{"title":"Modelling Count Data in Psychological Research: An Applied Tutorial","authors":"Miranda A. Too, Udi Alter, David B. Flora","doi":"10.1002/ijop.70018","DOIUrl":null,"url":null,"abstract":"<p>Across subfields of psychology, researchers frequently encounter count variables (i.e., non-negative integer values, which result from counted measurements). Although count variables are common in psychological research (e.g., frequency of behaviours or symptoms), researchers may not be aware of appropriate statistical procedures for modelling and drawing inferences from count data. Specialised regression techniques (i.e., generalised linear models and zero-augmented models) have been developed for the unique properties of count data, but they can seem inaccessible to non-technical audiences because of their departure from more familiar methods. Assuming a basic knowledge of linear regression, this tutorial aims to demystify count regression approaches and empower researchers to apply these methods to their own count data, using free, open-source statistical software (i.e., R). This tutorial takes researchers step-by-step through the implementation of count regression methods in applied research, imparting them with the knowledge to confidently implement these techniques.</p>","PeriodicalId":48146,"journal":{"name":"International Journal of Psychology","volume":"60 2","pages":""},"PeriodicalIF":3.3000,"publicationDate":"2025-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ijop.70018","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Psychology","FirstCategoryId":"102","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/ijop.70018","RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHOLOGY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Across subfields of psychology, researchers frequently encounter count variables (i.e., non-negative integer values, which result from counted measurements). Although count variables are common in psychological research (e.g., frequency of behaviours or symptoms), researchers may not be aware of appropriate statistical procedures for modelling and drawing inferences from count data. Specialised regression techniques (i.e., generalised linear models and zero-augmented models) have been developed for the unique properties of count data, but they can seem inaccessible to non-technical audiences because of their departure from more familiar methods. Assuming a basic knowledge of linear regression, this tutorial aims to demystify count regression approaches and empower researchers to apply these methods to their own count data, using free, open-source statistical software (i.e., R). This tutorial takes researchers step-by-step through the implementation of count regression methods in applied research, imparting them with the knowledge to confidently implement these techniques.
期刊介绍:
The International Journal of Psychology (IJP) is the journal of the International Union of Psychological Science (IUPsyS) and is published under the auspices of the Union. IJP seeks to support the IUPsyS in fostering the development of international psychological science. It aims to strengthen the dialog within psychology around the world and to facilitate communication among different areas of psychology and among psychologists from different cultural backgrounds. IJP is the outlet for empirical basic and applied studies and for reviews that either (a) incorporate perspectives from different areas or domains within psychology or across different disciplines, (b) test the culture-dependent validity of psychological theories, or (c) integrate literature from different regions in the world.