View source: R/tidyMS_R6_Modelling.R
linfct_matrix_contrasts | R Documentation |
linfct_matrix_contrasts
linfct_matrix_contrasts(linfct, contrasts, p.message = FALSE)
linfct |
linear functions as created by linfct_from_model |
p.message |
print messages default FALSE |
contrast |
contrasts to determine linear functions for |
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()
,
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_lm()
,
sim_build_models_lmer()
,
sim_make_model_lm()
,
sim_make_model_lmer()
,
strategy_lmer()
,
summary_ROPECA_median_p.scaled()
m <- sim_make_model_lm( "factors")
Contr <- c("TreatmentA_vs_B" = "TreatmentA - TreatmentB",
"BackgroundX_vs_Z" = "BackgroundX - BackgroundZ",
"IntoflintoA" = "`TreatmentA:BackgroundX` - `TreatmentA:BackgroundZ`",
"IntoflintoB" = "`TreatmentB:BackgroundX` - `TreatmentB:BackgroundZ`",
"IntoflintoX" = "`TreatmentA:BackgroundX` - `TreatmentB:BackgroundX`",
"IntoflintoZ" = "`TreatmentA:BackgroundZ` - `TreatmentB:BackgroundZ`",
"interactXZ" = "IntoflintoX - IntoflintoZ",
"interactAB" = "IntoflintoA - IntoflintoB"
)
linfct <- linfct_from_model(m, as_list = FALSE)
x <- linfct_matrix_contrasts(linfct, Contr )
stopifnot(sum(x["interactXZ",]) == 0 )
stopifnot(sum(x["interactAB",]) == 0 )
m <- sim_make_model_lm( "interaction")
linfct <- linfct_from_model(m, as_list = FALSE)
x <- linfct_matrix_contrasts(linfct, Contr )
stopifnot(sum(x["interactXZ",]) ==1 )
stopifnot(sum(x["interactAB",]) ==1 )
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