase <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"ranovaBase",
inherit = jmvcore::Analysis,
public = list(
initialize = function(options, data=NULL, datasetId="", analysisId="", revision=0) {
super$initialize(
package = "walrus",
name = "ranova",
version = c(1,0,0),
options = options,
results = ranovaResults$new(options=options),
data = data,
datasetId = datasetId,
analysisId = analysisId,
revision = revision,
pause = NULL,
completeWhenFilled = TRUE,
requiresMissings = FALSE)
}))
#' Robust ANOVA
#'
#' Robust Analysis of Variance
#'
#' @examples
#' data('goggles', package='WRS2')
#'
#' ranova(goggles,
#' dep = 'attractiveness',
#' factors = c('gender', 'alcohol'),
#' ph = TRUE)
#'
#' #
#' # ROBUST ANOVA
#' #
#' # Robust ANOVA
#' # ------------------------------------
#' # Q p
#' # ------------------------------------
#' # gender 1.67 0.209
#' # alcohol 48.28 0.001
#' # gender:alcohol 26.26 0.001
#' # ------------------------------------
#' # Note. Method of trimmed means,
#' # trim level 0.2
#' #
#' #
#' # POST HOC TESTS
#' #
#' # Post Hoc Tests - gender
#' # --------------------------------------------------------
#' # psi-hat p Lower Upper
#' # --------------------------------------------------------
#' # Female Male 10.0 0.209 -6.00 26.0
#' # --------------------------------------------------------
#' #
#' #
#' # Post Hoc Tests - alcohol
#' # -------------------------------------------------------------
#' # psi-hat p Lower Upper
#' # -------------------------------------------------------------
#' # None 2 Pints -3.33 0.611 -20.5 13.8
#' # None 4 Pints 35.83 < .001 19.3 52.3
#' # 2 Pints 4 Pints 39.17 < .001 22.5 55.9
#' # -------------------------------------------------------------
#' #
#'
#' @param data the data as a data frame
#' @param dep a string naming the dependent variable from \code{data}; the
#' variable must be numeric
#' @param factors a vector of strings naming the fixed factors from
#' \code{data}
#' @param method \code{'median'}, \code{'trim'} (default) or \code{'boot'};
#' the method to use, median, trimmed means, or bootstrapped
#' @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 est \code{'onestep'}, \code{'mom'} (default) or \code{'median'}, the
#' M-estimator to use; One-step, Modified one-step or Median respectively
#' @param nboot a number (default: 599) specifying the number of bootstrap
#' samples to use when using the bootstrap method
#' @param dist \code{'maha'} or \code{'proj'} (default), whether to use
#' Mahalanobis or Projection distances respectively
#' @param ph \code{TRUE} or \code{FALSE} (default), provide post hoc tests
#' @return A results object containing:
#' \tabular{llllll}{
#' \code{results$main} \tab \tab \tab \tab \tab the table of ANOVA results \cr
#' \code{results$phs} \tab \tab \tab \tab \tab the table of posthoc tests \cr
#' }
#'
#' Tables can be converted to data frames with \code{asDF} or \code{\link{as.data.frame}}. For example:
#'
#' \code{results$main$asDF}
#'
#' \code{as.data.frame(results$main)}
#'
#' @export
ranova <- function(
data,
dep,
factors = NULL,
method = "trim",
tr = 0.2,
est = "mom",
nboot = 599,
dist = "proj",
ph = FALSE) {
if ( ! requireNamespace("jmvcore", quietly=TRUE))
stop("ranova requires jmvcore to be installed (restart may be required)")
if ( ! missing(dep)) dep <- jmvcore::resolveQuo(jmvcore::enquo(dep))
if ( ! missing(factors)) factors <- jmvcore::resolveQuo(jmvcore::enquo(factors))
if (missing(data))
data <- jmvcore::marshalData(
parent.frame(),
`if`( ! missing(dep), dep, NULL),
`if`( ! missing(factors), factors, NULL))
for (v in factors) if (v %in% names(data)) data[[v]] <- as.factor(data[[v]])
options <- ranovaOptions$new(
dep = dep,
factors = factors,
method = method,
tr = tr,
est = est,
nboot = nboot,
dist = dist,
ph = ph)
analysis <- ranovaClass$new(
options = options,
data = data)
analysis$run()
analysis$results
}
jamovi/walrus documentation built on July 21, 2023, 7:31 p.m.
R Package Documentation
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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 ranova
Documented in ranova
# This file is automatically generated, you probably don't want to edit this
ranovaOptions <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"ranovaOptions",
inherit = jmvcore::Options,
public = list(
initialize = function(
dep = NULL,
factors = NULL,
method = "trim",
tr = 0.2,
est = "mom",
nboot = 599,
dist = "proj",
ph = FALSE, ...) {
super$initialize(
package="walrus",
name="ranova",
requiresData=TRUE,
...)
private$..dep <- jmvcore::OptionVariable$new(
"dep",
dep,
suggested=list(
"continuous"),
permitted=list(
"numeric"))
private$..factors <- jmvcore::OptionVariables$new(
"factors",
factors,
suggested=list(
"nominal",
"ordinal"),
permitted=list(
"factor"),
default=NULL)
private$..method <- jmvcore::OptionList$new(
"method",
method,
options=list(
"median",
"trim",
"boot"),
default="trim")
private$..tr <- jmvcore::OptionNumber$new(
"tr",
tr,
min=0,
max=0.5,
default=0.2)
private$..est <- jmvcore::OptionList$new(
"est",
est,
options=list(
"onestep",
"mom",
"median"),
default="mom")
private$..nboot <- jmvcore::OptionInteger$new(
"nboot",
nboot,
min=0,
default=599)
private$..dist <- jmvcore::OptionList$new(
"dist",
dist,
options=list(
"maha",
"proj"),
default="proj")
private$..ph <- jmvcore::OptionBool$new(
"ph",
ph,
default=FALSE)
self$.addOption(private$..dep)
self$.addOption(private$..factors)
self$.addOption(private$..method)
self$.addOption(private$..tr)
self$.addOption(private$..est)
self$.addOption(private$..nboot)
self$.addOption(private$..dist)
self$.addOption(private$..ph)
}),
active = list(
dep = function() private$..dep$value,
factors = function() private$..factors$value,
method = function() private$..method$value,
tr = function() private$..tr$value,
est = function() private$..est$value,
nboot = function() private$..nboot$value,
dist = function() private$..dist$value,
ph = function() private$..ph$value),
private = list(
..dep = NA,
..factors = NA,
..method = NA,
..tr = NA,
..est = NA,
..nboot = NA,
..dist = NA,
..ph = NA)
)
ranovaResults <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"ranovaResults",
inherit = jmvcore::Group,
active = list(
main = function() private$.items[["main"]],
phs = function() private$.items[["phs"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="",
title="Robust ANOVA")
self$add(jmvcore::Table$new(
options=options,
name="main",
title="Robust ANOVA",
clearWith=list(
"dep",
"factors",
"method",
"nboot",
"tr",
"est",
"dist"),
columns=list(
list(
`name`="name",
`title`="",
`type`="text"),
list(
`name`="s",
`title`="F",
`type`="number"),
list(
`name`="critval",
`title`="Critical value",
`type`="number",
`visible`=FALSE),
list(
`name`="df1",
`title`="df1",
`type`="number",
`visible`=FALSE),
list(
`name`="df2",
`title`="df2",
`type`="number",
`visible`=FALSE),
list(
`name`="p",
`title`="p",
`type`="number",
`format`="zto,pvalue"),
list(
`name`="expvar",
`title`="Variance explained",
`type`="number",
`visible`=FALSE),
list(
`name`="es",
`title`="ES",
`type`="number",
`visible`=FALSE),
list(
`name`="escil",
`title`="Lower",
`superTitle`="Bootstrap CI",
`type`="number",
`visible`=FALSE),
list(
`name`="esciu",
`title`="Upper",
`superTitle`="Bootstrap CI",
`type`="number",
`visible`=FALSE))))
self$add(jmvcore::Array$new(
options=options,
name="phs",
title="Post Hoc Tests",
items=7,
template=jmvcore::Table$new(
options=options,
name="ph",
title="",
visible=FALSE,
clearWith=list(
"dep",
"factors",
"method",
"nboot",
"tr",
"est",
"dist"),
columns=list(
list(
`name`="v1",
`title`="",
`type`="text",
`combineBelow`=TRUE),
list(
`name`="v2",
`title`="",
`type`="text"),
list(
`name`="psi",
`title`="psi-hat",
`type`="number"),
list(
`name`="p",
`title`="p",
`type`="number",
`format`="zto,pvalue"),
list(
`name`="adjp",
`title`="adj.p",
`type`="number",
`format`="zto,pvalue",
`visible`=FALSE),
list(
`name`="cil",
`title`="Lower",
`superTitle`="95% Confidence interval",
`type`="number"),
list(
`name`="ciu",
`title`="Upper",
`superTitle`="95% Confidence interval",
`type`="number")))))}))
ranovaBase <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"ranovaBase",
inherit = jmvcore::Analysis,
public = list(
initialize = function(options, data=NULL, datasetId="", analysisId="", revision=0) {
super$initialize(
package = "walrus",
name = "ranova",
version = c(1,0,0),
options = options,
results = ranovaResults$new(options=options),
data = data,
datasetId = datasetId,
analysisId = analysisId,
revision = revision,
pause = NULL,
completeWhenFilled = TRUE,
requiresMissings = FALSE)
}))
#' Robust ANOVA
#'
#' Robust Analysis of Variance
#'
#' @examples
#' data('goggles', package='WRS2')
#'
#' ranova(goggles,
#' dep = 'attractiveness',
#' factors = c('gender', 'alcohol'),
#' ph = TRUE)
#'
#' #
#' # ROBUST ANOVA
#' #
#' # Robust ANOVA
#' # ------------------------------------
#' # Q p
#' # ------------------------------------
#' # gender 1.67 0.209
#' # alcohol 48.28 0.001
#' # gender:alcohol 26.26 0.001
#' # ------------------------------------
#' # Note. Method of trimmed means,
#' # trim level 0.2
#' #
#' #
#' # POST HOC TESTS
#' #
#' # Post Hoc Tests - gender
#' # --------------------------------------------------------
#' # psi-hat p Lower Upper
#' # --------------------------------------------------------
#' # Female Male 10.0 0.209 -6.00 26.0
#' # --------------------------------------------------------
#' #
#' #
#' # Post Hoc Tests - alcohol
#' # -------------------------------------------------------------
#' # psi-hat p Lower Upper
#' # -------------------------------------------------------------
#' # None 2 Pints -3.33 0.611 -20.5 13.8
#' # None 4 Pints 35.83 < .001 19.3 52.3
#' # 2 Pints 4 Pints 39.17 < .001 22.5 55.9
#' # -------------------------------------------------------------
#' #
#'
#' @param data the data as a data frame
#' @param dep a string naming the dependent variable from \code{data}; the
#' variable must be numeric
#' @param factors a vector of strings naming the fixed factors from
#' \code{data}
#' @param method \code{'median'}, \code{'trim'} (default) or \code{'boot'};
#' the method to use, median, trimmed means, or bootstrapped
#' @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 est \code{'onestep'}, \code{'mom'} (default) or \code{'median'}, the
#' M-estimator to use; One-step, Modified one-step or Median respectively
#' @param nboot a number (default: 599) specifying the number of bootstrap
#' samples to use when using the bootstrap method
#' @param dist \code{'maha'} or \code{'proj'} (default), whether to use
#' Mahalanobis or Projection distances respectively
#' @param ph \code{TRUE} or \code{FALSE} (default), provide post hoc tests
#' @return A results object containing:
#' \tabular{llllll}{
#' \code{results$main} \tab \tab \tab \tab \tab the table of ANOVA results \cr
#' \code{results$phs} \tab \tab \tab \tab \tab the table of posthoc tests \cr
#' }
#'
#' Tables can be converted to data frames with \code{asDF} or \code{\link{as.data.frame}}. For example:
#'
#' \code{results$main$asDF}
#'
#' \code{as.data.frame(results$main)}
#'
#' @export
ranova <- function(
data,
dep,
factors = NULL,
method = "trim",
tr = 0.2,
est = "mom",
nboot = 599,
dist = "proj",
ph = FALSE) {
if ( ! requireNamespace("jmvcore", quietly=TRUE))
stop("ranova requires jmvcore to be installed (restart may be required)")
if ( ! missing(dep)) dep <- jmvcore::resolveQuo(jmvcore::enquo(dep))
if ( ! missing(factors)) factors <- jmvcore::resolveQuo(jmvcore::enquo(factors))
if (missing(data))
data <- jmvcore::marshalData(
parent.frame(),
`if`( ! missing(dep), dep, NULL),
`if`( ! missing(factors), factors, NULL))
for (v in factors) if (v %in% names(data)) data[[v]] <- as.factor(data[[v]])
options <- ranovaOptions$new(
dep = dep,
factors = factors,
method = method,
tr = tr,
est = est,
nboot = nboot,
dist = dist,
ph = ph)
analysis <- ranovaClass$new(
options = options,
data = data)
analysis$run()
analysis$results
}
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