tests/testthat/test-lgcm.R

In jasp-stats/jaspSem: SEM Module for JASP

context("MIMIC")

options <- list(
  .meta = list(
    categorical = list(
      hasTypes = TRUE,
      shouldEncode = TRUE
    ),
    curvePlotCategorical = list(
      shouldEncode = TRUE
    ),
    group = list(
      shouldEncode = TRUE
    ),
    regressions = list(
      hasTypes = TRUE,
      shouldEncode = TRUE
    ),
    timings = list(
      hasTypes = TRUE,
      shouldEncode = TRUE
    ),
    variables = list(
      hasTypes = TRUE,
      shouldEncode = TRUE
    )
  ),
  additionalFitMeasures = FALSE,
  bootstrapCiType = "percentileBiasCorrected",
  bootstrapSamples = 1000,
  categorical = "group",
  categorical.types = "nominal",
  ciLevel = 0.95,
  colorPalette = "colorblind",
  covariates = list(),
  covaryingLatentCurve = TRUE,
  cubic = FALSE,
  curvePlot = FALSE,
  curvePlotCategorical = "group",
  curvePlotMaxLines = 30,
  dependentCorrelation = TRUE,
  emulation = "lavaan",
  errorCalculationMethod = "standard",
  estimator = "default",
  exogenousLatentCorrelation = TRUE,
  group = "",
  impliedCovariance = FALSE,
  intercept = TRUE,
  latentInterceptFixedToZero = TRUE,
  linear = TRUE,
  manifestInterceptFixedToZero = FALSE,
  misfitPlot = FALSE,
  naAction = "fiml",
  pathPlot = FALSE,
  pathPlotMean = FALSE,
  pathPlotParameter = FALSE,
  plotHeight = 320,
  plotWidth = 480,
  quadratic = FALSE,
  rSquared = FALSE,
  regressions = "x3",
  regressions.types = "scale",
  residualCovariance = FALSE,
  residualSingleIndicatorOmitted = TRUE,
  residualVariance = TRUE,
  scalingParameter = TRUE,
  standardizedEstimate = FALSE,
  standardizedEstimateType = "all",
  syntax = FALSE,
  threshold = TRUE,
  timings = list(
    list(timing = 0, variable = "y1"),
    list(timing = 1, variable = "y2"),
    list(timing = 2, variable = "y3"),
    list(timing = 3, variable = "y4")
  ),
  timings.types = c("scale", "scale", "scale", "scale"),
  variables = c("y1", "y2", "y3", "y4"),
  variables.types = c("scale", "scale", "scale", "scale")
)

set.seed(1)
results <- runAnalysis("LatentGrowthCurve", data = testthat::test_path("poldem_grouped.csv"), options = options, makeTests = F)

test_that("Chi-square Test table results match", {
  table <- results[["results"]][["modelContainer"]][["collection"]][["modelContainer_maintab"]][["collection"]][["modelContainer_maintab_chisqtab"]][["data"]]
  jaspTools::expect_equal_tables(table,
                                 list(187.534921995622, 14, "Baseline model", "", 69.7448930126911,
                                      9, "Growth curve model", 1.7085333148259e-11))
})

test_that("Latent covariances table results match", {
  table <- results[["results"]][["modelContainer"]][["collection"]][["modelContainer_partabs"]][["collection"]][["modelContainer_partabs_latcov"]][["data"]]
  jaspTools::expect_equal_tables(table,
                                 list(-0.586546753687804, 0.920563814498034, 0.167008530405115, "Intercept",
                                      0.664011207974188, "Linear slope", 0.384474046480888, "<unicode><unicode>",
                                      0.434381805309756))
})

test_that("Latent curve table results match", {
  table <- results[["results"]][["modelContainer"]][["collection"]][["modelContainer_partabs"]][["collection"]][["modelContainer_partabs_latcur"]][["data"]]
  jaspTools::expect_equal_tables(table,
                                 list(1.91067166426575, 7.29253585271669, "Intercept", 4.60160375849122,
                                      "Mean", 0.000803406635452308, 1.37294976614428, 3.35161844370616,
                                      2.23084848964563, 7.43262609819151, "Intercept", 4.83173729391857,
                                      "Variance", 0.000271502073965424, 1.32700846790472, 3.6410749522553,
                                      -1.31843387751812, 0.254743186892948, "Linear slope", -0.531845345312584,
                                      "Mean", 0.185100357300383, 0.401328054193874, -1.32521347499834,
                                      -0.279812019736802, 0.58560544257759, "Linear slope", 0.152896711420394,
                                      "Variance", 0.488592554701348, 0.220773817565194, 0.69254911251079
                                 ))
})

test_that("Regressions table results match", {
  table <- results[["results"]][["modelContainer"]][["collection"]][["modelContainer_partabs"]][["collection"]][["modelContainer_partabs_latreg"]][["data"]]
  jaspTools::expect_equal_tables(table,
                                 list(-0.0164990486098335, 0.83129631851575, "Intercept", 0.407398634952958,
                                      "x3", 0.0596085724085578, 0.216278302512925, 1.88367779023331,
                                      -1.58384563758143, 0.783933270269892, "Intercept", -0.399956183655768,
                                      "group", 0.507881961502067, 0.604036330904052, -0.662139284001609,
                                      0.0117615965627584, 0.259581344548597, "Linear slope", 0.135671470555678,
                                      "x3", 0.03187258823186, 0.0632204851570258, 2.14600489412095,
                                      -0.494241490855952, 0.197885872636682, "Linear slope", -0.148177809109635,
                                      "group", 0.401346504623975, 0.176566347379862, -0.839218861966079
                                 ))
})

test_that("Residual variances table results match", {
  table <- results[["results"]][["modelContainer"]][["collection"]][["modelContainer_partabs"]][["collection"]][["modelContainer_partabs_resvar"]][["data"]]
  jaspTools::expect_equal_tables(table,
                                 list(-0.324588296041848, 3.6454907529351, 1.66045122844662, 0.101114170618842,
                                      1.01279387792133, "y1", 1.63947597299319, 5.29913958703259,
                                      11.0467904666191, 8.17296502682586, 2.4894871941683e-08, 1.46626441223494,
                                      "y2", 5.57400490568294, 5.45925010966836, 11.5067395932775,
                                      8.48299485147291, 3.82817306743277e-08, 1.54275525757384, "y3",
                                      5.4986005134822, -0.442535417440978, 4.28674625451398, 1.9221054185365,
                                      0.11112371395684, 1.20647157530927, "y4", 1.59316262220581
                                 ))
})