R/jmvpower.h.R
In Lakens/ANOVApower: Simulation-Based Power Analysis for ANOVA Designs
Defines functions
jmvpower
Documented in
jmvpower
# This file is automatically generated, you probably don't want to edit this
jmvpowerOptions <- if (requireNamespace('jmvcore')) R6::R6Class(
"jmvpowerOptions",
inherit = jmvcore::Options,
public = list(
initialize = function(
design = "2b*2w",
labelnames = "AGE,old,young,SPEED,fast,slow",
n = 80,
sd = 1.03,
r = 0.87,
mu = "1.03, 1.21, 0.98, 1.01",
plot = TRUE,
simulate = FALSE,
alpha_level = 0.05,
nsims = 100,
p_adjust = "holm", ...) {
super$initialize(
package='ANOVApower',
name='jmvpower',
requiresData=FALSE,
...)
private$..design <- jmvcore::OptionString$new(
"design",
design,
default="2b*2w")
private$..labelnames <- jmvcore::OptionString$new(
"labelnames",
labelnames,
default="AGE,old,young,SPEED,fast,slow")
private$..n <- jmvcore::OptionInteger$new(
"n",
n,
default=80,
min=3)
private$..sd <- jmvcore::OptionNumber$new(
"sd",
sd,
default=1.03,
min=0.0001)
private$..r <- jmvcore::OptionNumber$new(
"r",
r,
default=0.87)
private$..mu <- jmvcore::OptionString$new(
"mu",
mu,
default="1.03, 1.21, 0.98, 1.01")
private$..plot <- jmvcore::OptionBool$new(
"plot",
plot,
default=TRUE)
private$..simulate <- jmvcore::OptionBool$new(
"simulate",
simulate,
default=FALSE,
hidden=TRUE)
private$..alpha_level <- jmvcore::OptionNumber$new(
"alpha_level",
alpha_level,
min=0,
max=1,
default=0.05)
private$..nsims <- jmvcore::OptionInteger$new(
"nsims",
nsims,
min=100,
max=10000,
default=100)
private$..p_adjust <- jmvcore::OptionList$new(
"p_adjust",
p_adjust,
options=list(
"none",
"holm",
"bonferroni",
"fdr"),
default="holm")
self$.addOption(private$..design)
self$.addOption(private$..labelnames)
self$.addOption(private$..n)
self$.addOption(private$..sd)
self$.addOption(private$..r)
self$.addOption(private$..mu)
self$.addOption(private$..plot)
self$.addOption(private$..simulate)
self$.addOption(private$..alpha_level)
self$.addOption(private$..nsims)
self$.addOption(private$..p_adjust)
}),
active = list(
design = function() private$..design$value,
labelnames = function() private$..labelnames$value,
n = function() private$..n$value,
sd = function() private$..sd$value,
r = function() private$..r$value,
mu = function() private$..mu$value,
plot = function() private$..plot$value,
simulate = function() private$..simulate$value,
alpha_level = function() private$..alpha_level$value,
nsims = function() private$..nsims$value,
p_adjust = function() private$..p_adjust$value),
private = list(
..design = NA,
..labelnames = NA,
..n = NA,
..sd = NA,
..r = NA,
..mu = NA,
..plot = NA,
..simulate = NA,
..alpha_level = NA,
..nsims = NA,
..p_adjust = NA)
)
jmvpowerResults <- if (requireNamespace('jmvcore')) R6::R6Class(
inherit = jmvcore::Group,
active = list(
design = function() private$.items[["design"]],
sims = function() private$.items[["sims"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="",
title="ANOVA power")
self$add(R6::R6Class(
inherit = jmvcore::Group,
active = list(
summary = function() private$.items[["summary"]],
matrix = function() private$.items[["matrix"]],
plot = function() private$.items[["plot"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="design",
title="Design")
self$add(jmvcore::Table$new(
options=options,
name="summary",
title="Design",
rows=4,
columns=list(
list(
`name`="name",
`title`="",
`type`="text"),
list(
`name`="value",
`title`="",
`type`="text")),
clearWith=list(
"design",
"labelnames",
"n",
"sd",
"r",
"mu")))
self$add(jmvcore::Table$new(
options=options,
name="matrix",
title="Correlation matrix",
columns=list(),
clearWith=list(
"design",
"labelnames",
"n",
"sd",
"r",
"mu")))
self$add(jmvcore::Image$new(
options=options,
name="plot",
title="Means plot",
visible="(plot)",
renderFun=".plot",
clearWith=list(
"design",
"labelnames",
"n",
"sd",
"r",
"mu")))}))$new(options=options))
self$add(R6::R6Class(
inherit = jmvcore::Group,
active = list(
results = function() private$.items[["results"]],
multi = function() private$.items[["multi"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="sims",
title="Simulation")
self$add(jmvcore::Table$new(
options=options,
name="results",
title="Results",
visible="(simulate)",
columns=list(
list(
`name`="name",
`title`="",
`type`="text"),
list(
`name`="power",
`title`="Power"),
list(
`name`="es",
`title`="Effect-size")),
clearWith=list(
"design",
"labelnames",
"n",
"sd",
"r",
"mu",
"nsims",
"alpha_level",
"p_adjust")))
self$add(jmvcore::Table$new(
options=options,
name="multi",
title="Multiple comparisons",
visible="(simulate)",
columns=list(
list(
`name`="name",
`title`="",
`type`="text"),
list(
`name`="power",
`title`="Power"),
list(
`name`="es",
`title`="Effect-size")),
clearWith=list(
"design",
"labelnames",
"n",
"sd",
"r",
"mu",
"nsims",
"alpha_level",
"p_adjust")))}))$new(options=options))}))
jmvpowerBase <- if (requireNamespace('jmvcore')) R6::R6Class(
"jmvpowerBase",
inherit = jmvcore::Analysis,
public = list(
initialize = function(options, data=NULL, datasetId="", analysisId="", revision=0) {
super$initialize(
package = 'ANOVApower',
name = 'jmvpower',
version = c(1,0,0),
options = options,
results = jmvpowerResults$new(options=options),
data = data,
datasetId = datasetId,
analysisId = analysisId,
revision = revision,
pause = NULL,
completeWhenFilled = FALSE)
}))
#' ANOVA power
#'
#'
#' @param design a string describing the design
#' @param labelnames a comma separated string describing the factor and level
#' labels
#' @param n an integer specifying the sample size in each condition
#' @param sd a number specifying the group standard deviations
#' @param r a number specifying the correlation between dependent variables
#' @param mu a comma separated string specifying the group means
#' @param plot \code{TRUE} (default) or \code{FALSE} specifying whether to
#' provide a means plot
#' @param simulate \code{TRUE} or \code{FALSE} (default); perform the
#' simulation
#' @param alpha_level a number specifying the alpha level
#' @param nsims an integer specifying the number of simulations to perform
#' @param p_adjust the p-adjustment method to use
#' @return A results object containing:
#' \tabular{llllll}{
#' \code{results$design$summary} \tab \tab \tab \tab \tab a table \cr
#' \code{results$design$matrix} \tab \tab \tab \tab \tab a table \cr
#' \code{results$design$plot} \tab \tab \tab \tab \tab an image \cr
#' \code{results$sims$results} \tab \tab \tab \tab \tab a table \cr
#' \code{results$sims$multi} \tab \tab \tab \tab \tab a table \cr
#' }
#'
#' @importFrom utils data
#' @export
jmvpower <- function(
design = "2b*2w",
labelnames = "AGE,old,young,SPEED,fast,slow",
n = 80,
sd = 1.03,
r = 0.87,
mu = "1.03, 1.21, 0.98, 1.01",
plot = TRUE,
simulate = FALSE,
alpha_level = 0.05,
nsims = 100,
p_adjust = "holm") {
if ( ! requireNamespace('jmvcore'))
stop('jmvpower requires jmvcore to be installed (restart may be required)')
options <- jmvpowerOptions$new(
design = design,
labelnames = labelnames,
n = n,
sd = sd,
r = r,
mu = mu,
plot = plot,
simulate = simulate,
alpha_level = alpha_level,
nsims = nsims,
p_adjust = p_adjust)
results <- jmvpowerResults$new(
options = options)
analysis <- jmvpowerClass$new(
options = options,
data = data)
analysis$run()
analysis$results
}
Lakens/ANOVApower documentation built on Jan. 9, 2020, 5:32 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Defines functions jmvpower
Documented in jmvpower
# This file is automatically generated, you probably don't want to edit this
jmvpowerOptions <- if (requireNamespace('jmvcore')) R6::R6Class(
"jmvpowerOptions",
inherit = jmvcore::Options,
public = list(
initialize = function(
design = "2b*2w",
labelnames = "AGE,old,young,SPEED,fast,slow",
n = 80,
sd = 1.03,
r = 0.87,
mu = "1.03, 1.21, 0.98, 1.01",
plot = TRUE,
simulate = FALSE,
alpha_level = 0.05,
nsims = 100,
p_adjust = "holm", ...) {
super$initialize(
package='ANOVApower',
name='jmvpower',
requiresData=FALSE,
...)
private$..design <- jmvcore::OptionString$new(
"design",
design,
default="2b*2w")
private$..labelnames <- jmvcore::OptionString$new(
"labelnames",
labelnames,
default="AGE,old,young,SPEED,fast,slow")
private$..n <- jmvcore::OptionInteger$new(
"n",
n,
default=80,
min=3)
private$..sd <- jmvcore::OptionNumber$new(
"sd",
sd,
default=1.03,
min=0.0001)
private$..r <- jmvcore::OptionNumber$new(
"r",
r,
default=0.87)
private$..mu <- jmvcore::OptionString$new(
"mu",
mu,
default="1.03, 1.21, 0.98, 1.01")
private$..plot <- jmvcore::OptionBool$new(
"plot",
plot,
default=TRUE)
private$..simulate <- jmvcore::OptionBool$new(
"simulate",
simulate,
default=FALSE,
hidden=TRUE)
private$..alpha_level <- jmvcore::OptionNumber$new(
"alpha_level",
alpha_level,
min=0,
max=1,
default=0.05)
private$..nsims <- jmvcore::OptionInteger$new(
"nsims",
nsims,
min=100,
max=10000,
default=100)
private$..p_adjust <- jmvcore::OptionList$new(
"p_adjust",
p_adjust,
options=list(
"none",
"holm",
"bonferroni",
"fdr"),
default="holm")
self$.addOption(private$..design)
self$.addOption(private$..labelnames)
self$.addOption(private$..n)
self$.addOption(private$..sd)
self$.addOption(private$..r)
self$.addOption(private$..mu)
self$.addOption(private$..plot)
self$.addOption(private$..simulate)
self$.addOption(private$..alpha_level)
self$.addOption(private$..nsims)
self$.addOption(private$..p_adjust)
}),
active = list(
design = function() private$..design$value,
labelnames = function() private$..labelnames$value,
n = function() private$..n$value,
sd = function() private$..sd$value,
r = function() private$..r$value,
mu = function() private$..mu$value,
plot = function() private$..plot$value,
simulate = function() private$..simulate$value,
alpha_level = function() private$..alpha_level$value,
nsims = function() private$..nsims$value,
p_adjust = function() private$..p_adjust$value),
private = list(
..design = NA,
..labelnames = NA,
..n = NA,
..sd = NA,
..r = NA,
..mu = NA,
..plot = NA,
..simulate = NA,
..alpha_level = NA,
..nsims = NA,
..p_adjust = NA)
)
jmvpowerResults <- if (requireNamespace('jmvcore')) R6::R6Class(
inherit = jmvcore::Group,
active = list(
design = function() private$.items[["design"]],
sims = function() private$.items[["sims"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="",
title="ANOVA power")
self$add(R6::R6Class(
inherit = jmvcore::Group,
active = list(
summary = function() private$.items[["summary"]],
matrix = function() private$.items[["matrix"]],
plot = function() private$.items[["plot"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="design",
title="Design")
self$add(jmvcore::Table$new(
options=options,
name="summary",
title="Design",
rows=4,
columns=list(
list(
`name`="name",
`title`="",
`type`="text"),
list(
`name`="value",
`title`="",
`type`="text")),
clearWith=list(
"design",
"labelnames",
"n",
"sd",
"r",
"mu")))
self$add(jmvcore::Table$new(
options=options,
name="matrix",
title="Correlation matrix",
columns=list(),
clearWith=list(
"design",
"labelnames",
"n",
"sd",
"r",
"mu")))
self$add(jmvcore::Image$new(
options=options,
name="plot",
title="Means plot",
visible="(plot)",
renderFun=".plot",
clearWith=list(
"design",
"labelnames",
"n",
"sd",
"r",
"mu")))}))$new(options=options))
self$add(R6::R6Class(
inherit = jmvcore::Group,
active = list(
results = function() private$.items[["results"]],
multi = function() private$.items[["multi"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="sims",
title="Simulation")
self$add(jmvcore::Table$new(
options=options,
name="results",
title="Results",
visible="(simulate)",
columns=list(
list(
`name`="name",
`title`="",
`type`="text"),
list(
`name`="power",
`title`="Power"),
list(
`name`="es",
`title`="Effect-size")),
clearWith=list(
"design",
"labelnames",
"n",
"sd",
"r",
"mu",
"nsims",
"alpha_level",
"p_adjust")))
self$add(jmvcore::Table$new(
options=options,
name="multi",
title="Multiple comparisons",
visible="(simulate)",
columns=list(
list(
`name`="name",
`title`="",
`type`="text"),
list(
`name`="power",
`title`="Power"),
list(
`name`="es",
`title`="Effect-size")),
clearWith=list(
"design",
"labelnames",
"n",
"sd",
"r",
"mu",
"nsims",
"alpha_level",
"p_adjust")))}))$new(options=options))}))
jmvpowerBase <- if (requireNamespace('jmvcore')) R6::R6Class(
"jmvpowerBase",
inherit = jmvcore::Analysis,
public = list(
initialize = function(options, data=NULL, datasetId="", analysisId="", revision=0) {
super$initialize(
package = 'ANOVApower',
name = 'jmvpower',
version = c(1,0,0),
options = options,
results = jmvpowerResults$new(options=options),
data = data,
datasetId = datasetId,
analysisId = analysisId,
revision = revision,
pause = NULL,
completeWhenFilled = FALSE)
}))
#' ANOVA power
#'
#'
#' @param design a string describing the design
#' @param labelnames a comma separated string describing the factor and level
#' labels
#' @param n an integer specifying the sample size in each condition
#' @param sd a number specifying the group standard deviations
#' @param r a number specifying the correlation between dependent variables
#' @param mu a comma separated string specifying the group means
#' @param plot \code{TRUE} (default) or \code{FALSE} specifying whether to
#' provide a means plot
#' @param simulate \code{TRUE} or \code{FALSE} (default); perform the
#' simulation
#' @param alpha_level a number specifying the alpha level
#' @param nsims an integer specifying the number of simulations to perform
#' @param p_adjust the p-adjustment method to use
#' @return A results object containing:
#' \tabular{llllll}{
#' \code{results$design$summary} \tab \tab \tab \tab \tab a table \cr
#' \code{results$design$matrix} \tab \tab \tab \tab \tab a table \cr
#' \code{results$design$plot} \tab \tab \tab \tab \tab an image \cr
#' \code{results$sims$results} \tab \tab \tab \tab \tab a table \cr
#' \code{results$sims$multi} \tab \tab \tab \tab \tab a table \cr
#' }
#'
#' @importFrom utils data
#' @export
jmvpower <- function(
design = "2b*2w",
labelnames = "AGE,old,young,SPEED,fast,slow",
n = 80,
sd = 1.03,
r = 0.87,
mu = "1.03, 1.21, 0.98, 1.01",
plot = TRUE,
simulate = FALSE,
alpha_level = 0.05,
nsims = 100,
p_adjust = "holm") {
if ( ! requireNamespace('jmvcore'))
stop('jmvpower requires jmvcore to be installed (restart may be required)')
options <- jmvpowerOptions$new(
design = design,
labelnames = labelnames,
n = n,
sd = sd,
r = r,
mu = mu,
plot = plot,
simulate = simulate,
alpha_level = alpha_level,
nsims = nsims,
p_adjust = p_adjust)
results <- jmvpowerResults$new(
options = options)
analysis <- jmvpowerClass$new(
options = options,
data = data)
analysis$run()
analysis$results
}
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.