prolfqua 1.3.6
  • Reference
  • Articles
    • Comparing Two Groups with prolfqua
    • Getting Started, Data Import, Creating prolfqua Configurations
    • Modelling dataset with two Factors
    • Quality Control & Sample Size Estimation
    • QC and Sample Size Estimation
    • Simulate Peptide level Data
    • Impute

Summarize modelling and error reporting

Source: R/tidyMS_R6Model.R
model_summary.Rd

Summarize modelling and error reporting

model_summary(mod)

Arguments

mod

model table see build_model

See also

Other modelling: Contrasts, ContrastsMissing, ContrastsModerated, ContrastsPlotter, ContrastsProDA, ContrastsROPECA, ContrastsTable, INTERNAL_FUNCTIONS_BY_FAMILY, LR_test(), 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(), 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()

Contents

Developed by Witold Wolski.

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