# This file is automatically generated, you probably don't want to edit this
metaMeanDiffOptions <- if (requireNamespace('jmvcore')) R6::R6Class(
"metaMeanDiffOptions",
inherit = jmvcore::Options,
public = list(
initialize = function(
n1i = NULL,
m1i = NULL,
sd1i = NULL,
n2i = NULL,
m2i = NULL,
sd2i = NULL,
slab = NULL,
moderatorcor = NULL,
methodmetacor = "REML",
cormeasure = "SMD",
moderatorType = "NON",
testType = FALSE,
level = 95,
showModelFit = FALSE,
addcred = FALSE,
addfit = TRUE,
showweights = FALSE,
steps = 5,
xAxisTitle = NULL,
forestPlotSize = "SMALL",
funnelPlotSize = "SMALL",
pchForest = "15",
forestOrder = "fit",
fsntype = "Rosenthal",
tesAlternative = "two.sided",
tesAlpha = 0.5,
tesH0 = 0,
showTes = FALSE,
puniformSide = "right",
selModelType = "none",
yaxis = "sei",
yaxisInv = FALSE,
enhanceFunnel = FALSE,
lowerTOST = -0.5,
upperTOST = 0.5,
alphaTOST = 0.05,
showTOST = FALSE,
showInfPlot = FALSE,
showLL = FALSE,
showPuniform = FALSE,
showSelmodel = FALSE,
showPcurve = FALSE, ...) {
super$initialize(
package='MAJOR',
name='metaMeanDiff',
requiresData=TRUE,
...)
private$..n1i <- jmvcore::OptionVariable$new(
"n1i",
n1i,
suggested=list(
"continuous"),
permitted=list(
"numeric"))
private$..m1i <- jmvcore::OptionVariable$new(
"m1i",
m1i,
suggested=list(
"continuous"),
permitted=list(
"numeric"))
private$..sd1i <- jmvcore::OptionVariable$new(
"sd1i",
sd1i,
suggested=list(
"continuous"),
permitted=list(
"numeric"))
private$..n2i <- jmvcore::OptionVariable$new(
"n2i",
n2i,
suggested=list(
"continuous"),
permitted=list(
"numeric"))
private$..m2i <- jmvcore::OptionVariable$new(
"m2i",
m2i,
suggested=list(
"continuous"),
permitted=list(
"numeric"))
private$..sd2i <- jmvcore::OptionVariable$new(
"sd2i",
sd2i,
suggested=list(
"continuous"),
permitted=list(
"numeric"))
private$..slab <- jmvcore::OptionVariable$new(
"slab",
slab,
suggested=list(
"nominal"))
private$..moderatorcor <- jmvcore::OptionVariable$new(
"moderatorcor",
moderatorcor,
suggested=list(
"continuous"),
permitted=list(
"numeric"))
private$..methodmetacor <- jmvcore::OptionList$new(
"methodmetacor",
methodmetacor,
options=list(
"DL",
"HE",
"HS",
"SJ",
"ML",
"REML",
"EB",
"PM",
"FE"),
default="REML")
private$..cormeasure <- jmvcore::OptionList$new(
"cormeasure",
cormeasure,
options=list(
"MD",
"SMD",
"SMDH",
"ROM"),
default="SMD")
private$..moderatorType <- jmvcore::OptionList$new(
"moderatorType",
moderatorType,
options=list(
"NON",
"CAT",
"CON"),
default="NON")
private$..testType <- jmvcore::OptionBool$new(
"testType",
testType,
default=FALSE)
private$..level <- jmvcore::OptionNumber$new(
"level",
level,
min=50,
max=99.9,
default=95)
private$..showModelFit <- jmvcore::OptionBool$new(
"showModelFit",
showModelFit,
default=FALSE)
private$..addcred <- jmvcore::OptionBool$new(
"addcred",
addcred,
default=FALSE)
private$..addfit <- jmvcore::OptionBool$new(
"addfit",
addfit,
default=TRUE)
private$..showweights <- jmvcore::OptionBool$new(
"showweights",
showweights,
default=FALSE)
private$..steps <- jmvcore::OptionNumber$new(
"steps",
steps,
min=1,
max=999,
default=5)
private$..xAxisTitle <- jmvcore::OptionString$new(
"xAxisTitle",
xAxisTitle)
private$..forestPlotSize <- jmvcore::OptionList$new(
"forestPlotSize",
forestPlotSize,
options=list(
"SMALL",
"MEDIUM",
"LARGE",
"SMALLWIDE",
"MEDIUMWIDE",
"LARGEWIDE"),
default="SMALL")
private$..funnelPlotSize <- jmvcore::OptionList$new(
"funnelPlotSize",
funnelPlotSize,
options=list(
"SMALL",
"MEDIUM",
"LARGE"),
default="SMALL")
private$..pchForest <- jmvcore::OptionList$new(
"pchForest",
pchForest,
options=list(
"16",
"18",
"15",
"17",
"1",
"5",
"0",
"2",
"8"),
default="15")
private$..forestOrder <- jmvcore::OptionList$new(
"forestOrder",
forestOrder,
options=list(
"obs",
"fit",
"prec",
"resid",
"abs.resid"),
default="fit")
private$..fsntype <- jmvcore::OptionList$new(
"fsntype",
fsntype,
options=list(
"Rosenthal",
"Orwin",
"Rosenberg"),
default="Rosenthal")
private$..tesAlternative <- jmvcore::OptionList$new(
"tesAlternative",
tesAlternative,
options=list(
"two.sided",
"less",
"greater"),
default="two.sided")
private$..tesAlpha <- jmvcore::OptionNumber$new(
"tesAlpha",
tesAlpha,
min=0.000001,
max=1,
default=0.5)
private$..tesH0 <- jmvcore::OptionNumber$new(
"tesH0",
tesH0,
min=-9999,
max=9999,
default=0)
private$..showTes <- jmvcore::OptionBool$new(
"showTes",
showTes,
default=FALSE)
private$..puniformSide <- jmvcore::OptionList$new(
"puniformSide",
puniformSide,
options=list(
"right",
"left"),
default="right")
private$..selModelType <- jmvcore::OptionList$new(
"selModelType",
selModelType,
options=list(
"none",
"beta",
"halfnorm",
"negexp",
"logistic",
"power",
"stepfun"),
default="none")
private$..yaxis <- jmvcore::OptionList$new(
"yaxis",
yaxis,
options=list(
"sei",
"vi",
"ni",
"sqrtni",
"lni"),
default="sei")
private$..yaxisInv <- jmvcore::OptionBool$new(
"yaxisInv",
yaxisInv,
default=FALSE)
private$..enhanceFunnel <- jmvcore::OptionBool$new(
"enhanceFunnel",
enhanceFunnel,
default=FALSE)
private$..lowerTOST <- jmvcore::OptionNumber$new(
"lowerTOST",
lowerTOST,
min=-100,
max=100,
default=-0.5)
private$..upperTOST <- jmvcore::OptionNumber$new(
"upperTOST",
upperTOST,
min=-100,
max=100,
default=0.5)
private$..alphaTOST <- jmvcore::OptionNumber$new(
"alphaTOST",
alphaTOST,
min=0.000001,
max=1,
default=0.05)
private$..showTOST <- jmvcore::OptionBool$new(
"showTOST",
showTOST,
default=FALSE)
private$..showInfPlot <- jmvcore::OptionBool$new(
"showInfPlot",
showInfPlot,
default=FALSE)
private$..showLL <- jmvcore::OptionBool$new(
"showLL",
showLL,
default=FALSE)
private$..showPuniform <- jmvcore::OptionBool$new(
"showPuniform",
showPuniform,
default=FALSE)
private$..showSelmodel <- jmvcore::OptionBool$new(
"showSelmodel",
showSelmodel,
default=FALSE)
private$..showPcurve <- jmvcore::OptionBool$new(
"showPcurve",
showPcurve,
default=FALSE)
self$.addOption(private$..n1i)
self$.addOption(private$..m1i)
self$.addOption(private$..sd1i)
self$.addOption(private$..n2i)
self$.addOption(private$..m2i)
self$.addOption(private$..sd2i)
self$.addOption(private$..slab)
self$.addOption(private$..moderatorcor)
self$.addOption(private$..methodmetacor)
self$.addOption(private$..cormeasure)
self$.addOption(private$..moderatorType)
self$.addOption(private$..testType)
self$.addOption(private$..level)
self$.addOption(private$..showModelFit)
self$.addOption(private$..addcred)
self$.addOption(private$..addfit)
self$.addOption(private$..showweights)
self$.addOption(private$..steps)
self$.addOption(private$..xAxisTitle)
self$.addOption(private$..forestPlotSize)
self$.addOption(private$..funnelPlotSize)
self$.addOption(private$..pchForest)
self$.addOption(private$..forestOrder)
self$.addOption(private$..fsntype)
self$.addOption(private$..tesAlternative)
self$.addOption(private$..tesAlpha)
self$.addOption(private$..tesH0)
self$.addOption(private$..showTes)
self$.addOption(private$..puniformSide)
self$.addOption(private$..selModelType)
self$.addOption(private$..yaxis)
self$.addOption(private$..yaxisInv)
self$.addOption(private$..enhanceFunnel)
self$.addOption(private$..lowerTOST)
self$.addOption(private$..upperTOST)
self$.addOption(private$..alphaTOST)
self$.addOption(private$..showTOST)
self$.addOption(private$..showInfPlot)
self$.addOption(private$..showLL)
self$.addOption(private$..showPuniform)
self$.addOption(private$..showSelmodel)
self$.addOption(private$..showPcurve)
}),
active = list(
n1i = function() private$..n1i$value,
m1i = function() private$..m1i$value,
sd1i = function() private$..sd1i$value,
n2i = function() private$..n2i$value,
m2i = function() private$..m2i$value,
sd2i = function() private$..sd2i$value,
slab = function() private$..slab$value,
moderatorcor = function() private$..moderatorcor$value,
methodmetacor = function() private$..methodmetacor$value,
cormeasure = function() private$..cormeasure$value,
moderatorType = function() private$..moderatorType$value,
testType = function() private$..testType$value,
level = function() private$..level$value,
showModelFit = function() private$..showModelFit$value,
addcred = function() private$..addcred$value,
addfit = function() private$..addfit$value,
showweights = function() private$..showweights$value,
steps = function() private$..steps$value,
xAxisTitle = function() private$..xAxisTitle$value,
forestPlotSize = function() private$..forestPlotSize$value,
funnelPlotSize = function() private$..funnelPlotSize$value,
pchForest = function() private$..pchForest$value,
forestOrder = function() private$..forestOrder$value,
fsntype = function() private$..fsntype$value,
tesAlternative = function() private$..tesAlternative$value,
tesAlpha = function() private$..tesAlpha$value,
tesH0 = function() private$..tesH0$value,
showTes = function() private$..showTes$value,
puniformSide = function() private$..puniformSide$value,
selModelType = function() private$..selModelType$value,
yaxis = function() private$..yaxis$value,
yaxisInv = function() private$..yaxisInv$value,
enhanceFunnel = function() private$..enhanceFunnel$value,
lowerTOST = function() private$..lowerTOST$value,
upperTOST = function() private$..upperTOST$value,
alphaTOST = function() private$..alphaTOST$value,
showTOST = function() private$..showTOST$value,
showInfPlot = function() private$..showInfPlot$value,
showLL = function() private$..showLL$value,
showPuniform = function() private$..showPuniform$value,
showSelmodel = function() private$..showSelmodel$value,
showPcurve = function() private$..showPcurve$value),
private = list(
..n1i = NA,
..m1i = NA,
..sd1i = NA,
..n2i = NA,
..m2i = NA,
..sd2i = NA,
..slab = NA,
..moderatorcor = NA,
..methodmetacor = NA,
..cormeasure = NA,
..moderatorType = NA,
..testType = NA,
..level = NA,
..showModelFit = NA,
..addcred = NA,
..addfit = NA,
..showweights = NA,
..steps = NA,
..xAxisTitle = NA,
..forestPlotSize = NA,
..funnelPlotSize = NA,
..pchForest = NA,
..forestOrder = NA,
..fsntype = NA,
..tesAlternative = NA,
..tesAlpha = NA,
..tesH0 = NA,
..showTes = NA,
..puniformSide = NA,
..selModelType = NA,
..yaxis = NA,
..yaxisInv = NA,
..enhanceFunnel = NA,
..lowerTOST = NA,
..upperTOST = NA,
..alphaTOST = NA,
..showTOST = NA,
..showInfPlot = NA,
..showLL = NA,
..showPuniform = NA,
..showSelmodel = NA,
..showPcurve = NA)
)
metaMeanDiffResults <- if (requireNamespace('jmvcore')) R6::R6Class(
inherit = jmvcore::Group,
active = list(
textRICH = function() private$.items[["textRICH"]],
tableTauSqaured = function() private$.items[["tableTauSqaured"]],
modelFitRICH = function() private$.items[["modelFitRICH"]],
summaryOutputText = function() private$.items[["summaryOutputText"]],
summaryOutputText2 = function() private$.items[["summaryOutputText2"]],
plot = function() private$.items[["plot"]],
plotMed = function() private$.items[["plotMed"]],
plotLarge = function() private$.items[["plotLarge"]],
plotSmallWide = function() private$.items[["plotSmallWide"]],
plotMedWide = function() private$.items[["plotMedWide"]],
plotLargeWide = function() private$.items[["plotLargeWide"]],
selModelOutput = function() private$.items[["selModelOutput"]],
fsnRICH = function() private$.items[["fsnRICH"]],
funplot = function() private$.items[["funplot"]],
funplotMed = function() private$.items[["funplotMed"]],
funplotLarge = function() private$.items[["funplotLarge"]],
resultsTES = function() private$.items[["resultsTES"]],
resultsTES2 = function() private$.items[["resultsTES2"]],
tesOutput3 = function() private$.items[["tesOutput3"]],
pCurvePlot = function() private$.items[["pCurvePlot"]],
puniformModelOutput = function() private$.items[["puniformModelOutput"]],
puniformModelOutput2 = function() private$.items[["puniformModelOutput2"]],
TOSToutput = function() private$.items[["TOSToutput"]],
TOSToutputtext = function() private$.items[["TOSToutputtext"]],
tostplot = function() private$.items[["tostplot"]],
likelihoodPlot = function() private$.items[["likelihoodPlot"]],
diagPlotAll = function() private$.items[["diagPlotAll"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="",
title="Meta-Analysis")
self$add(jmvcore::Table$new(
options=options,
name="textRICH",
refs=list(
"metafor"),
title="Random-Effects Model",
rows=2,
columns=list(
list(
`name`="Intercept",
`title`="",
`type`="text"),
list(
`name`="Estimate",
`type`="number"),
list(
`name`="se",
`type`="number"),
list(
`name`="Z",
`type`="number"),
list(
`name`="p",
`type`="number",
`format`="zto,pvalue"),
list(
`name`="CILow",
`title`="CI Lower Bound",
`type`="number",
`format`="zto"),
list(
`name`="CIHigh",
`title`="CI Upper Bound",
`type`="number",
`format`="zto"))))
self$add(jmvcore::Table$new(
options=options,
name="tableTauSqaured",
title="Heterogeneity Statistics",
rows=1,
columns=list(
list(
`name`="tauSQRT",
`title`="Tau",
`type`="number",
`format`="zto"),
list(
`name`="tauSqComb",
`title`="Tau\u00B2",
`type`="number",
`format`="zto"),
list(
`name`="ISqu",
`title`="I\u00B2",
`type`="text"),
list(
`name`="HSqu",
`title`="H\u00B2",
`type`="number",
`format`="zto"),
list(
`name`="RSqu",
`title`="R\u00B2",
`type`="text"),
list(
`name`="QallDF",
`title`="df",
`type`="integer",
`format`="zto"),
list(
`name`="Qall",
`title`="Q",
`type`="number",
`format`="zto"),
list(
`name`="QallPval",
`title`="p",
`type`="number",
`format`="zto,pvalue"))))
self$add(jmvcore::Table$new(
options=options,
name="modelFitRICH",
title="Model Fit Statistics and Information Criteria",
rows=2,
columns=list(
list(
`name`="label",
`title`="",
`type`="text"),
list(
`name`="loglikelihood",
`title`="log-likelihood",
`type`="number",
`format`="zto"),
list(
`name`="deviance",
`title`="Deviance",
`type`="number",
`format`="zto"),
list(
`name`="AIC",
`type`="number",
`format`="zto"),
list(
`name`="BIC",
`type`="number",
`format`="zto"),
list(
`name`="AICc",
`type`="number",
`format`="zto"))))
self$add(jmvcore::Html$new(
options=options,
name="summaryOutputText",
title="Model Summary"))
self$add(jmvcore::Html$new(
options=options,
name="summaryOutputText2",
title="Model Summary"))
self$add(jmvcore::Image$new(
options=options,
name="plot",
title="Forest Plot",
width=600,
height=450,
renderFun=".plot",
refs=list(
"metafor")))
self$add(jmvcore::Image$new(
options=options,
name="plotMed",
title="Forest Plot",
width=600,
height=625,
renderFun=".plot",
refs=list(
"metafor")))
self$add(jmvcore::Image$new(
options=options,
name="plotLarge",
title="Forest Plot",
width=600,
height=900,
renderFun=".plot",
refs=list(
"metafor")))
self$add(jmvcore::Image$new(
options=options,
name="plotSmallWide",
title="Forest Plot",
width=900,
height=450,
renderFun=".plot",
refs=list(
"metafor")))
self$add(jmvcore::Image$new(
options=options,
name="plotMedWide",
title="Forest Plot",
width=900,
height=625,
renderFun=".plot",
refs=list(
"metafor")))
self$add(jmvcore::Image$new(
options=options,
name="plotLargeWide",
title="Forest Plot",
width=900,
height=900,
renderFun=".plot",
refs=list(
"metafor")))
self$add(jmvcore::Table$new(
options=options,
name="selModelOutput",
title="Selection Model Results",
refs=list(
"metafor"),
rows=1,
columns=list(
list(
`name`="deltaEstimate",
`title`="Estimate",
`type`="number"),
list(
`name`="deltaSE",
`title`="SE",
`type`="number",
`format`="zto"),
list(
`name`="deltaPVAL",
`title`="p-value",
`type`="number",
`format`="pval"),
list(
`name`="deltaCILB",
`title`="CI Lower Bound",
`type`="number",
`format`="zto"),
list(
`name`="deltaCIUB",
`title`="CI Upper Bound",
`type`="number",
`format`="zto"))))
self$add(jmvcore::Table$new(
options=options,
name="fsnRICH",
title="",
rows=4,
columns=list(
list(
`name`="label",
`title`="Test Name",
`type`="text"),
list(
`name`="failSafeNumber",
`title`="value",
`type`="integer",
`format`="zto"),
list(
`name`="p",
`type`="number",
`format`="zto,pvalue"))))
self$add(jmvcore::Image$new(
options=options,
name="funplot",
title="Funnel Plot",
width=600,
height=450,
renderFun=".funplot",
refs=list(
"metafor")))
self$add(jmvcore::Image$new(
options=options,
name="funplotMed",
title="Funnel Plot",
width=750,
height=563,
renderFun=".funplot",
refs=list(
"metafor")))
self$add(jmvcore::Image$new(
options=options,
name="funplotLarge",
title="Funnel Plot",
width=900,
height=675,
renderFun=".funplot",
refs=list(
"metafor")))
self$add(jmvcore::Table$new(
options=options,
name="resultsTES",
title="Test of Excess Significance | Significant Findings",
rows=3,
refs=list(
"tes"),
columns=list(
list(
`name`="label",
`title`="",
`type`="text"),
list(
`name`="tesNumberOutput",
`title`="",
`type`="number",
`format`="zto"))))
self$add(jmvcore::Table$new(
options=options,
name="resultsTES2",
title="Test of Excess Significance | Estimated Power of Tests",
rows=1,
refs=list(
"tes"),
columns=list(
list(
`name`="tesOutputMin",
`title`="Min",
`type`="number",
`format`="zto"),
list(
`name`="tesOutputQ1",
`title`="Q1",
`type`="number",
`format`="zto"),
list(
`name`="tesOutputMed",
`title`="Median",
`type`="number",
`format`="zto"),
list(
`name`="tesOutputQ3",
`title`="Q3",
`type`="number",
`format`="zto"),
list(
`name`="tesOutputMax",
`title`="Max",
`type`="number",
`format`="zto"))))
self$add(jmvcore::Html$new(
options=options,
name="tesOutput3",
title="Test of Excess Significance | Results"))
self$add(jmvcore::Image$new(
options=options,
name="pCurvePlot",
title="p Curve Plot",
width=900,
height=675,
renderFun=".pcurveplot"))
self$add(jmvcore::Table$new(
options=options,
name="puniformModelOutput",
title="Publication bias test p-uniform",
rows=1,
columns=list(
list(
`name`="Lpb",
`title`="Test Statistic",
`type`="number",
`format`="zto"),
list(
`name`="pval",
`title`="p-value",
`type`="number",
`format`="pvalue"))))
self$add(jmvcore::Table$new(
options=options,
name="puniformModelOutput2",
title="Effect size estimation p-uniform",
rows=1,
columns=list(
list(
`name`="est",
`title`="Effect Size Estimate",
`type`="number",
`format`="zto"),
list(
`name`="cilb",
`title`="CI Lower Bound",
`type`="number",
`format`="zto"),
list(
`name`="ciub",
`title`="CI upper Bound",
`type`="number",
`format`="zto"),
list(
`name`="lzero",
`title`="Z",
`type`="number",
`format`="zto"),
list(
`name`="pval",
`title`="p-value",
`type`="number",
`format`="zto"),
list(
`name`="ksig",
`title`="Number of Significant Studies",
`type`="number",
`format`="zto"))))
self$add(jmvcore::Table$new(
options=options,
name="TOSToutput",
title="Two One-Sided Tests Equivalence Testing",
refs=list(
"TOSTER"),
rows=1,
columns=list(
list(
`name`="TOST_Z1",
`title`="Z-Value Lower Bound",
`type`="number",
`format`="zto"),
list(
`name`="TOST_p1",
`title`="P-Value Lower Bound",
`type`="number",
`format`="zto,pvalue"),
list(
`name`="TOST_Z2",
`title`="Z-Value Upper Bound",
`type`="number",
`format`="zto"),
list(
`name`="TOST_p2",
`title`="P-Value Upper Bound",
`type`="number",
`format`="zto"),
list(
`name`="LL_CI_TOST",
`title`="Lower Limit Confidence Interval TOST",
`type`="number",
`format`="zto"),
list(
`name`="UL_CI_TOST",
`title`="Upper Limit Confidence Interval TOST",
`type`="number",
`format`="zto,pvalue"),
list(
`name`="LL_CI_ZTEST",
`type`="number",
`format`="zto"),
list(
`name`="UL_CI_ZTEST",
`title`="Z-Value Upper Limit Confidence Interval TOST",
`type`="number",
`format`="zto"))))
self$add(jmvcore::Html$new(
options=options,
name="TOSToutputtext",
title="Two One-Sided Tests Equivalence Testing: Text Summary"))
self$add(jmvcore::Image$new(
options=options,
name="tostplot",
title="Equivalence Test Plot",
width=600,
height=450,
renderFun=".tostplot",
refs=list(
"TOSTER")))
self$add(jmvcore::Image$new(
options=options,
name="likelihoodPlot",
title="Likelihood Plot",
width=600,
height=450,
renderFun=".likelihoodPlot",
refs=list(
"llplot")))
self$add(R6::R6Class(
inherit = jmvcore::Group,
active = list(
diagplot1 = function() private$.items[["diagplot1"]],
diagplot2 = function() private$.items[["diagplot2"]],
diagplot3 = function() private$.items[["diagplot3"]],
diagplot4 = function() private$.items[["diagplot4"]],
diagplot5 = function() private$.items[["diagplot5"]],
diagplot6 = function() private$.items[["diagplot6"]],
diagplot7 = function() private$.items[["diagplot7"]],
diagplot8 = function() private$.items[["diagplot8"]],
diagplot9 = function() private$.items[["diagplot9"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="diagPlotAll",
title="Outlier and Influential Case Diagnostics")
self$add(jmvcore::Image$new(
options=options,
name="diagplot1",
title="Externally Standardized Residual",
width=750,
height=300,
renderFun=".influDiagPlot1"))
self$add(jmvcore::Image$new(
options=options,
name="diagplot2",
title="DFFITS Values",
width=750,
height=300,
renderFun=".influDiagPlot2"))
self$add(jmvcore::Image$new(
options=options,
name="diagplot3",
title="Cook's Distances",
width=750,
height=300,
renderFun=".influDiagPlot3"))
self$add(jmvcore::Image$new(
options=options,
name="diagplot4",
title="Covariance Ratios",
width=750,
height=300,
renderFun=".influDiagPlot4"))
self$add(jmvcore::Image$new(
options=options,
name="diagplot5",
title="Leave-one-out Tau Estimates",
width=750,
height=300,
renderFun=".influDiagPlot5"))
self$add(jmvcore::Image$new(
options=options,
name="diagplot6",
title="Leave-one-out (residual) Heterogeneity Test Statistics",
width=750,
height=300,
renderFun=".influDiagPlot6"))
self$add(jmvcore::Image$new(
options=options,
name="diagplot7",
title="Hat Values",
width=750,
height=300,
renderFun=".influDiagPlot7"))
self$add(jmvcore::Image$new(
options=options,
name="diagplot8",
title="Weights",
width=750,
height=300,
renderFun=".influDiagPlot8"))
self$add(jmvcore::Image$new(
options=options,
name="diagplot9",
title="Q-Q Plot",
width=700,
height=700,
renderFun=".influDiagPlot9"))}))$new(options=options))}))
metaMeanDiffBase <- if (requireNamespace('jmvcore')) R6::R6Class(
"metaMeanDiffBase",
inherit = jmvcore::Analysis,
public = list(
initialize = function(options, data=NULL, datasetId="", analysisId="", revision=0) {
super$initialize(
package = 'MAJOR',
name = 'metaMeanDiff',
version = c(1,0,0),
options = options,
results = metaMeanDiffResults$new(options=options),
data = data,
datasetId = datasetId,
analysisId = analysisId,
revision = revision,
pause = NULL,
completeWhenFilled = FALSE,
requiresMissings = FALSE)
}))
#' Mean Differences (n, M, SD)
#'
#'
#' @param data .
#' @param n1i .
#' @param m1i .
#' @param sd1i .
#' @param n2i .
#' @param m2i .
#' @param sd2i .
#' @param slab .
#' @param moderatorcor .
#' @param methodmetacor .
#' @param cormeasure .
#' @param moderatorType .
#' @param testType .
#' @param level .
#' @param showModelFit .
#' @param addcred .
#' @param addfit .
#' @param showweights .
#' @param steps .
#' @param xAxisTitle .
#' @param forestPlotSize .
#' @param funnelPlotSize .
#' @param pchForest .
#' @param forestOrder .
#' @param fsntype .
#' @param tesAlternative .
#' @param tesAlpha .
#' @param tesH0 .
#' @param showTes .
#' @param puniformSide .
#' @param selModelType .
#' @param yaxis .
#' @param yaxisInv .
#' @param enhanceFunnel .
#' @param lowerTOST .
#' @param upperTOST .
#' @param alphaTOST .
#' @param showTOST .
#' @param showInfPlot .
#' @param showLL .
#' @param showPuniform .
#' @param showSelmodel .
#' @param showPcurve .
#' @return A results object containing:
#' \tabular{llllll}{
#' \code{results$textRICH} \tab \tab \tab \tab \tab a table \cr
#' \code{results$tableTauSqaured} \tab \tab \tab \tab \tab a table \cr
#' \code{results$modelFitRICH} \tab \tab \tab \tab \tab a table \cr
#' \code{results$summaryOutputText} \tab \tab \tab \tab \tab a html \cr
#' \code{results$summaryOutputText2} \tab \tab \tab \tab \tab a html \cr
#' \code{results$plot} \tab \tab \tab \tab \tab an image \cr
#' \code{results$plotMed} \tab \tab \tab \tab \tab an image \cr
#' \code{results$plotLarge} \tab \tab \tab \tab \tab an image \cr
#' \code{results$plotSmallWide} \tab \tab \tab \tab \tab an image \cr
#' \code{results$plotMedWide} \tab \tab \tab \tab \tab an image \cr
#' \code{results$plotLargeWide} \tab \tab \tab \tab \tab an image \cr
#' \code{results$selModelOutput} \tab \tab \tab \tab \tab a table \cr
#' \code{results$fsnRICH} \tab \tab \tab \tab \tab a table \cr
#' \code{results$funplot} \tab \tab \tab \tab \tab an image \cr
#' \code{results$funplotMed} \tab \tab \tab \tab \tab an image \cr
#' \code{results$funplotLarge} \tab \tab \tab \tab \tab an image \cr
#' \code{results$resultsTES} \tab \tab \tab \tab \tab a table \cr
#' \code{results$resultsTES2} \tab \tab \tab \tab \tab a table \cr
#' \code{results$tesOutput3} \tab \tab \tab \tab \tab a html \cr
#' \code{results$pCurvePlot} \tab \tab \tab \tab \tab an image \cr
#' \code{results$puniformModelOutput} \tab \tab \tab \tab \tab a table \cr
#' \code{results$puniformModelOutput2} \tab \tab \tab \tab \tab a table \cr
#' \code{results$TOSToutput} \tab \tab \tab \tab \tab a table \cr
#' \code{results$TOSToutputtext} \tab \tab \tab \tab \tab a html \cr
#' \code{results$tostplot} \tab \tab \tab \tab \tab an image \cr
#' \code{results$likelihoodPlot} \tab \tab \tab \tab \tab an image \cr
#' \code{results$diagPlotAll$diagplot1} \tab \tab \tab \tab \tab an image \cr
#' \code{results$diagPlotAll$diagplot2} \tab \tab \tab \tab \tab an image \cr
#' \code{results$diagPlotAll$diagplot3} \tab \tab \tab \tab \tab an image \cr
#' \code{results$diagPlotAll$diagplot4} \tab \tab \tab \tab \tab an image \cr
#' \code{results$diagPlotAll$diagplot5} \tab \tab \tab \tab \tab an image \cr
#' \code{results$diagPlotAll$diagplot6} \tab \tab \tab \tab \tab an image \cr
#' \code{results$diagPlotAll$diagplot7} \tab \tab \tab \tab \tab an image \cr
#' \code{results$diagPlotAll$diagplot8} \tab \tab \tab \tab \tab an image \cr
#' \code{results$diagPlotAll$diagplot9} \tab \tab \tab \tab \tab an image \cr
#' }
#'
#' Tables can be converted to data frames with \code{asDF} or \code{\link{as.data.frame}}. For example:
#'
#' \code{results$textRICH$asDF}
#'
#' \code{as.data.frame(results$textRICH)}
#'
#' @export
metaMeanDiff <- function(
data,
n1i,
m1i,
sd1i,
n2i,
m2i,
sd2i,
slab,
moderatorcor,
methodmetacor = "REML",
cormeasure = "SMD",
moderatorType = "NON",
testType = FALSE,
level = 95,
showModelFit = FALSE,
addcred = FALSE,
addfit = TRUE,
showweights = FALSE,
steps = 5,
xAxisTitle,
forestPlotSize = "SMALL",
funnelPlotSize = "SMALL",
pchForest = "15",
forestOrder = "fit",
fsntype = "Rosenthal",
tesAlternative = "two.sided",
tesAlpha = 0.5,
tesH0 = 0,
showTes = FALSE,
puniformSide = "right",
selModelType = "none",
yaxis = "sei",
yaxisInv = FALSE,
enhanceFunnel = FALSE,
lowerTOST = -0.5,
upperTOST = 0.5,
alphaTOST = 0.05,
showTOST = FALSE,
showInfPlot = FALSE,
showLL = FALSE,
showPuniform = FALSE,
showSelmodel = FALSE,
showPcurve = FALSE) {
if ( ! requireNamespace('jmvcore'))
stop('metaMeanDiff requires jmvcore to be installed (restart may be required)')
if ( ! missing(n1i)) n1i <- jmvcore::resolveQuo(jmvcore::enquo(n1i))
if ( ! missing(m1i)) m1i <- jmvcore::resolveQuo(jmvcore::enquo(m1i))
if ( ! missing(sd1i)) sd1i <- jmvcore::resolveQuo(jmvcore::enquo(sd1i))
if ( ! missing(n2i)) n2i <- jmvcore::resolveQuo(jmvcore::enquo(n2i))
if ( ! missing(m2i)) m2i <- jmvcore::resolveQuo(jmvcore::enquo(m2i))
if ( ! missing(sd2i)) sd2i <- jmvcore::resolveQuo(jmvcore::enquo(sd2i))
if ( ! missing(slab)) slab <- jmvcore::resolveQuo(jmvcore::enquo(slab))
if ( ! missing(moderatorcor)) moderatorcor <- jmvcore::resolveQuo(jmvcore::enquo(moderatorcor))
if (missing(data))
data <- jmvcore::marshalData(
parent.frame(),
`if`( ! missing(n1i), n1i, NULL),
`if`( ! missing(m1i), m1i, NULL),
`if`( ! missing(sd1i), sd1i, NULL),
`if`( ! missing(n2i), n2i, NULL),
`if`( ! missing(m2i), m2i, NULL),
`if`( ! missing(sd2i), sd2i, NULL),
`if`( ! missing(slab), slab, NULL),
`if`( ! missing(moderatorcor), moderatorcor, NULL))
options <- metaMeanDiffOptions$new(
n1i = n1i,
m1i = m1i,
sd1i = sd1i,
n2i = n2i,
m2i = m2i,
sd2i = sd2i,
slab = slab,
moderatorcor = moderatorcor,
methodmetacor = methodmetacor,
cormeasure = cormeasure,
moderatorType = moderatorType,
testType = testType,
level = level,
showModelFit = showModelFit,
addcred = addcred,
addfit = addfit,
showweights = showweights,
steps = steps,
xAxisTitle = xAxisTitle,
forestPlotSize = forestPlotSize,
funnelPlotSize = funnelPlotSize,
pchForest = pchForest,
forestOrder = forestOrder,
fsntype = fsntype,
tesAlternative = tesAlternative,
tesAlpha = tesAlpha,
tesH0 = tesH0,
showTes = showTes,
puniformSide = puniformSide,
selModelType = selModelType,
yaxis = yaxis,
yaxisInv = yaxisInv,
enhanceFunnel = enhanceFunnel,
lowerTOST = lowerTOST,
upperTOST = upperTOST,
alphaTOST = alphaTOST,
showTOST = showTOST,
showInfPlot = showInfPlot,
showLL = showLL,
showPuniform = showPuniform,
showSelmodel = showSelmodel,
showPcurve = showPcurve)
analysis <- metaMeanDiffClass$new(
options = options,
data = data)
analysis$run()
analysis$results
}
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