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Beechey, Timothy – Journal of Speech, Language, and Hearing Research, 2023
Purpose: This article provides a tutorial introduction to ordinal pattern analysis, a statistical analysis method designed to quantify the extent to which hypotheses of relative change across experimental conditions match observed data at the level of individuals. This method may be a useful addition to familiar parametric statistical methods…
Descriptors: Hypothesis Testing, Multivariate Analysis, Data Analysis, Statistical Inference
García-Pérez, Miguel A. – Educational and Psychological Measurement, 2017
Null hypothesis significance testing (NHST) has been the subject of debate for decades and alternative approaches to data analysis have been proposed. This article addresses this debate from the perspective of scientific inquiry and inference. Inference is an inverse problem and application of statistical methods cannot reveal whether effects…
Descriptors: Hypothesis Testing, Statistical Inference, Effect Size, Bayesian Statistics
Lin, Johnny Cheng-Han – ProQuest LLC, 2013
Many methods exist for imputing missing data but fewer methods have been proposed to test the missing data mechanism. Little (1988) introduced a multivariate chi-square test for the missing completely at random data mechanism (MCAR) that compares observed means for each pattern with expectation-maximization (EM) estimated means. As an alternative,…
Descriptors: Data Analysis, Statistical Inference, Error of Measurement, Probability
Marsh, Herbert W.; Hau, Kit-Tai; Wen, Zhonglin – Structural Equation Modeling, 2004
Goodness-of-fit (GOF) indexes provide "rules of thumb"?recommended cutoff values for assessing fit in structural equation modeling. Hu and Bentler (1999) proposed a more rigorous approach to evaluating decision rules based on GOF indexes and, on this basis, proposed new and more stringent cutoff values for many indexes. This article discusses…
Descriptors: Statistical Significance, Structural Equation Models, Evaluation Methods, Evaluation Research