A Negative Binomial Regression Model for Accuracy Tests

Autor/in	Hung, Lai-Fa
Titel	A Negative Binomial Regression Model for Accuracy Tests
Quelle	In: Applied Psychological Measurement, 36 (2012) 2, S.88-103 (16 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0146-6216
DOI	10.1177/0146621611429548
Schlagwörter	Social Science Research; Markov Processes; Reading Tests; Social Sciences; Error Patterns; Evaluation Methods; Computation; Monte Carlo Methods; Simulation + Suchen Sie Ihr Suchwort? Social scientific research; Sozialwissenschaftliche Forschung; Markowscher Prozess; Lesetest; Social science; Sozialwissenschaften; Gesellschaftswissenschaften; Fehlertyp; Monte-Carlo-Methode; Simulation program; Simulationsprogramm
Abstract	Rasch used a Poisson model to analyze errors and speed in reading tests. An important property of the Poisson distribution is that the mean and variance are equal. However, in social science research, it is very common for the variance to be greater than the mean (i.e., the data are overdispersed). This study embeds the Rasch model within an overdispersion framework and proposes new estimation methods. The parameters in the proposed model can be estimated using the Markov chain Monte Carlo method implemented in WinBUGS and the marginal maximum likelihood method implemented in SAS. An empirical example based on models generated by the results of empirical data, which are fitted and discussed, is examined. (Contains 8 tables.) (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10