Accurate estimation of variance components used in generalizability theory is essential for the theory to be viewed as an efficacious mechanism for studying the reliability and validity of a measurement procedure. This paper explores two alternatives for dealing with the apparent instability of small sample size used in determining the accuracy of…

Describes the phenomenological and microscopic aspects of solid-state diffusion in an electric field and presents a Monte Carlo method which is used to stimulate an atomistic model of diffusion in an electric field. The Nernst-Einstein relation is also discussed. (HM)

This paper describes a computer simulation of Buffon's needle problem. The problem considers the probability that a needle will cross a line when the needle is thrown in a random way onto the parallel lines a certain distance apart. The paper provides the algorithm and computer program. (YP)

Describes the deterministic simulation (a given input always leads to the same output) and probabilistic simulation (new states are subject to predefined laws of chance). Provides examples of the application of the two simulations with mathematical expressions and PASCAL program. Lists seven references. (YP)

Examines the use of the computer to approximate the value of the definite integral normally calculated by mathematical means. Presents four examples using BASIC programs to approximate single and double integrals by numerical integration and the Monte Carlo method. Programs are provided. (MDH)

Monte Carlo techniques are used to examine the power of the "B" statistic of R. L. Brennan (1972) to detect negatively discriminating items drawn from a variety of nonnormal population distributions. A simplified procedure is offered for conducting an item-discrimination analysis on typical classroom objective tests. (SLD)

The ability of 3-way INDSCAL and ALSCAL models to recover true structure in proximity data based on 2-dimensional configurations varying in number of subjects (15 and 20) and stimuli, amount of error, and monotonic transformation is examined. INDSCAL outperformed metric and nonmetric ALSCAL in all conditions. (SLD)

Researchers studying monitoring accuracy currently use two different indexes to estimate accuracy: relative accuracy and absolute accuracy. The authors compared the distributional properties of two measures of monitoring accuracy using Monte Carlo procedures that fit within these categories. They manipulated the accuracy of judgments (i.e., chance…

The general linear model was described, and the influence that measurement errors have on model parameters was discussed. In particular, the assumptions of classical true-score theory were used to develop algebraic relationships between the squared multiple correlations coefficient and the regression coefficients in the infallible and fallible…

A stochastic multidimensional unfolding (MDU) procedure is presented to represent individual differences in phased or sequential decision processes spatially. A Monte Carlo analysis demonstrates estimation proficiency and the appropriateness of the proposed model selection heuristic, and an application to capture awareness, consideration, and…

Bias, standard error, and reliability of five ability estimators were evaluated using Monte Carlo estimates of the unknown conditional means and variances of the estimators. Results indicate that estimates based on Bayesian modal, expected a posteriori, and weighted likelihood estimators were reasonably unbiased with relatively small standard…

Classification studies are important for practitioners who need to identify individuals for specialized treatment or intervention. When interventions are irreversible or misclassifications are costly, information about the proficiency of different classification procedures becomes invaluable. This study furnishes information about the relative…

Measures of the robustness of disease class-specific diagnostic concepts could play a central role in training programs designed to assure the development of diagnostic competence. In the pilot study, the authors used disease/sign-symptom conditional probability estimates, Monte Carlo procedures, and artificial intelligence (AI) tools to create…

Item analysis data fitting the normal ogive model were simulated in order to investigate the problems encountered when applying the three-parameter logistic model. Binary item tests containing 10 and 35 items were created, and Monte Carlo methods simulated the responses of 2,000 and 500 examinees. Item parameters were obtained using Logist 5.…

A monte carlo simulation was conducted to assess the effects in an adaptive testing strategy for test batteries of varying subtest order, subtest termination criterion, and variable versus fixed entry on the psychometric properties of an existent achievement test battery. Comparisons were made among conventionally administered tests and adaptive…