Misspecification and Unreliable Interpretations in Psychology and Social Science

TL;DR

This paper highlights critical issues like misspecification and unreliable interpretations in psychology and social science research, emphasizing the need for improved statistical practices to enhance scientific validity and progress.

Contribution

It identifies key analytical weaknesses and offers recommendations for better statistical modeling and interpretation in social science research.

Findings

Simulation demonstrates consequences of misspecification

Recommendations for improving research practices

Awareness of statistical challenges is crucial

Abstract

The replicability crisis has drawn attention to numerous weaknesses in psychology and social science research practice. In this work we focus on three issues that cannot be addressed with replication alone, and which deserve more attention: Functional misspecification, structural misspecification, and unreliable interpretation of results. We demonstrate a number of possible consequences via simulation, and provide recommendations for researchers to improve their research practice. Psychologists and social scientists should engage with these areas of analytical and statistical improvement, as they have the potential to seriously hinder scientific progress. Every research question and hypothesis may present its own unique challenges, and it is only through an awareness and understanding of varied statistical methods for predictive and causal modeling, that researchers will have the tools with which to appropriately address them.