Seminar 2025-04-02: Johan Lyhagen

Topic Preliminary estimation using the LM-principle

Abstract Thematic theories are incomplete meaning that they do not give a full description of how to specify a model. Rather they focus on certain aspects of interest which means that there are parts of the model that needs to be empirically decided. This includes lag-lengths in time series analysis, factor structures and correlations amongst errors in SEM, or control variables in causal inference (sensitivity analysis). In SEM there are modification indices, mainly for the purpose of improving the fit of the model, that estimate the increase of the likelihood when relaxing a restriction. Subsequently, one can also derive an estimated parameter change when relaxing a restriction. In this paper we generalise this to relaxing more than one parameter, focusing on the estimated parameter change in the parameters of interest, and derive this in the GLM setting as well as in the traditional SEM. The paper includes theoretical results, Monte Carlo simulations to investigate the small sample properties and empirical examples to show the usefulness for empirical researchers.