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Enakshi Saha – ProQuest LLC, 2021
We study flexible Bayesian methods that are amenable to a wide range of learning problems involving complex high dimensional data structures, with minimal tuning. We consider parametric and semiparametric Bayesian models, that are applicable to both static and dynamic data, arising from a multitude of areas such as economics, finance and…
Descriptors: Bayesian Statistics, Probability, Nonparametric Statistics, Data Analysis
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Kukla-Acevedo, Sharon – Journal of Educational Research, 2009
The author explored whether 3 workplace conditions were related to teacher mobility decisions. The modeling strategy incorporated a series of binomial and multinomial logistic models to estimate the effects of administrative support, classroom control, and behavioral climate on teachers' decisions to quit teaching or switch schools. The results…
Descriptors: Mathematical Models, Prediction, Probability, Multiple Regression Analysis
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McSweeney, Maryellen; Schmidt, William H. – Journal of Educational Statistics, 1977
The relationship between quantitative predictor variables and the probability of occurrence of one or more levels of a qualitative criterion variable can be analyzed by quantal response techniques. This paper presents and discusses two quantal response models, comparing them to multiple linear regression and discriminant analysis. (Author/JKS)
Descriptors: Discriminant Analysis, Mathematical Models, Multiple Regression Analysis, Predictor Variables
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Bruno, James Edward; Nelkin, Ira – Educational Planning, 1975
The logit methodology provides a unique way of examining input-output relationships for social systems where the principal output of the analysis is a probability of some action or state. (Author)
Descriptors: Discriminant Analysis, Educational Planning, Educational Policy, Elementary Secondary Education
Lord, Frederic M. – 1971
A numerical procedure is outlined for obtaining an interval estimate of a parameter in an empirical Bayes estimation problem. The case where each observed value x has a binomial distribution, conditional on a parameter zeta, is the only case considered. For each x, the parameter estimated is the expected value of zeta given x. The main purpose is…
Descriptors: Bayesian Statistics, Computer Programs, Expectation, Goodness of Fit