In the context of linear models, the evaluation of parameter constancy and predictive accuracy is of paramount importance. This paper presents methods and tests for assessing the stability of model parameters over time and gauging the model's ability to make accurate predictions. The assessment of parameter constancy involves analysing how model coefficients or effects change over different time periods, while predictive accuracy evaluation pertains to the model's ability to make reliable predictions for new data.