Bayesian hierarchical linear model and options with censoring — bhm • tumr

Bayesian hierarchical linear model and options with censoring

Usage

bhm(data, cens = NULL, diagnostics = FALSE, return_fit = TRUE, ...)

Arguments

data: data.frame with columns ID, Day, Volume, Treatment
cens: Optional numeric scalar. If provided, observations with log1p(Volume) <= cens are treated as left-censored at cens. Set cens = NULL (default) to fit the non-censored model.
diagnostics: logical; whether to return diagnostic summary
return_fit: logical; whether to return the CmdStan fit object
...: further arguments

Value

A list of posterior summaries (and optionally diagnostics / fit)

Examples

if (FALSE) { # \dontrun{
data(melanoma2)
fit <- bhm(melanoma2)
fit_cens <- bhm(melanoma2, cens = log1p(10))
} # }