Stepwise covariate modelling for exposure-response TTE models

Usage

ertte_scm_forward(mod, candidates, threshold = 0.01, seed = NULL)

ertte_scm_backward(mod, candidates, threshold = 0.001, seed = NULL)

ertte_scm_history(mod)

Arguments

mod: An ertte model object
candidates: Character vector with list of candidate terms
threshold: Threshold to test against
seed: Optional seed to control order of term tests

Value

For ertte_scm_forward() and ertte_scm_backward(), the updated ertte model is returned, with the SCM history log updated internally. For ertte_scm_history(), a data frame is returned containing the SCM history log

Details

Terms are compared with a likelihood-ratio Chi-squared test (stats::anova() on nested survreg fits) – unlike the companion erglm package's SCM, there's no family-dependent choice of test here, since a survreg model's likelihood ratio test doesn't vary by distribution.

seed exists as a safety measure against run-to-run variation in the order candidate terms are tested within a step (sample(), shuffled before testing one at a time). Model fitting itself (survival::survreg()) is deterministic given a starting formula, so seed only matters in the (essentially measure-zero) case of an exact p-value tie between competing candidates within a step – see the companion erglm package's equivalent documentation for the full rationale, which applies unchanged here.

If a candidate term is aliased (perfectly collinear) with a term already in the model, stats::anova() reports an NA p-value for it. That candidate is skipped for the step (with a warning) rather than being selected or crashing the search.

candidates is validated up front: every element must be parseable as a formula and name exactly one covariate term (e.g. "sex", not "sex + dose" or "not a formula").

Examples

mod0 <- ertte_model(survival::Surv(time, event) ~ aucss, ertte_data)
mod1 <- ertte_scm_forward(mod0, candidates = c("sex", "dose"))
ertte_scm_history(mod1)
#> # A tibble: 4 × 11
#>   iteration attempt step       action term_tested model_tested   model_converged
#>       <int>   <int> <chr>      <chr>  <chr>       <chr>          <lgl>          
#> 1         0       0 base model NA     NA          survival::Sur… TRUE           
#> 2         1       1 forward    add    ~sex        survival::Sur… TRUE           
#> 3         1       2 forward    add    ~dose       survival::Sur… TRUE           
#> 4         2       3 forward    add    ~dose       survival::Sur… TRUE           
#> # ℹ 4 more variables: term_p_value <dbl>, model_aic <dbl>, model_bic <dbl>,
#> #   model_updated <int>

mod2 <- ertte_model(survival::Surv(time, event) ~ aucss + sex + dose, ertte_data)
mod3 <- ertte_scm_backward(mod2, candidates = c("sex", "dose"))
ertte_scm_history(mod3)
#> # A tibble: 4 × 11
#>   iteration attempt step       action term_tested model_tested   model_converged
#>       <int>   <int> <chr>      <chr>  <chr>       <chr>          <lgl>          
#> 1         0       0 base model NA     NA          survival::Sur… TRUE           
#> 2         1       1 backward   remove ~dose       survival::Sur… TRUE           
#> 3         1       2 backward   remove ~sex        survival::Sur… TRUE           
#> 4         2       3 backward   remove ~sex        survival::Sur… TRUE           
#> # ℹ 4 more variables: term_p_value <dbl>, model_aic <dbl>, model_bic <dbl>,
#> #   model_updated <int>