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more estimators for cfa, change standardization output
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‎DESCRIPTION

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@@ -2,7 +2,7 @@ Package: jaspFactor
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Type: Package
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Title: Factor Module for JASP
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Version: 0.19.0
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Date: 2023-04-14
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Date: 2024-08-19
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Author: JASP Team
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Website: jasp-stats.org
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Maintainer: JASP Team <[email protected]>

‎R/confirmatoryfactoranalysis.R

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‎inst/help/ConfirmatoryFactorAnalysis.md

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@@ -60,7 +60,7 @@ JASP allows the factors in turn to be indicators of a second-order factor. This
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### Advanced
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-------
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- Emulation: Emulate results from different software
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- Error calculation: Change how standard errors for the parameters are computed
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- Error calculation: Change how standard errors for the parameters are computed, if bootstrap the CIs are percentile bootstrap type
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- Estimator: change the estimator for the CFA (Auto: ML if only scale variables used, WLS otherwise)
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- Standardization: display standardized parameters for different standardization schemes
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- Missing data handling: change the missing data handling method.

‎inst/help/forQml/tooltipEstimators.md

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### Help on Estimators
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Some of the estimators come with options that are set in the background:
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- Estimators without extra effects (standard errors and model test are standard):
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- ML, GLS, WLS, ULS, DWLS, DLS
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- Extensions of ML-estimators with extra effects:
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- MLM: classic robust se (se="robust.sem"), Satorra-Bentler test statistic (test="satorra.bentler")
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- MLMV: classic robust se, scaled and shifted test statistic (test="scaled.shifted")
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- MLMVS: classic robust se, mean and var adjusted Satterthwaite style test statistic (test="mean.var.adjusted")
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- MLF: first-order standard se (information="first.order"), standard test
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- MLR: Huber-White robust se (se="robust.huber.white"), Yuan-Bentler T2-star test statistic (test="yuan.bentler.mplus")
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- Others:
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- WLSM: implies DWLS with scaled test and robust se
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- WLSMV: implies DWLS with mean and var adjusted test and robust se
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- ULSM: implies ULS with scaled test and robust se
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- ULSMV: implies ULS with mean-var adjusted test and robust se
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- Note: If you specify "Standard errors" instead of leaving it at default the corresponding options set by the estimators in the background will be overwritten

‎inst/qml/ConfirmatoryFactorAnalysis.qml

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@@ -102,8 +102,8 @@ Form
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label: qsTr("Model identification")
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name: "modelIdentification"
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values: [
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{ label: qsTr("Factor variances"), value: "factorVariance" },
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{ label: qsTr("Marker variable"), value: "markerVariable" },
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{ label: qsTr("Factor variances"), value: "factorVariance" },
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{ label: qsTr("Effects coding"), value: "effectsCoding" }
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]
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}
@@ -206,64 +206,88 @@ Form
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Section
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{
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title: qsTr("Advanced")
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RadioButtonGroup
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{
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title: qsTr("Mimic package")
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name: "packageMimiced"
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RadioButton { label: qsTr("Lavaan"); value: "lavaan" ; checked: true }
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RadioButton { label: qsTr("Mplus") ; value: "Mplus" }
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RadioButton { label: qsTr("EQS") ; value: "EQS" }
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}
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Group
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{
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title: qsTr("Error calculation")
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CIField { text: qsTr("CI level"); name: "ciLevel" }
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RadioButtonGroup
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Group {
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DropDown
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{
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title: qsTr("Standard error")
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name: "seType"
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RadioButton { label: qsTr("Standard"); value: "standard"; checked: true}
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RadioButton { label: qsTr("Robust"); value: "robust" }
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RadioButton {
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label: qsTr("Bootstrap")
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value: "bootstrap"
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IntegerField {
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label: qsTr("Bootstrap samples")
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name: "bootstrapSamples"
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defaultValue: 1000
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min: 100
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max: 1000000
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}
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name: "packageMimiced"
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label: qsTr("Mimic")
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values: [
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{ label: qsTr("Lavaan"), value: "lavaan" },
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{ label: qsTr("Mplus"), value: "mplus" },
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{ label: qsTr("EQS"), value: "eqs" }
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]
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}
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RowLayout
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{
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DropDown
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{
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name: "estimator"
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label: qsTr("Estimator")
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id: estimator
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values: [
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{ label: qsTr("Default"), value: "default" },
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{ label: qsTr("ML"), value: "ml" },
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{ label: qsTr("GLS"), value: "gls" },
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{ label: qsTr("WLS"), value: "wls" },
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{ label: qsTr("ULS"), value: "uls" },
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{ label: qsTr("DWLS"), value: "dwls" },
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{ label: qsTr("DLS"), value: "dls" },
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{ label: qsTr("PML"), value: "pml" },
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{ label: qsTr("MLM"), value: "mlm" },
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{ label: qsTr("MLMV"), value: "mlmv" },
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{ label: qsTr("MLMVS"), value: "mlmvs" },
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{ label: qsTr("MLF"), value: "mlf" },
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{ label: qsTr("MLR"), value: "mlr" },
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{ label: qsTr("WLSM"), value: "wlsm" },
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{ label: qsTr("WLSMV"), value: "wlsmv" },
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{ label: qsTr("ULSM"), value: "ulsm" },
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{ label: qsTr("ULSMV"), value: "ulsmv" }
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]
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}
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HelpButton
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{
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toolTip: qsTr("Click for more information")
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helpPage: "forQml/tooltipEstimators"
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}
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}
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}
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RadioButtonGroup
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{
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title: qsTr("Estimator")
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name: "estimator"
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RadioButton { label: qsTr("Auto") ; value: "default"; checked: true }
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RadioButton { label: qsTr("ML") ; value: "maximumLikelihood" }
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RadioButton { label: qsTr("GLS") ; value: "generalizedLeastSquares" }
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RadioButton { label: qsTr("WLS") ; value: "weightedLeastSquares" }
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RadioButton { label: qsTr("ULS") ; value: "unweightedLeastSquares" }
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RadioButton { label: qsTr("DWLS") ; value: "diagonallyWeightedLeastSquares" }
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}
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DropDown
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DropDown
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{
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label: qsTr("Standard errors")
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name: "seType"
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id: errorCalc
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values: [
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{ label: qsTr("Default"), value: "default" },
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{ label: qsTr("Standard"), value: "standard" },
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{ label: qsTr("Robust"), value: "robust" },
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{ label: qsTr("Bootstrap"), value: "bootstrap" }
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]
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}
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IntegerField
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{
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visible: errorCalc.value == "bootstrap"
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name: "bootstrapSamples"
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label: qsTr(" Bootstrap samples")
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defaultValue: 1000
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min: 100
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max: 1000000
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}
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CIField { text: qsTr(" CI level"); name: "ciLevel" }
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DropDown
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{
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name: "naAction"
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label: qsTr("Missing data handling")
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values:
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[
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{ label: qsTr("FIML") , value: "fiml" },
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{ label: qsTr("Listwise deletion") , value: "listwise" },
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{ label: qsTr("FIML") , value: "fiml" },
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{ label: qsTr("Pairwise") , value: "pairwise" },
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{ label: qsTr("Two-stage") , value: "twoStage" },
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{ label: qsTr("Robust two-stage") , value: "twoStageRobust" },
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]
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}
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}
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RadioButtonGroup
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{

‎tests/testthat/test-confirmatoryfactoranalysis.R

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@@ -201,48 +201,44 @@ test_that("[CFA Second order] Chi-square test table results match", {
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})
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test_that("Bootstrapping works", {
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options <- jaspTools::analysisOptions("confirmatoryFactorAnalysis")
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options$group <- ""
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options$invarianceTesting <- "configural"
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options$packageMimiced <- "lavaan"
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options$seType <- "bootstrap"
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options$bootstrapSamples <- 100
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options$estimator <- "default"
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options$standardized <- "none"
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options$factors <- list(
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list(indicators = list("x1", "x2", "x3"), name = "Factor1", title = "Factor 1", types = rep("scale", 3)),
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list(indicators = list("x4", "x5", "x6"), name = "Factor2", title = "Factor 2", types = rep("scale", 3)),
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list(indicators = list("x7", "x8", "x9"), name = "Factor3", title = "Factor 3", types = rep("scale", 3))
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)
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options$modelIdentification <- "factorVariance"
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options$naAction <- "listwise"
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set.seed(1)
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results <- jaspTools::runAnalysis("confirmatoryFactorAnalysis", "holzingerswineford.csv", options)
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# factor loadings with bootstrapping are correct
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options <- jaspTools::analysisOptions("confirmatoryFactorAnalysis")
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options$group <- ""
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options$invarianceTesting <- "configural"
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options$packageMimiced <- "lavaan"
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options$seType <- "bootstrap"
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options$bootstrapSamples <- 100
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options$estimator <- "default"
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options$standardized <- "none"
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options$factors <- list(
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list(indicators = list("x1", "x2", "x3"), name = "Factor1", title = "Factor 1", types = rep("scale", 3)),
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list(indicators = list("x4", "x5", "x6"), name = "Factor2", title = "Factor 2", types = rep("scale", 3)),
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list(indicators = list("x7", "x8", "x9"), name = "Factor3", title = "Factor 3", types = rep("scale", 3))
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)
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options$modelIdentification <- "factorVariance"
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options$naAction <- "listwise"
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set.seed(1)
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results <- jaspTools::runAnalysis("confirmatoryFactorAnalysis", "holzingerswineford.csv", options)
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test_that("Factor loadings table results match", {
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table <- results[["results"]][["estimates"]][["collection"]][["estimates_fl1"]][["data"]]
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jaspTools::expect_equal_tables(table,
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list(0.712022271311838, 1.11279383173753, 0.899620313867488,
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"Factor 1", 0, "x1", 0.0808465333987386, 11.1275063512065, 0.339182433474584,
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0.693156723678194, 0.49794051110941, "Factor 1",
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1.28623778294923e-10, "x2", 0.0774547818506273, 6.42878979466621,
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0.539990088382033, 0.805660643384033, 0.656156092628451,
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"Factor 1", 0, "x3", 0.0744212256974568, 8.81678696472846, 0.856032790026098,
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1.08543684864592, 0.989693449094392, "Factor 2",
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0, "x4", 0.0566367179185465, 17.4744138690689, 0.954112872546464,
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1.24054019999221, 1.10160465003145, "Factor 2",
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0, "x5", 0.0626757561168699, 17.5762482701815, 0.803928010900409,
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1.03630968014001, 0.916600977759373, "Factor 2",
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0, "x6", 0.0536584940344529, 17.0821226769958, 0.375767927218761,
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0.741040160352204, 0.619475433557926, "Factor 3",
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0, "x7", 0.0695825769015842, 8.90273774186456, 0.506218568773711,
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0.900974372672674, 0.730948802915075, "Factor 3",
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0, "x8", 0.0659093164600047, 11.0902197469857, 0.498364732719689,
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0.860170344673322, 0.669980108781259, "Factor 3",
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0, "x9", 0.0650169734598685, 10.3046954222623))
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list(0.712022271311838, 1.11279383173753, 0.899620313867488, "Factor 1",
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0, "x1", 0.101880932132255, 8.8301146744482, 0.339182433474583,
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0.693156723678194, 0.49794051110941, "Factor 1", 5.03185138001072e-09,
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"x2", 0.0851745954124038, 5.84611536689373, 0.539990088382032,
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0.805660643384033, 0.656156092628451, "Factor 1", 0, "x3", 0.0702283472359389,
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9.34318004699771, 0.856032790026097, 1.08543684864592, 0.989693449094393,
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"Factor 2", 0, "x4", 0.060824826209009, 16.2712088266979, 0.954112872546464,
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1.24054019999221, 1.10160465003145, "Factor 2", 0, "x5", 0.0610564023902934,
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18.042410081577, 0.803928010900409, 1.03630968014001, 0.916600977759372,
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"Factor 2", 0, "x6", 0.0544830064226891, 16.8236123140528, 0.37576792721876,
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0.741040160352204, 0.619475433557926, "Factor 3", 7.69848629289527e-11,
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"x7", 0.0952105063825611, 6.50637683901018, 0.50621856877371,
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0.900974372672673, 0.730948802915075, "Factor 3", 2.32125429988628e-12,
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"x8", 0.104217630469302, 7.0136770489172, 0.498364732719688,
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0.860170344673323, 0.669980108781259, "Factor 3", 5.52868861802835e-12,
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"x9", 0.0972211926575642, 6.8912969535468))
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})
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