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ERIC Number: ED545691
Record Type: Non-Journal
Publication Date: 2012
Pages: 82
Abstractor: As Provided
Reference Count: N/A
ISBN: 978-1-2675-2353-2
Mixed-Effects Models for Count Data with Applications to Educational Research
Shin, Jihyung
ProQuest LLC, Ph.D. Dissertation, The Florida State University
This research is motivated by an analysis of reading research data. We are interested in modeling the test outcome of ability to fluently recode letters into sounds of kindergarten children aged between 5 and 7. The data showed excessive zero scores (more than 30% of children) on the test. In this dissertation, we carefully examine the models dealing with excessive zeros, which are based on the mixture of distributions, a distribution with zeros and a standard probability distribution with non negative values. In such cases, a log normal variable or a Poisson random (lambda) variable is often observed with probability from semicontinuous data or count data. The previously proposed models, mixed-effects and mixed-distribution models (MEMD) by Tooze (2002) et al. for semicontinuous data and zero-inflated Poisson (ZIP) regression models by Lambert (1992) for count data are reviewed. We apply zero-inflated Poisson models to repeated measures data of zero-inflated data by introducing a pair of possibly correlated random effects to the zero-inflated Poisson model to accommodate within-subject correlation and between subject heterogeneity. The model describes the effect of predictor variables on the probability of nonzero responses (occurrence) and mean of nonzero responses (intensity) separately. The likelihood function is maximized using dual quasi-Newton optimization of an approximated by adaptive Gaussian quadrature. The maximum likelihood estimates are obtained through standard statistical software package. Using different model parameters, the number of subject, and the number of measurements per subject, the simulation study is conducted and the results are presented. The dissertation ends with the application of the model to reading research data and future research. We examine the number of correct letter sound counted of children collected over 2008-2009 academic year. We find that age, gender and socioeconomic status are significantly related to the letter sound fluency of children in both parts of the model. The model provides better explanation of data structure and easier interpretations of parameter values, as they are the same as in standard logistic models and Poisson regression models. The model can be extended to accommodate serial correlation which can be observed in longitudinal data. Also, one may consider multilevel zero-inflated Poisson model. Although the multilevel model was proposed previously, parameter estimation by penalized quasi likelihood methods is questionable, and further examination is needed. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page:]
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Publication Type: Dissertations/Theses - Doctoral Dissertations
Education Level: Kindergarten; Primary Education; Early Childhood Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A