For much of the twentieth century, Markov theory and Markov processes have been widely accepted as valid ways to view statistical variables and parameters. In the complex realm of online searching, where researchers are always seeking the route to the best search strategies and the most powerful query terms and sequences, Markov process analysis…

Suggests ways for using data from championship tennis as a means for exploring probabilistic models, especially binomial probability. Examples include the probability of winning a service point and the probability of winning a service game using data from tables and graphs. (AIM)

The asymptotic posterior normality of latent variable distributions is established under very general and appropriate hypotheses, providing a probabilistic basis for assessing ability estimation/prediction accuracy in the long test case, as well as a first step in making the Dutch Identity conjecture rigorous. (SLD)

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…

A multiparameter, programmable model was developed to examine the interactive influence of certain parameters on the probability of deciding that an examinee had attained a specified degree of mastery. It was applied within the simulated context of performance testing of military trainees. These parameters included: (1) the number of assumed…

Describes advances in capture-recapture modeling, including the biologically motivated emphasis on model-based hypothesis testing and the development of models for spatially stratified populations. Discusses the severe problems associated with count statistics reflecting unknown sampling fractions. (67 references) (KR)

THIS PAPER DEALS WITH SOME TESTS OF HYPOTHESIS FREQUENTLY ENCOUNTERED IN THE ANALYSIS OF MULTIVARIATE DATA. THE TYPE OF HYPOTHESIS CONSIDERED IS THAT WHICH THE STATISTICIAN CAN ANSWER IN THE NEGATIVE OR AFFIRMATIVE. THE DOOLITTLE METHOD MAKES IT POSSIBLE TO EVALUATE THE DETERMINANT OF A MATRIX OF HIGH ORDER, TO SOLVE A MATRIX EQUATION, OR TO…

A Markov model for predicting performance on criterion-referenced tests is presented,. The model is expressed mathematically as a function of transition matrix, a current state vector, and a future state vector. The matrix is defined in terms of conditional probabilities, i.e., the probability of making a transition to a specific future…

A descriptive model of how people make judgments under ambiguity is proposed. Two factors are reflected in the model: (1) the amount of ambiguity, which affects the size of the simulation, and (2) one's attitudes toward ambiguity. The model is tested in four experiments using individual and group analyses. (Author/LMO)

Topics concerning latent trait theory are addressed: (1) dimensionality of latent space, local independence, and item characteristic curves; (2) models--equations, parameter estimation, testing assumptions, and goodness of fit, (3) applications test developments, item bias, tailored testing and equating; and (4) advantages over classical…

An elementary survey of item characteristic curve theory, centered around the problems of individualized (tailored) testing, is presented. Following the introduction, discussions are provided of the following: Test Theory for Itemized Tests; The Guttman Scale; Item Characteristic Curve Theory; An Alternative Model; Specialization, Application, and…

Expectancy theory and decision theory research predicting occupational preference and choice were reviewed to assess the usefulness of such approaches. Each investigation produced substantial support for the use of such models suggesting that both theories can provide practical insights for occupational guidance and counseling. While theoretical,…