oday, as data sets used in computations grow in size and complexity, the technologies developed over the years to deal with scientific data sets have become less efficient and effective. Many frequently used operations , such as Eigenvector computation, could quickly exhaust our desktop workstations once the data size reaches certain limits. On the other hand, the high-dimensional data sets we ...

We develop and estimate a full information maximum likelihood ordered categorical response model with endogenous switching. Simulation exercises show that estimated parameters are unbias and consistent. And application to Internet access indicates that there are selection and moral hazard.

Covariant-contravariant simulation and conformance simulation are two generalizations of the simple notion of simulation which aim at capturing the fact that it is not always the case that “the larger the number of behaviors, the better”. Therefore, they can be considered to be more adequate to express the fact that a system is a correct implementation of some specification. We have previously ...

This article reviews several basic statistical tools needed for modeling data with sampling weights that are implemented in Mplus Version 3. These tools are illustrated in simulation studies for several latent variable models including factor analysis with continuous and categorical indicators, latent class analysis, and growth models. The pseudomaximum likelihood estimation method is reviewed ...

Increases in computing power have enabled Monte Carlo simulations to become increasingly common in contemporary statistical practice. Some applications require specialized statistical software while others can be implemented with general multipurpose statistical programs. Simulations of the power of statistical tests—the probability of rejecting the null hypothesis when it is false—are among th...

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