run_meta_loocv | R Documentation |
Performs Leave-One-Out Cross-Validation (LOOCV) on hierarchical model outputs to assess the influence of individual simulated animals on population-level estimates. Supports analyses with or without groups.
In each iteration, the function removes one individual, refits the hierarchical model to the remaining dataset, and recalculates the target population-level estimates. This process is repeated until every individual has been excluded once.
This approach provides insight into how sensitive overall conclusions are to specific individuals. This helps identify influential individuals and assess robustness.
run_meta_loocv(
rv,
set_target = c("hr", "ctsd"),
subpop = FALSE,
trace = FALSE,
...
)
rv |
A |
set_target |
Character vector specifying the target metrics.
Options are |
subpop |
Logical; if |
trace |
Logical; if |
... |
Additional arguments for advanced control:
|
A data frame containing summarized simulation outputs.
Inês Silva i.simoes-silva@hzdr.de
if(interactive()) {
run_meta_loocv(rv, set_target = "hr")
}
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