Measuring Dynamics with Static Tools: Ising-Generated Data Challenges Classical Psychometrics and Temporal Invariance

We investigate when static psychometric models remain valid for data generated by dynamic psychological processes. Using simulations from Ising networks and high-frequency empirical EMA data, we show how temporal dependencies, aggregation choices, and nonlinear dynamics systematically distort IRT item parameters, challenging assumptions of temporal invariance in classical measurement.