A Simple and Transparent Alternative to Repeated Measures ANOVA | Zendy

James W. Grice | Zendy; David Philip Arthur Craig | Zendy; Charles I. Abramson | Zendy

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A Simple and Transparent Alternative to Repeated Measures ANOVA

Author(s) -

James W. Grice,

David Philip Arthur Craig,

Charles I. Abramson

Publication year - 2015

Publication title -

sage open

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.357

H-Index - 32

ISSN - 2158-2440

DOI - 10.1177/2158244015604192

Subject(s) - outlier , parametric statistics , nonparametric statistics , repeated measures design , parametric model , missing data , analysis of variance , computer science , econometrics , statistics , statistical model , population , machine learning , mathematics , artificial intelligence , demography , sociology

Observation Oriented Modeling is a novel approach towardconceptualizing and analyzing data. Compared with traditional parametric statistics,Observation Oriented Modeling is more intuitive, relatively free of assumptions, andencourages researchers to stay close to their data. Rather than estimating abstractpopulation parameters, the overarching goal of the analysis is to identify and explaindistinct patterns within the observations. Selected data from a recent study by Craig etal. were analyzed using Observation Oriented Modeling; this analysis was contrasted witha traditional repeated measures ANOVA assessment. Various pitfalls in traditionalparametric analyses were avoided when using Observation Oriented Modeling, including thepresence of outliers and missing data. The differences between Observation OrientedModeling and various parametric and nonparametric statistical methods were finallydiscussed

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