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Bootstrap confidence interval for heritability

confint.heritable.Rd

Computes a confidence interval for a heritability estimate using parametric bootstrap of the underlying mixed model. Parallel computing is supported through boot::boot()

Usage

# S3 method for class 'heritable'
confint(
  object,
  parm = NULL,
  level = 0.95,
  B = 100,
  random_effect = c("resample", "conditional"),
  type = c("basic", "norm", "perc"),
  return_model = TRUE,
  seed = NULL,
  ...
)

Arguments

object

A heritability object returned by H2() (broad-sense) h2() (narrow-sense). The object must store the fitted model as an attribute.

parm

a specification of which methods are to be given confidence intervals, either a vector of numbers or a vector of names. If missing, all methods are considered.

level

Confidence level.

B

Integer. Number of bootstrap replicates.

random_effect

Character. Strategy for handling random effects.

"resample"

Resample random effects to propagate uncertainty.

"conditional"

Condition on estimated random effects.

type

Character. Bootstrap interval type; one of "basic", "norm", or "perc".

return_model

Logical. Whether to return to the boot object.

seed

Optional random seed.

...

Additional arguments passed to the bootstrap routine. Check boot::boot(), as well as the examples below for parallel computation

Value

A matrix of confidence intervals.

See also

boot::boot(), H2()

Examples

if (FALSE) { # \dontrun{
  lettuce_subset <- lettuce_phenotypes |> subset(loc == "L2")
  lettuce_asreml <- asreml(
    fixed = y ~ rep * pseudo_var1,
    random = ~gen,
    sparse = ~pseudo_var2,
    data = lettuce_subset,
    trace = FALSE
  )

  my_H2 <- H2(lettuce_asreml, "gen", c("Cullis", "Standard"))

  my_ci <- confint(my_H2)

  # Get bootstrap model
  boot_mod <- attr(my_ci, "boot_mod")
  boot_mod$t # Check bootstrap statistics

  # Parallel computing (On Windows)
  # Note that for asreml, `ncpus` can't be larger than the number of asreml
  # license available
  confint(my_H2, parallel = "snow", ncpus = 3)

  # Parallel computing (On non-Windows)
  confint(my_H2, parallel = "multicore", ncpus = 3)

} # }