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Summarize a generated dataset and its simulation mechanism

Source: R/describe_data_generation.R
describe_generation.Rd

Given one element returned by load_recipe_sets() (a list with data and a rich meta list), this builds tidy tables describing the data-generating process: model family, baseline parameters, linear predictor coefficients (intercept / treatment / covariates), treatment assignment, and censoring.

Usage

describe_generation(set)

Arguments

set

A single element from load_recipe_sets(), i.e. list(data=<df>, meta=<list>).

Value

A list of data frames:

  • header: n, L (analysis horizon; stored as attr "tau"), model, event_rate, achieved_censoring.

  • baseline: flattened baseline parameters.

  • effects: coefficients for intercept/treatment and covariates (and formula terms if used).

  • treatment: assignment mechanism and knobs.

  • censoring: censoring mode/target/admin time.

  • covariates: each generated covariate with its distribution and parameters.

  • files: paths to on-disk files (csv/rds/rdata) when available.

Examples

if (FALSE) { # \dontrun{
sets <- load_recipe_sets("checks/manifest.rds")
spec <- describe_generation(sets[[1]])
spec$header
spec$baseline
spec$effects
spec$treatment
spec$censoring
spec$covariates
spec$files
} # }