perform_lrt performs the likelihood ratio test to compare two list of marginal models.
Arguments
- alter_marginal
A list of marginal models from the alternative hypothesis.
- null_marginal
A list of marginal models from the null hypothesis. It must be strictly nested in the alternative model.
Details
The function takes two lists of marginal models (by default, the first list is the alternative and the second is the null)
from fit_marginal. Note that LRT only makes sense for NESTED models. This can be quite tricky if you use penalized-splines (e.g., for trajectory data).
Examples
data(example_sce)
my_data <- construct_data(
sce = example_sce,
assay_use = "counts",
celltype = "cell_type",
pseudotime = "pseudotime",
spatial = NULL,
other_covariates = NULL,
corr_by = "cell_type"
)
my_data2 <- construct_data(
sce = example_sce,
assay_use = "counts",
celltype = "cell_type",
pseudotime = "pseudotime",
spatial = NULL,
other_covariates = NULL,
corr_by = "pseudotime",
ncell = 10000
)
#> fitting ...
#>
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my_marginal1 <- fit_marginal(
data = my_data,
mu_formula = "1",
sigma_formula = "1",
family_use = "nb",
n_cores = 1,
usebam = FALSE
)
my_marginal2 <- fit_marginal(
data = my_data,
mu_formula = "s(pseudotime, bs = 'cr', k = 10)",
sigma_formula = "1",
family_use = "nb",
n_cores = 1,
usebam = FALSE
)
my_fit1 <- lapply(my_marginal1, function(x)x$fit)
my_fit2 <- lapply(my_marginal2, function(x)x$fit)
my_pvalue <- perform_lrt(my_fit2, my_fit1)