Parameter Recovery Checker

Purpose

This skill encodes expert methodological knowledge for conducting parameter recovery studies -- a critical validation step before interpreting fitted model parameters. Parameter recovery determines whether a model's parameters are identifiable given the experimental design and sample size. A general-purpose programmer unfamiliar with computational modeling would not know that fitting a model is insufficient validation, or how to diagnose parameter tradeoffs and non-identifiability.

When to Use This Skill

• Before trusting fitted parameter values from any computational cognitive model
• When developing a new model and assessing whether parameters can be distinguished from data
• When planning an experiment and determining the minimum trial count for reliable parameter estimation
• When a reviewer asks for evidence of model identifiability
• When comparing models and needing to ensure each model can be distinguished (model recovery)
• When fitted parameters produce suspiciously extreme values or hit bounds

Research Planning Protocol

Before executing the domain-specific steps below, you MUST: