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Quasibinomial detection-count strategy

Source: R/BinomialNested.R
StrategyBinomial.Rd

Quasibinomial detection-count strategy

Quasibinomial detection-count strategy

Value

An R6 class generator.

Details

Fits detected and undetected child-feature counts for each parent feature using glm with a quasibinomial family. The symmetric pseudo-count stabilizes fits under complete separation; it is not equivalent to Firth's bias-reducing penalty.

Public fields

formula

quasibinomial model formula

model_name

model identity

report_columns

result columns supported by the strategy

is_mixed

always FALSE

anova_df

ANOVA extractor

prior_count

symmetric pseudo-count added to both outcomes

Methods

Public methods

Method new()

Create a quasibinomial count strategy.

Usage

StrategyBinomial$new(
  modelstr,
  prior_count = 0.1,
  model_name = "binomial_nested",
  report_columns = c("statistic", "p.value", "p.value.adjusted", "moderated.p.value",
    "moderated.p.value.adjusted")
)

Arguments

modelstr

right-hand-side model formula, for example "~ group_"

prior_count

non-negative symmetric pseudo-count

model_name

model identity

report_columns

result columns supported by the strategy

Method model_fun()

Fit one parent's detection counts.

Usage

StrategyBinomial$model_fun(x, pb, get_formula = FALSE)

Arguments

x

parent-by-sample count data

pb

optional progress reporter

get_formula

if TRUE, return the model formula without fitting

Method isSingular()

Check whether the model is singular.

Usage

StrategyBinomial$isSingular(model)

Arguments

model

fitted quasibinomial model

Method contrast_fun()

Compute linear contrasts.

Usage

StrategyBinomial$contrast_fun(...)

Arguments

...

passed to compute_contrast

Method df_residual()

Return residual degrees of freedom.

Usage

StrategyBinomial$df_residual(model)

Arguments

model

fitted quasibinomial model

Method sigma()

Return the Pearson residual scale used by vcov().

Usage

StrategyBinomial$sigma(model)

Arguments

model

fitted quasibinomial model

Method clone()

The objects of this class are cloneable with this method.

Usage

StrategyBinomial$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

dat <- data.frame(
  group_ = factor(rep(c("A", "B"), each = 4)),
  detected = c(1, 2, 1, 3, 4, 5, 3, 5),
  undetected = c(4, 3, 4, 2, 1, 0, 2, 0)
)
strategy <- StrategyBinomial$new("~ group_")
fit <- strategy$model_fun(dat)
coefficients(fit)
#> (Intercept)     group_B 
#>  -0.5937747   2.2264695