build dataframe with models for testing
sim_build_models_lm(
model = c("parallel2", "parallel3", "factors", "interaction"),
Nprot = 10,
with_missing = TRUE,
weight_missing = 1
)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(),
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_lmer(),
sim_make_model_lm(),
sim_make_model_lmer(),
strategy_lmer(),
summary_ROPECA_median_p.scaled()
modi <- sim_build_models_lm(model = "interaction", weight_missing = 1)
#> creating sampleName from fileName column
#> completing cases
#> Joining with `by = join_by(protein_Id)`
stopifnot(dim(modi$modelDF) == c(10,9))
mod2 <- sim_build_models_lm(model = "parallel2", weight_missing = 1)
#> creating sampleName from fileName column
#> completing cases
#> Joining with `by = join_by(protein_Id)`
mod2$modelDF$linear_model[[1]]
#>
#> Call:
#> lm(formula = formula, data = x)
#>
#> Coefficients:
#> (Intercept) TreatmentB
#> 20.321 4.158
#>
mod3 <- sim_build_models_lm(model = "parallel3", weight_missing = 1)
#> creating sampleName from fileName column
#> completing cases
#> Joining with `by = join_by(protein_Id)`
modf <- sim_build_models_lm(model = "factors", weight_missing = 1)
#> creating sampleName from fileName column
#> completing cases
#> Joining with `by = join_by(protein_Id)`