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build_model_logistf

Source: R/logistf.R
build_model_logistf.Rd

build_model_logistf

Usage

build_model_logistf(data, formula)

See also

Other modelling: Contrasts, ContrastsFirth, ContrastsLimma, ContrastsMissing, ContrastsModerated, ContrastsModeratedDEqMS, ContrastsPlotter, ContrastsProDA, ContrastsROPECA, ContrastsTable, INTERNAL_FUNCTIONS_BY_FAMILY, LR_test(), Model, ModelFirth, ModelLimma, build_model(), build_model_limma(), contrasts_fisher_exact(), get_anova_df(), get_complete_model_fit(), get_p_values_pbeta(), group_label(), 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(), 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_build_models_logistf(), sim_make_model_lm(), sim_make_model_lmer(), strategy_limma(), strategy_logistf(), summary_ROPECA_median_p.scaled()

Examples

istar <- prolfqua::sim_lfq_data_peptide_config(Nprot = 10, with_missing = TRUE,
  weight_missing = 0.5, seed = 3)
#> creating sampleName from fileName column
#> completing cases
#> completing cases done
#> setup done
istar$data <- prolfqua::encode_bin_resp(istar$data, istar$config)
#> completing cases
tmp <- LFQData$new(istar$data, istar$config)
formula <- paste0(tmp$config$bin_resp , "~ group_")
xx2 <- build_model_logistf(tmp, formula)
#> Joining with `by = join_by(protein_Id)`
#> Joining with `by = join_by(protein_Id)`
#> Joining with `by = join_by(protein_Id)`
#> Joining with `by = join_by(protein_Id)`

istar <- prolfqua::sim_lfq_data_protein_config(Nprot = 10, with_missing = TRUE,
  weight_missing = 0.5, seed = 3)
#> creating sampleName from fileName column
#> completing cases
#> completing cases done
#> setup done
istar$data <- prolfqua::encode_bin_resp(istar$data, istar$config)
#> completing cases
tmp <- LFQData$new(istar$data, istar$config)
formula <- paste0(tmp$config$bin_resp , "~ group_")
xx <- build_model_logistf(tmp, formula)
#> Joining with `by = join_by(protein_Id)`
#> Joining with `by = join_by(protein_Id)`



m <- xx$models$models1$modelDF$linear_model[[1]]
linfct <- linfct_from_model(m)
linfct_all_possible_contrasts(linfct$linfct_factors)
#>                      (Intercept) group_B group_Ctrl
#> group_A - group_B              0      -1          0
#> group_A - group_Ctrl           0       0         -1
#> group_B - group_Ctrl           0       1         -1
x <- prolfqua::linfct_all_possible_contrasts(linfct$linfct_interactions)
linfct <- linfct_factors_contrasts(m)

m <- xx2$models$models2$modelDF$linear_model[[1]]
linfct <- linfct_from_model(m)
x <- linfct_all_possible_contrasts(linfct$linfct_factors)
x <- prolfqua::linfct_all_possible_contrasts(linfct$linfct_interactions)
linfct <- linfct_factors_contrasts(m)