Repeated measures designs in cognitive research permit causal inference

The retrieved literature shows a sharp methodological debate regarding whether repeated measures or longitudinal designs automatically permit causal inference. Paper [0] and Paper [1] caution that within-subject and longitudinal adjustments can introduce or obscure bias, meaning causal conclusions are far from straightforward without strict assumptions. Conversely, Paper [5] notes that multi-time point designs can offer stronger, potentially causal insights when studying temporal dynamics. Therefore, the balance verdict is CONTESTED because repeated measures are useful tools for examining change over time, but their ability to yield valid causal inference is heavily contested and contingent upon overcoming significant statistical and methodological hurdles.