build dataframe with models for testing

Usage

sim_build_models_logistf(
  model = c("parallel2", "parallel3", "factors", "interaction"),
  Nprot = 10,
  with_missing = TRUE,
  weight_missing = 1,
  peptide = FALSE
)

Other modelling: AnovaExtractor, Contrasts, ContrastsDEqMSFacade, ContrastsDEqMSVoomFacade, ContrastsFirth, ContrastsFirthFacade, ContrastsLMFacade, ContrastsLMImputeFacade, ContrastsLMMissingFacade, ContrastsLimma, ContrastsLimmaFacade, ContrastsLimmaImputeFacade, ContrastsLimmaVoomFacade, ContrastsLimmaVoomImputeFacade, ContrastsLimpaFacade, ContrastsLmerFacade, ContrastsMissing, ContrastsModerated, ContrastsModeratedDEqMS, ContrastsPlotter, ContrastsRLMFacade, ContrastsROPECA, ContrastsROPECAFacade, ContrastsTable, INTERNAL_FUNCTIONS_BY_FAMILY, LR_test(), Model, ModelFirth, ModelLimma, StrategyLM, StrategyLimma, StrategyLimpa, StrategyLmer, StrategyLogistf, StrategyRLM, build_contrast_analysis(), build_model(), build_model_glm_peptide(), build_model_glm_protein(), build_model_impute(), build_model_limma(), build_model_limma_impute(), build_model_limma_voom(), build_model_limma_voom_impute(), build_model_limpa(), build_model_logistf(), compute_borrowed_variance(), compute_borrowed_variance_limma(), compute_contrast(), compute_lmer_contrast(), contrasts_fisher_exact(), get_anova_df(), get_complete_model_fit(), get_p_values_pbeta(), group_label(), impute_refit_singular(), isSingular_lm(), linfct_all_possible_contrasts(), linfct_factors_contrasts(), linfct_from_model(), linfct_matrix_contrasts(), merge_contrasts_results(), model_analyse(), model_summary(), moderated_p_deqms(), moderated_p_deqms_long(), moderated_p_limma(), moderated_p_limma_long(), new_lm_imputed(), pivot_model_contrasts_2_Wide(), plot_lmer_peptide_predictions(), sim_build_models_lm(), sim_build_models_lmer(), sim_make_model_lm(), sim_make_model_lmer(), strategy_limma(), strategy_limpa(), strategy_logistf(), summary_ROPECA_median_p.scaled()

Examples

modi <- sim_build_models_logistf(model = "interaction", weight_missing = 1)
#> creating sampleName from file_name column
#> completing cases
#> completing cases done
#> setup done
#> completing cases
#> Joining with `by = join_by(protein_Id)`
stopifnot(dim(modi$modelDF) == c(10,9))
mod2 <- sim_build_models_logistf(model = "parallel2", weight_missing = 1)
#> creating sampleName from file_name column
#> completing cases
#> completing cases done
#> setup done
#> completing cases
#> Joining with `by = join_by(protein_Id)`
mod2$modelDF$linear_model[[1]]
#> NULL
mod3 <- sim_build_models_logistf(model = "parallel3", weight_missing = 1)
#> creating sampleName from file_name column
#> completing cases
#> completing cases done
#> setup done
#> completing cases
#> Joining with `by = join_by(protein_Id)`
modf <- sim_build_models_logistf(model = "factors", weight_missing = 1)
#> creating sampleName from file_name column
#> completing cases
#> completing cases done
#> setup done
#> completing cases
#> Joining with `by = join_by(protein_Id)`

mod3 <- sim_build_models_logistf(model = "parallel3", weight_missing = 1, peptide=TRUE)
#> creating sampleName from file_name column
#> completing cases
#> completing cases done
#> setup done
#> completing cases
#> Joining with `by = join_by(protein_Id)`
#> Joining with `by = join_by(protein_Id)`
modf <- sim_build_models_logistf(model = "factors", weight_missing = 1, peptide=TRUE)
#> Warning: Unknown or uninitialised column: `nr_peptides`.
#> creating sampleName from file_name column
#> completing cases
#> completing cases done
#> setup done
#> completing cases
#> Joining with `by = join_by(protein_Id)`
#> Joining with `by = join_by(protein_Id)`

build dataframe with models for testing

Usage

See also

Examples