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Bernoulli distribution with logit parametrization

logistic_bin_outcome.Rd

Bernoulli distribution with logit parametrization

Usage

logistic_bin_outcome(binary_var, baseline_prior, weight_var = "")

Arguments

binary_var

character. Name of binary (1/0 or TRUE/FALSE) outcome variable in the model matrix

baseline_prior

Prior. Object of class Prior specifying prior distribution for the baseline outcome. See Details for more information.

weight_var

character. Optional name of variable in model matrix for weighting the log likelihood.

Value

Object of class LogisticBinaryOutcome.

Details

Baseline Prior

The baseline_prior argument specifies the prior distribution for the baseline log odds. The interpretation of the baseline_prior differs slightly between methods selected in borrowing_details():

  • 'BDB': the baseline_prior for Bayesian Dynamic Borrowing refers to the log odds of the external control arm.

  • 'Full borrowing' or 'No borrowing': the baseline_prior for these borrowing methods refers to the log odds for the internal control arm.

See also

Other outcome models: exp_surv_dist(), weib_ph_surv_dist()

Examples

lg <- logistic_bin_outcome(
  binary_var = "response",
  baseline_prior = normal_prior(0, 1000)
)