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Analysis of the Response Structure to a Set of Questions with Large Number of Scale Points: A New Combined Metric and Categorical Approach
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Abascal, Elena; Díaz De Rada, Vidal; García Lautre, Ignacio; Landaluce, M. Isabel – International Journal of Social Research Methodology, 2018
In the field of social sciences, certain tasks, such as the identification of typologies and the characterization of groups of individuals according to a set of questions, tend to pose a challenge for researchers. Further complications arise if the chosen rating scale is from 0 to 10, since the responses can be treated either as metric or…
Descriptors: Social Science Research, Research Problems, Rating Scales, Factor Analysis
Brief Research Report: Growth Models with Small Samples and Missing Data
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McNeish, Daniel – Journal of Experimental Education, 2018
Small samples are common in growth models due to financial and logistical difficulties of following people longitudinally. For similar reasons, longitudinal studies often contain missing data. Though full information maximum likelihood (FIML) is popular to accommodate missing data, the limited number of studies in this area have found that FIML…
Descriptors: Growth Models, Sampling, Sample Size, Hierarchical Linear Modeling
Missing Data and Multiple Imputation in the Context of Multivariate Analysis of Variance
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Finch, W. Holmes – Journal of Experimental Education, 2016
Multivariate analysis of variance (MANOVA) is widely used in educational research to compare means on multiple dependent variables across groups. Researchers faced with the problem of missing data often use multiple imputation of values in place of the missing observations. This study compares the performance of 2 methods for combining p values in…
Descriptors: Multivariate Analysis, Educational Research, Error of Measurement, Research Problems
Challenging Conventional Wisdom for Multivariate Statistical Models with Small Samples
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McNeish, Daniel – Review of Educational Research, 2017
In education research, small samples are common because of financial limitations, logistical challenges, or exploratory studies. With small samples, statistical principles on which researchers rely do not hold, leading to trust issues with model estimates and possible replication issues when scaling up. Researchers are generally aware of such…
Descriptors: Models, Statistical Analysis, Sampling, Sample Size
The Statistical and Methodological Acuity of Scholarship Appearing in the "International Journal of Listening" (1987-2011)
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Keaton, Shaughan A.; Bodie, Graham D. – International Journal of Listening, 2013
This article investigates the quality of social scientific listening research that reports numerical data to substantiate claims appearing in the "International Journal of Listening" between 1987 and 2011. Of the 225 published articles, 100 included one or more studies reporting numerical data. We frame our results in terms of eight…
Descriptors: Periodicals, Journal Articles, Listening, Social Science Research
Rationale, Detection, and Implications of Interactions between Independent Variables and Unmeasured Variables in Linear Models.
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Wood, Phillip Karl; Games, Paul – Multivariate Behavioral Research, 1990
Conceptual rationales from five research contexts are presented, which all posit unmeasured variables that interact with observed independent variables to produce a complete model of the dependent variable. Strategies for overcoming related difficulties are outlined, including increased longitudinal assessment, oversampling of levels of…
Descriptors: Estimation (Mathematics), Longitudinal Studies, Mathematical Models, Multivariate Analysis