get linfct from model
See also
Other modelling:
AnovaExtractor,
Contrasts,
ContrastsDEqMSFacade,
ContrastsDEqMSVoomFacade,
ContrastsFirth,
ContrastsFirthFacade,
ContrastsLMFacade,
ContrastsLMImputeFacade,
ContrastsLMMissingFacade,
ContrastsLimma,
ContrastsLimmaFacade,
ContrastsLimmaImputeFacade,
ContrastsLimmaVoomFacade,
ContrastsLimmaVoomImputeFacade,
ContrastsLimpaFacade,
ContrastsLmerFacade,
ContrastsMissing,
ContrastsModerated,
ContrastsModeratedDEqMS,
ContrastsPlotter,
ContrastsRLMFacade,
ContrastsROPECA,
ContrastsROPECAFacade,
ContrastsTable,
INTERNAL_FUNCTIONS_BY_FAMILY,
LR_test(),
Model,
ModelFirth,
ModelLimma,
StrategyLM,
StrategyLimma,
StrategyLimpa,
StrategyLmer,
StrategyLogistf,
StrategyRLM,
build_contrast_analysis(),
build_model(),
build_model_glm_peptide(),
build_model_glm_protein(),
build_model_impute(),
build_model_limma(),
build_model_limma_impute(),
build_model_limma_voom(),
build_model_limma_voom_impute(),
build_model_limpa(),
build_model_logistf(),
compute_borrowed_variance(),
compute_borrowed_variance_limma(),
compute_contrast(),
compute_lmer_contrast(),
contrasts_fisher_exact(),
get_anova_df(),
get_complete_model_fit(),
get_p_values_pbeta(),
group_label(),
impute_refit_singular(),
is_singular_lm(),
linfct_all_possible_contrasts(),
linfct_factors_contrasts(),
linfct_matrix_contrasts(),
merge_contrasts_results(),
model_analyse(),
model_summary(),
moderated_p_deqms(),
moderated_p_deqms_long(),
moderated_p_limma(),
moderated_p_limma_long(),
new_lm_imputed(),
pivot_model_contrasts_to_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_limpa(),
strategy_logistf(),
summary_ROPECA_median_p.scaled()
Examples
m <- sim_make_model_lm("factors")
#> creating sampleName from file_name column
#> completing cases
#> completing cases done
#> setup done
linfct <- linfct_from_model(m, as_list = TRUE)
linfct$linfct_factors
#> (Intercept) TreatmentB BackgroundZ
#> BackgroundX 1 0.5 0.0
#> BackgroundZ 1 0.5 1.0
#> TreatmentA 1 0.0 0.5
#> TreatmentB 1 1.0 0.5
linfct$linfct_interactions
#> (Intercept) TreatmentB BackgroundZ
#> TreatmentA:BackgroundX 1 0 0
#> TreatmentA:BackgroundZ 1 0 1
#> TreatmentB:BackgroundX 1 1 0
#> TreatmentB:BackgroundZ 1 1 1
lf <- matrix(
c(1, 1, 1, 1, 0.5, 0.5, 0, 1, 0, 1, 0.5, 0.5),
nrow = 4,
byrow = FALSE,
dimnames = list(c("BackgroundX", "BackgroundZ", "TreatmentA", "TreatmentB"),
c("(Intercept)", "TreatmentB", "BackgroundZ"))
)
stopifnot(lf == linfct$linfct_factors)
m <- sim_make_model_lm("interaction")
#> creating sampleName from file_name column
#> completing cases
#> completing cases done
#> setup done
linfct <- linfct_from_model(m)
m <- lm(Petal.Width ~ Species, data = iris)
linfct_from_model(m)
#> $linfct_factors
#> (Intercept) Speciesversicolor Speciesvirginica
#> Speciessetosa 1 0 0
#> Speciesversicolor 1 1 0
#> Speciesvirginica 1 0 1
#>
#> $linfct_interactions
#> (Intercept) Speciesversicolor Speciesvirginica
#> Speciessetosa 1 0 0
#> Speciesversicolor 1 1 0
#> Speciesvirginica 1 0 1
#>
xx <- data.frame( Y = 1:10 , Condition = c(rep("a",5), rep("b",5)) )
m <- lm(Y ~ Condition, data = xx)
linfct_from_model(m)
#> $linfct_factors
#> (Intercept) Conditionb
#> Conditiona 1 0
#> Conditionb 1 1
#>
#> $linfct_interactions
#> (Intercept) Conditionb
#> Conditiona 1 0
#> Conditionb 1 1
#>
xx <- data.frame( Y = 1:10 , Condition = c(rep("a",5), rep("b.b",5)) )
m <- lm(Y ~ Condition, data = xx)
linfct_from_model(m)
#> $linfct_factors
#> (Intercept) Conditionb.b
#> Conditiona 1 0
#> Conditionb.b 1 1
#>
#> $linfct_interactions
#> (Intercept) Conditionb.b
#> Conditiona 1 0
#> Conditionb.b 1 1
#>
xx <- data.frame( Y = 1:10 , Condition = c(rep("a",5), rep("ab",5)) )
m <- lm(Y ~ Condition, data = xx)
linfct_from_model(m)
#> $linfct_factors
#> (Intercept) Conditionab
#> Conditiona 1 0
#> Conditionab 1 1
#>
#> $linfct_interactions
#> (Intercept) Conditionab
#> Conditiona 1 0
#> Conditionab 1 1
#>