دورية أكاديمية

Assessing Potential Heteroscedasticity in Psychological Data: A GAMLSS approach

التفاصيل البيبلوغرافية
العنوان: Assessing Potential Heteroscedasticity in Psychological Data: A GAMLSS approach
المؤلفون: Correa, Juan C., Kneib, Thomas, Ospina, Raydonal, Tejada, Julian, Marmolejo-Ramos, Fernando
المصدر: Tutorials in Quantitative Methods for Psychology, Vol 19, Iss 4, Pp 333-346 (2023)
بيانات النشر: Université d'Ottawa, 2023.
سنة النشر: 2023
المجموعة: LCC:Psychology
مصطلحات موضوعية: heteroscedasticity, gamlss, scientific evidence., Psychology, BF1-990
الوصف: This paper provides a tutorial for analyzing psychological research data with GAMLSS, an R package that uses the family of generalized additive models for location, scale, and shape. These models extend the capacities of traditional parametric and non-parametric tools that primarily rely on the first moment of the statistical distribution. When psychological data fails the assumption of homoscedasticity, the GAMLSS approach might yield less biased estimates while offering more insights about the data when considering sources of heteroscedasticity. The supplemental material and data help newcomers understand the implementation of this approach in a straightforward step-by-step procedure.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
French
تدمد: 1913-4126
العلاقة: https://www.tqmp.org/RegularArticles/vol19-4/p333/p333.pdfTest; https://doaj.org/toc/1913-4126Test
DOI: 10.20982/tqmp.19.4.p333
الوصول الحر: https://doaj.org/article/2adf67064db948e7bc547c20193331c2Test
رقم الانضمام: edsdoj.2adf67064db948e7bc547c20193331c2
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:19134126
DOI:10.20982/tqmp.19.4.p333