View source: R/tidyMS_R6Model.R
LR_test | R Documentation |
Likelihood ratio test
LR_test(
modelProteinF,
modelName,
modelProteinF_Int,
modelName_Int,
subject_Id = "protein_Id",
path = NULL
)
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. |
Other modelling:
Contrasts
,
ContrastsMissing
,
ContrastsModerated
,
ContrastsPlotter
,
ContrastsProDA
,
ContrastsROPECA
,
ContrastsTable
,
INTERNAL_FUNCTIONS_BY_FAMILY
,
Model
,
build_model()
,
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()
,
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_peptide_predictions()
,
sim_build_models_lm()
,
sim_build_models_lmer()
,
sim_make_model_lm()
,
sim_make_model_lmer()
,
strategy_lmer()
,
summary_ROPECA_median_p.scaled()
data_2Factor <- prolfqua::sim_lfq_data_2Factor_config(
Nprot = 200,
with_missing = TRUE,
weight_missing = 2)
pMerged <- LFQData$new(data_2Factor$data, data_2Factor$config)
pMerged$config$table$get_response()
pMerged$factors()
formula_condition_and_Batches <-
prolfqua::strategy_lm("abundance ~ Treatment + Background")
modCB <- prolfqua::build_model(
pMerged$data,
formula_condition_and_Batches,
subject_Id = pMerged$config$table$hierarchy_keys() )
formula_condition <-
prolfqua::strategy_lm("abundance ~ Treatment")
modC <- prolfqua::build_model(
pMerged$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)
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