LR_test: Likelihood ratio test

In wolski/prolfqua: Proteomics Label Free Quantification

Likelihood ratio test

Description

Likelihood ratio test

Usage

LR_test(
  modelProteinF,
  modelName,
  modelProteinF_Int,
  modelName_Int,
  subject_Id = "protein_Id",
  path = NULL
)

Arguments

modelProteinF	table with models (see build model)
modelName	name of model
modelProteinF_Int	reduced model
modelName_Int	name of reduced model
subject_Id	subject id typically Assession or protein_Id
path	default NULL, set to a directory if you need to write diagnostic plots.

See Also

Other modelling: Contrasts, ContrastsMissing, ContrastsModerated, ContrastsPlotter, ContrastsProDA, ContrastsROPECA, ContrastsTable, INTERNAL_FUNCTIONS_BY_FAMILY, Model, build_model(), build_models(), contrasts_fisher_exact(), get_anova_df(), get_complete_model_fit(), get_p_values_pbeta(), isSingular_lm(), linfct_all_possible_contrasts(), linfct_factors_contrasts(), linfct_from_model(), linfct_matrix_contrasts(), make_model(), merge_contrasts_results(), model_analyse(), model_summary(), moderated_p_limma(), moderated_p_limma_long(), my_contest(), my_contrast(), my_contrast_V1(), my_contrast_V2(), my_glht(), pivot_model_contrasts_2_Wide(), plot_lmer_model_and_data(), plot_lmer_peptide_noRandom(), plot_lmer_peptide_predictions(), plot_lmer_predicted_interactions(), strategy_lmer(), summary_ROPECA_median_p.scaled()

Examples

data_Yeast2Factor <- prolfqua::prolfqua_data("data_Yeast2Factor")
pMerged <- LFQData$new(data_Yeast2Factor$data, prolfqua::old2new(data_Yeast2Factor$config))

pMerged$data$Run_ID <- as.numeric(pMerged$data$Run_ID)
pMerged$config$table$get_response()
pMerged$factors()

formula_condition_and_Batches <-
  prolfqua::strategy_lm("transformedIntensity ~ condition_ + batch_")
modCB <- prolfqua::build_model(
  pMerged$data,
  formula_condition_and_Batches,
  subject_Id = pMerged$config$table$hierarchy_keys() )

formula_condition <-
  prolfqua::strategy_lm("transformedIntensity ~ condition_")
modC <- prolfqua::build_model(
  pMerged$data,
  formula_condition,
  subject_Id = pMerged$config$table$hierarchy_keys() )

tmp <- LR_test(modCB$modelDF, "modCB", modC$modelDF, "modB")
hist(tmp$likelihood_ratio_test.pValue)

wolski/prolfqua documentation built on May 12, 2024, 10:16 p.m.