apply multcomp::glht method to linfct
my_glht(model, linfct, sep = TRUE)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(),
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()
mb <- sim_make_model_lm( "interaction")
#> creating sampleName from fileName column
#> completing cases
#> Joining with `by = join_by(protein_Id)`
linfct <- linfct_from_model(mb)
names(linfct)
#> [1] "linfct_factors" "linfct_interactions"
my_glht(mb, linfct$linfct_factors)
#> # A tibble: 4 × 10
#> contrast null.value estimate std.error statistic adj.p.value conf.low
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 BackgroundX 0 18.6 0.322 57.8 4.44e-16 17.9
#> 2 BackgroundZ 0 18.2 0.322 56.4 6.66e-16 17.5
#> 3 TreatmentA 0 18.8 0.322 58.2 4.44e-16 18.1
#> 4 TreatmentB 0 18.1 0.322 56.1 6.66e-16 17.4
#> # ℹ 3 more variables: conf.high <dbl>, df <int>, sigma <dbl>
m <- sim_make_model_lm( "factors")
#> creating sampleName from fileName column
#> completing cases
#> Joining with `by = join_by(protein_Id)`
linfct <- linfct_from_model(m)$linfct_factors
my_glht(m, linfct)
#> # A tibble: 4 × 10
#> contrast null.value estimate std.error statistic adj.p.value conf.low
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 BackgroundX 0 18.6 0.551 33.8 4.62e-14 17.4
#> 2 BackgroundZ 0 18.2 0.551 33.0 6.29e-14 17.0
#> 3 TreatmentA 0 18.8 0.551 34.1 4.26e-14 17.6
#> 4 TreatmentB 0 18.1 0.551 32.8 6.83e-14 16.9
#> # ℹ 3 more variables: conf.high <dbl>, df <int>, sigma <dbl>