R/OpenStatsReportMM.R

In OpenStats: A Robust and Scalable Software Package for Reproducible Analysis of High-Throughput genotype-phenotype association

OpenStatsReportCont <- function(object,
                                debug = FALSE) {
  if (!is.null(object$messages)) {
    return(NULL)
  }
  #####################################################################
  Labels <- OpenStatsListLevels(object = object)
  Fmodel <- object$output$Final.Model
  frm <- formula(Fmodel)
  fim <- object$input$fixed
  depVariable <- all_vars0(frm)[1]
  equation <- ifelse(
    Labels$Weight %in% all_vars0(frm),
    paste0("including ", Labels$Weight),
    paste0("not including ", Labels$Weight)
  )
  formula <- printformula(frm)
  # modelContrast  = modelContrasts(formula = frm,data = object$input$data)
  framework <- switch(
    # object$output$Final.Model.Tag
    class(object$output$Final.Model),
    lme  = "Linear Mixed Model framework",
    gls  = "Linear Model Using Generalized Least Squares framework",
    glm  = "Generalized Linear Model framework"
  )
  # fittingMethod    = toupper(object$output$Final.Model.Tag)
  fittingMethod <- toupper(class(object$output$Final.Model))
  #####################################################################
  x <- object$input$OpenStatsList@datasetPL
  columnOfInterest <- x[, c(depVariable)]
  #####################################################################
  variability <- list(
    "Value" = length(unique(columnOfInterest)) / max(length(columnOfInterest), 1),
    "Type" = "Total unique response divided by total number of response"
  )
  #####################################################################
  DSsize <- SummaryStats(
    x = object$input$data,
    formula = checkModelTermsInData(
      formula = object$input$fixed,
      data = x,
      responseIsTheFirst = TRUE
    ),
    # label = 'Summary statistics',
    lower = TRUE,
    drop = TRUE,
    sep = "_"
  )
  MultiBatch <- ifelse(multiBatch(x),
    "Dataset contains multiple batches",
    "Dataset contains single batch"
  )
  addInfo <- list(
    Data = list(
      "Data signature" = dataSignature(
        formula = object$input$fixed,
        data = object$input$data
      ),
      "Variability" = variability,
      "Summary statistics" = DSsize
    ),
    # 'Formula'                = list(
    # 	input   = printformula(object$input$fixed),
    # 	final   =	printformula(formula)
    # ),
    Analysis = list(
      "Model setting" = extractLmeTerms(object),
      "Is model optimised" = optimM(object$output$optimised),
      "Multibatch in analysis" = MultiBatch,
      "Gender included in analysis" = GenderIncludedInAnalysis(x),
      "Further models" = if (!is.null(object$output$SplitModels)) {
        lapply(object$output$SplitModels, function(v) {
          if (class(v) %in% c("lme", "gls", "glm")) {
            r <- as.list(unmatrix0(summary1(v)$tTable))
            r$Model <- printformula(v$SplitFormula)
            r$Method <- pasteComma(class(v), truncate = FALSE)
          } else {
            r <- v
          }
          return(r)
        })
      } else {
        NULL
      },
      "Effect sizes" = object$output$"Effect sizes",
      "Other residual normality tests" = object$output$ResidualNormalityTests
    )
  )
  #####################################################################
  pcS <- object$output$"Effect sizes"$"Combined effect sizes.Genotype_Sex"$"Percentage change"
  pcO <- object$output$"Effect sizes"$Genotype$"Percentage change"
  percentageChanges <- if (!is.null(pcS)) {
    pcS
  } else {
    pcO
  }
  SexDymFinalModel <- TermInFormulaReturn(
    active = TRUE,
    formula = frm,
    term = CombineLevels(Labels$Genotype$Genotype, Labels$Sex$Sex, debug = debug),
    return = TRUE,
    not = FALSE,
    debug = debug
  )
  SexDymInputModel <- TermInFormulaReturn(
    active = TRUE,
    formula = fim,
    term = CombineLevels(Labels$Genotype$Genotype, Labels$Sex$Sex, debug = debug),
    return = TRUE,
    not = FALSE,
    debug = debug
  )

  #####################################################################
  OpenStatsReportMM0 <- list(
    "Applied method" = paste0(framework, ", ", fittingMethod, ", ", format(equation)),
    "Dependent variable" = depVariable,
    "Batch included" = object$output$BatchIn,
    "Batch p-value" = NULL,
    "Residual variances homogeneity" = object$output$VarHomoIn,
    "Residual variances homogeneity p-value" = NULL,
    #####################################################################
    "Genotype contribution" = list(
      Overall = TermInFormulaReturn(
        active = TRUE,
        formula = frm,
        term = CombineLevels(Labels$Genotype$Genotype,
          Labels$Sex$Sex,
          debug = debug
        ),
        return = NULL,
        not = modelSummaryPvalueExtract(
          x = Fmodel,
          variable = Labels$Genotype$Genotype,
          anova = TRUE,
          debug = debug
        ),
        debug = debug
      ),
      "Sex FvKO p-value" = TermInFormulaReturn(
        active = TRUE,
        formula = frm,
        term = CombineLevels(
          Labels$Sex$Sex,
          Labels$Genotype$Genotype,
          debug = debug
        ),
        not = NULL,
        return = modelSummaryPvalueExtract(
          x = object$output$SplitModels$Genotype_Sex,
          # SexFemale:Genotypeexperimental
          variable = CombineLevels(
            paste0("Sex", Labels$Sex$Female),
            Labels$Genotype$Levels,
            debug = debug
          ),
          anova = FALSE,
          debug = debug
        ),
        debug = debug
      ),
      "Sex MvKO p-value" = TermInFormulaReturn(
        active = TRUE,
        formula = frm,
        term = CombineLevels(
          Labels$Sex$Sex,
          Labels$Genotype$Genotype,
          debug = debug
        ),
        not = NULL,
        return = modelSummaryPvalueExtract(
          x = object$output$SplitModels$Genotype_Sex,
          variable = CombineLevels(
            paste0("Sex", Labels$Sex$Male),
            Labels$Genotype$Levels,
            debug = debug
          ),
          anova = FALSE,
          debug = debug
        ),
        debug = debug
      ),
      "Sexual dimorphism detected" = list(
        "Criteria" = SexDymFinalModel,
        "Note" = paste0(
          "Genotype-Sex interaction ",
          ifelse(SexDymInputModel, "is", "is not"),
          " part of the input ",
          ifelse(SexDymFinalModel, "(it is part of the final)", "(it is not part of the final)"),
          " model. "
        )
      )
    ),
    "Genotype estimate" =
      modelSummaryPvalueExtract(
        x = Fmodel,
        variable = unlist(Labels$Genotype$Levels),
        anova = FALSE,
        what = "Value",
        debug = debug,
        ci_display = TRUE
      ),
    "Genotype standard error" =
      modelSummaryPvalueExtract(
        x = Fmodel,
        variable = unlist(Labels$Genotype$Levels),
        anova = FALSE,
        what = "Std.Error",
        debug = debug
      ),
    "Genotype p-value" =
      modelSummaryPvalueExtract(
        x = Fmodel,
        variable = Labels$Genotype$Genotype,
        anova = TRUE,
        debug = debug
      ),
    "Genotype percentage change" = percentageChanges,
    "Genotype effect size" = object$output$"Effect sizes"[[Labels$Genotype$Genotype]],
    #####################################################################
    "Sex estimate" = modelSummaryPvalueExtract(
      x = Fmodel,
      variable = unlist(Labels$Sex$Levels),
      anova = FALSE,
      what = "Value",
      debug = debug,
      ci_display = TRUE
    ),
    "Sex standard error" = modelSummaryPvalueExtract(
      x = Fmodel,
      variable = unlist(Labels$Sex$Levels),
      anova = FALSE,
      what = "Std.Error",
      debug = debug
    ),
    "Sex p-value" = modelSummaryPvalueExtract(
      x = Fmodel,
      variable = Labels$Sex$Sex,
      anova = TRUE,
      debug = debug
    ),
    "Sex effect size" = object$output$"Effect sizes"[[Labels$Sex$Sex]],
    #####################################################################
    "LifeStage estimate" = modelSummaryPvalueExtract(
      x = Fmodel,
      variable = unlist(Labels$LifeStage$Levels),
      anova = FALSE,
      what = "Value",
      debug = debug,
      ci_display = TRUE
    ),
    "LifeStage standard error" = modelSummaryPvalueExtract(
      x = Fmodel,
      variable = unlist(Labels$LifeStage$Levels),
      anova = FALSE,
      what = "Std.Error",
      debug = debug
    ),
    "LifeStage p-value" = modelSummaryPvalueExtract(
      x = Fmodel,
      variable = Labels$LifeStage$LifeStage,
      anova = TRUE,
      debug = debug
    ),
    "LifeStage effect size" = object$output$"Effect sizes"[[Labels$LifeStage$LifeStage]],
    #####################################################################
    "Weight estimate" = modelSummaryPvalueExtract(
      x = Fmodel,
      variable = Labels$Weight,
      anova = FALSE,
      what = "Value",
      debug = debug,
      ci_display = TRUE
    ),
    "Weight standard error" = modelSummaryPvalueExtract(
      x = Fmodel,
      variable = Labels$Weight,
      anova = FALSE,
      what = "Std.Error",
      debug = debug
    ),
    "Weight p-value" = modelSummaryPvalueExtract(
      x = Fmodel,
      variable = Labels$Weight,
      anova = TRUE,
      debug = debug
    ),
    "Weight effect size" = object$output$"Effect sizes"[[Labels$Weight]],
    #####################################################################
    "Gp1 genotype" = Labels$Genotype$Control,
    "Gp1 Residuals normality test" = object$output$ResidualNormalityTests$Genotype[Labels$Genotype$Control][[1]],
    "Gp2 genotype" = Labels$Genotype$Mutant,
    "Gp2 Residuals normality test" = object$output$ResidualNormalityTests$Genotype[Labels$Genotype$Mutant][[1]],
    #####################################################################
    "Blups test" = NULL,
    "Rotated residuals normality test" = NULL,
    #####################################################################
    "Intercept estimate" = modelSummaryPvalueExtract(
      x = Fmodel,
      variable = "(Intercept)",
      anova = FALSE,
      what = "Value",
      debug = debug,
      ci_display = TRUE
    ),
    "Intercept standard error" = modelSummaryPvalueExtract(
      x = Fmodel,
      variable = "(Intercept)",
      anova = FALSE,
      what = "Std.Error",
      debug = debug
    ),
    "Intercept p-value" = modelSummaryPvalueExtract(
      x = Fmodel,
      variable = "(Intercept)",
      anova = TRUE,
      debug = debug
    ),
    #####################################################################
    "Interactions included" = list(
      "Genotype Sex" = TermInFormulaReturn(
        formula = frm,
        term = CombineLevels(Labels$Genotype$Genotype, Labels$Sex$Sex, debug = debug),
        return =
          !is.null(
            modelSummaryPvalueExtract(
              x = Fmodel,
              variable = CombineLevels(Labels$Genotype$Genotype, Labels$Sex$Sex, debug = debug),
              anova = TRUE,
              debug = debug
            )
          ),
        not = NULL
      ),
      "Genotype LifeStage" = TermInFormulaReturn(
        formula = frm,
        term = CombineLevels(Labels$Genotype$Genotype, Labels$LifeStage$LifeStage, debug = debug),
        return = !is.null(
          modelSummaryPvalueExtract(
            x = Fmodel,
            variable = CombineLevels(Labels$Genotype$Genotype, Labels$LifeStage$LifeStage, debug = debug),
            anova = TRUE,
            debug = debug
          )
        ),
        not = NULL
      ),
      "Sex LifeStage" = TermInFormulaReturn(
        formula = frm,
        term = CombineLevels(Labels$Sex$Sex, Labels$LifeStage$LifeStage, debug = debug),
        return = !is.null(
          modelSummaryPvalueExtract(
            x = Fmodel,
            variable = CombineLevels(Labels$Sex$Sex, Labels$LifeStage$LifeStage, debug = debug),
            anova = TRUE,
            debug = debug
          )
        ),
        not = NULL
      ),
      "Genotype Sex LifeStage" = TermInFormulaReturn(
        formula = frm,
        term = CombineLevels(
          Labels$Genotype$Genotype,
          Labels$Sex$Sex,
          Labels$LifeStage$LifeStage,
          len   = 3,
          debug = debug
        ),
        return = !is.null(
          modelSummaryPvalueExtract(
            x = Fmodel,
            variable = CombineLevels(
              Labels$Genotype$Genotype,
              Labels$Sex$Sex,
              Labels$LifeStage$LifeStage,
              len   = 3,
              debug = debug
            ),
            anova = TRUE,
            debug = debug
          )
        ),
        not = NULL
      )
    ),
    #####################################################################
    ################ interaction
    "Interactions p-value" = list(
      "Genotype Sex" =
        modelSummaryPvalueExtract(
          x = Fmodel,
          variable = CombineLevels(Labels$Genotype$Genotype, Labels$Sex$Sex, debug = debug),
          anova = TRUE,
          debug = debug
        ),
      "Genotype LifeStage" =
        modelSummaryPvalueExtract(
          x = Fmodel,
          variable = CombineLevels(Labels$Genotype$Genotype, Labels$LifeStage$LifeStage, debug = debug),
          anova = TRUE,
          debug = debug
        ),
      "Sex LifeStage" =
        modelSummaryPvalueExtract(
          x = Fmodel,
          variable = CombineLevels(Labels$Sex$Sex, Labels$LifeStage$LifeStage, debug = debug),
          anova = TRUE,
          debug = debug
        ),
      "Genotype Sex LifeStage" =
        modelSummaryPvalueExtract(
          x = Fmodel,
          variable = CombineLevels(
            Labels$Genotype$Genotype,
            Labels$Sex$Sex,
            Labels$LifeStage$LifeStage,
            debug = debug,
            len = 3
          ),
          anova = TRUE,
          debug = debug
        )
    ),
    #####################################################################
    ################ Sex interactions
    "Sex FvKO estimate" =
      modelSummaryPvalueExtract(
        x = object$output$SplitModels$Genotype_Sex,
        variable = CombineLevels(
          paste0("Sex", Labels$Sex$Female),
          Labels$Genotype$Levels,
          debug = debug
        ),
        anova = FALSE,
        what = "Value",
        debug = debug,
        ci_display = TRUE
      ),
    "Sex FvKO standard error" = modelSummaryPvalueExtract(
      x = object$output$SplitModels$Genotype_Sex,
      variable = CombineLevels(
        paste0("Sex", Labels$Sex$Female),
        Labels$Genotype$Levels,
        debug = debug
      ),
      anova = FALSE,
      what = "Std.Error",
      debug = debug
    ),
    "Sex FvKO p-value" = modelSummaryPvalueExtract(
      x = object$output$SplitModels$Genotype_Sex,
      variable = CombineLevels(
        paste0("Sex", Labels$Sex$Female),
        Labels$Genotype$Levels,
        debug = debug
      ),
      anova = FALSE,
      debug = debug
    ),
    "Sex FvKO effect size" = object$output$"Effect sizes"[[paste(Labels$Genotype$Genotype, Labels$Sex$Female, sep = "_")]],
    #####################################################################
    "Sex MvKO estimate" = modelSummaryPvalueExtract(
      x = object$output$SplitModels$Genotype_Sex,
      variable = CombineLevels(
        paste0("Sex", Labels$Sex$Male),
        Labels$Genotype$Levels,
        debug = debug
      ),
      anova = FALSE,
      what = "Value",
      debug = debug,
      ci_display = TRUE
    ),
    "Sex MvKO standard error" = modelSummaryPvalueExtract(
      x = object$output$SplitModels$Genotype_Sex,
      variable = CombineLevels(
        paste0("Sex", Labels$Sex$Male),
        Labels$Genotype$Levels,
        debug = debug
      ),
      anova = FALSE,
      what = "Std.Error",
      debug = debug
    ),
    "Sex MvKO p-value" = modelSummaryPvalueExtract(
      x = object$output$SplitModels$Genotype_Sex,
      variable = CombineLevels(
        paste0("Sex", Labels$Sex$Male),
        Labels$Genotype$Levels,
        debug = debug
      ),
      anova = FALSE,
      debug = debug
    ),
    "Sex MvKO effect size" = object$output$"Effect sizes"[[paste(Labels$Genotype$Genotype, Labels$Sex$Male, sep = "_")]],
    #####################################################################
    ################ LifeStage interaction
    "LifeStage EvKO estimate" = modelSummaryPvalueExtract(
      x = object$output$SplitModels$Genotype_LifeStage,
      variable = CombineLevels(
        paste0(Labels$LifeStage$LifeStage, Labels$LifeStage$Early),
        Labels$Genotype$Levels,
        debug = debug
      ),
      anova = FALSE,
      what = "Value",
      debug = debug,
      ci_display = TRUE
    ),
    "LifeStage EvKO standard error" = modelSummaryPvalueExtract(
      x = object$output$SplitModels$Genotype_LifeStage,
      variable = CombineLevels(
        paste0(Labels$LifeStage$LifeStage, Labels$LifeStage$Early),
        Labels$Genotype$Levels,
        debug = debug
      ),
      anova = FALSE,
      what = "Std.Error",
      debug = debug
    ),
    "LifeStage EvKO p-value" = modelSummaryPvalueExtract(
      x = object$output$SplitModels$Genotype_LifeStage,
      variable = CombineLevels(
        paste0(Labels$LifeStage$LifeStage, Labels$LifeStage$Early),
        Labels$Genotype$Levels,
        debug = debug
      ),
      anova = FALSE,
      debug = debug
    ),
    "LifeStage EvKO effect size" = object$output$"Effect sizes"$Genotype_Early,
    #####################################################################
    "LifeStage LvKO estimate" = modelSummaryPvalueExtract(
      x = object$output$SplitModels$Genotype_LifeStage,
      variable = CombineLevels(
        paste0(Labels$LifeStage$LifeStage, Labels$LifeStage$Late),
        Labels$Genotype$Levels,
        debug = debug
      ),
      anova = FALSE,
      what = "Value",
      debug = debug,
      ci_display = TRUE
    ),
    "LifeStage LvKO standard error" = modelSummaryPvalueExtract(
      x = object$output$SplitModels$Genotype_LifeStage,
      variable = CombineLevels(
        paste0(Labels$LifeStage$LifeStage, Labels$LifeStage$Late),
        Labels$Genotype$Levels,
        debug = debug
      ),
      anova = FALSE,
      what = "Std.Error",
      debug = debug
    ),
    "LifeStage LvKO p-value" = modelSummaryPvalueExtract(
      x = object$output$SplitModels$Genotype_LifeStage,
      variable = CombineLevels(
        paste0(Labels$LifeStage$LifeStage, Labels$LifeStage$Late),
        Labels$Genotype$Levels,
        debug = debug
      ),
      anova = FALSE,
      debug = debug
    ),
    "LifeStage LvKO effect size" = object$output$"Effect sizes"$Genotype_Late,
    #####################################################################
    ################ Sex LifeStage Genotype interactions
    # 1.
    "LifeStageSexGenotype FvEvKO estimate" = modelSummaryPvalueExtract(
      x = object$output$SplitModels$Genotype_Sex.LifeStage,
      variable = CombineLevels(
        paste0(Labels$Sex$Sex, Labels$Sex$Female),
        paste0(Labels$LifeStage$LifeStage, Labels$LifeStage$Early),
        Labels$Genotype$Levels,
        debug = debug
      ),
      anova = FALSE,
      what = "Value",
      debug = debug,
      ci_display = TRUE
    ),
    "LifeStageSexGenotype FvEvKO standard error" = modelSummaryPvalueExtract(
      x = object$output$SplitModels$Genotype_Sex.LifeStage,
      variable = CombineLevels(
        paste0(Labels$Sex$Sex, Labels$Sex$Female),
        paste0(Labels$LifeStage$LifeStage, Labels$LifeStage$Early),
        Labels$Genotype$Levels,
        debug = debug
      ),
      anova = FALSE,
      what = "Std.Error",
      debug = debug
    ),
    "LifeStageSexGenotype FvEvKO p-value" = modelSummaryPvalueExtract(
      x = object$output$SplitModels$Genotype_Sex.LifeStage,
      variable = CombineLevels(
        paste0(Labels$Sex$Sex, Labels$Sex$Female),
        paste0(Labels$LifeStage$LifeStage, Labels$LifeStage$Early),
        Labels$Genotype$Levels,
        debug = debug
      ),
      anova = FALSE,
      debug = debug
    ),
    "LifeStageSexGenotype FvEvKO effect size" = object$output$"Effect sizes"$"Genotype_Female Early",
    # 2.
    "LifeStageSexGenotype MvEvKO estimate" = modelSummaryPvalueExtract(
      x = object$output$SplitModels$Genotype_Sex.LifeStage,
      variable = CombineLevels(
        paste0(Labels$Sex$Sex, Labels$Sex$Male),
        paste0(Labels$LifeStage$LifeStage, Labels$LifeStage$Early),
        Labels$Genotype$Levels,
        debug = debug
      ),
      anova = FALSE,
      what = "Value",
      debug = debug,
      ci_display = TRUE
    ),
    "LifeStageSexGenotype MvEvKO standard error" = modelSummaryPvalueExtract(
      x = object$output$SplitModels$Genotype_Sex.LifeStage,
      variable = CombineLevels(
        paste0(Labels$Sex$Sex, Labels$Sex$Male),
        paste0(Labels$LifeStage$LifeStage, Labels$LifeStage$Early),
        Labels$Genotype$Levels,
        debug = debug
      ),
      anova = FALSE,
      what = "Std.Error",
      debug = debug
    ),
    "LifeStageSexGenotype MvEvKO p-value" = modelSummaryPvalueExtract(
      x = object$output$SplitModels$Genotype_Sex.LifeStage,
      variable = CombineLevels(
        paste0(Labels$Sex$Sex, Labels$Sex$Male),
        paste0(Labels$LifeStage$LifeStage, Labels$LifeStage$Early),
        Labels$Genotype$Levels,
        debug = debug
      ),
      anova = FALSE,
      debug = debug
    ),
    "LifeStageSexGenotype MvEvKO effect size" = object$output$"Effect sizes"$"Genotype_Male Early",
    # 3.
    "LifeStageSexGenotype FvLvKO estimate" = modelSummaryPvalueExtract(
      x = object$output$SplitModels$Genotype_Sex.LifeStage,
      variable = CombineLevels(
        paste0(Labels$Sex$Sex, Labels$Sex$Female),
        paste0(Labels$LifeStage$LifeStage, Labels$LifeStage$Late),
        Labels$Genotype$Levels,
        debug = debug
      ),
      anova = FALSE,
      what = "Value",
      debug = debug,
      ci_display = TRUE
    ),
    "LifeStageSexGenotype FvLvKO standard error" = modelSummaryPvalueExtract(
      x = object$output$SplitModels$Genotype_Sex.LifeStage,
      variable = CombineLevels(
        paste0(Labels$Sex$Sex, Labels$Sex$Female),
        paste0(Labels$LifeStage$LifeStage, Labels$LifeStage$Late),
        Labels$Genotype$Levels,
        debug = debug
      ),
      anova = FALSE,
      what = "Std.Error",
      debug = debug
    ),
    "LifeStageSexGenotype FvLvKO p-value" = modelSummaryPvalueExtract(
      x = object$output$SplitModels$Genotype_Sex.LifeStage,
      variable = CombineLevels(
        paste0(Labels$Sex$Sex, Labels$Sex$Female),
        paste0(Labels$LifeStage$LifeStage, Labels$LifeStage$Late),
        Labels$Genotype$Levels,
        debug = debug
      ),
      anova = FALSE,
      debug = debug
    ),
    "LifeStageSexGenotype FvLvKO effect size" = object$output$"Effect sizes"$"Genotype_Female Late",
    # 4.
    "LifeStageSexGenotype MvLvKO estimate" = modelSummaryPvalueExtract(
      x = object$output$SplitModels$Genotype_Sex.LifeStage,
      variable = CombineLevels(
        paste0(Labels$Sex$Sex, Labels$Sex$Male),
        paste0(Labels$LifeStage$LifeStage, Labels$LifeStage$Late),
        Labels$Genotype$Levels,
        debug = debug
      ),
      anova = FALSE,
      what = "Value",
      debug = debug,
      ci_display = TRUE
    ),
    "LifeStageSexGenotype MvLvKO standard error" = modelSummaryPvalueExtract(
      x = object$output$SplitModels$Genotype_Sex.LifeStage,
      variable = CombineLevels(
        paste0(Labels$Sex$Sex, Labels$Sex$Male),
        paste0(Labels$LifeStage$LifeStage, Labels$LifeStage$Late),
        Labels$Genotype$Levels,
        debug = debug
      ),
      anova = FALSE,
      what = "Std.Error",
      debug = debug
    ),
    "LifeStageSexGenotype MvLvKO p-value" = modelSummaryPvalueExtract(
      x = object$output$SplitModels$Genotype_Sex.LifeStage,
      variable = CombineLevels(
        paste0(Labels$Sex$Sex, Labels$Sex$Male),
        paste0(Labels$LifeStage$LifeStage, Labels$LifeStage$Late),
        Labels$Genotype$Levels,
        debug = debug
      ),
      anova = FALSE,
      debug = debug
    ),
    "LifeStageSexGenotype MvLvKO effect size" = object$output$"Effect sizes"$"Genotype_Male Late",
    ################
    "Classification tag" = NULL,
    "Transformation" = NULL,
    "Additional information" = addInfo
  )

  return(OpenStatsReportMM0)
}