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Latent Variable Models and Factor Analysis
Wiley Series in Probability and Statistics (Book #904)
Latent Variable Models and Factor Analysis provides a comprehensive and unified approach to factor analysis and latent variable modeling from a statistical perspective. This book presents a general framework to enable the derivation of the commonly used models, along with updated numerical examples. Nature and interpretation of a latent variable is also introduced along with related techniques forGod, Chance and Purpose: Can God Have It Both Ways?
Scientific accounts of existence give chance a central role. At the smallest level, quantum theory involves uncertainty and evolution is driven by chance and necessity. These ideas do not fit easily with theology in which chance has been seen as the enemy of purpose. One option is to argue, as proponents of Intelligent Design do, that chance is not real and can be replaced by the work of aEssentials of Statistical Inference
Cambridge Series in Statistical and Probabilistic Mathematics (Book #16)
Aimed at advanced undergraduate and graduate students in mathematics and related disciplines, this 2005 book presents the concepts and results underlying the Bayesian, frequentist and Fisherian approaches, with particular emphasis on the contrasts between them. Computational ideas are explained, as well as basic mathematical theory. Written in a lucid and informal style, this concise text providesEconometric Society Monographs (Book #38)
Quantile regression is gradually emerging as a unified statistical methodology for estimating models of conditional quantile functions. By complementing the exclusive focus of classical least squares regression on the conditional mean, quantile regression offers a systematic strategy for examining how covariates influence the location, scale and shape of the entire response distribution. ThisApplied Multiple Regression/Correlation Analysis for the Behavioral Sciences
This classic text on multiple regression is noted for its nonmathematical, applied, and data-analytic approach. Readers profit from its verbal-conceptual exposition and frequent use of examples. The applied emphasis provides clear illustrations of the principles and provides worked examples of the types of applications that are possible. Researchers learn how to specify regression models thatA Handbook for Data Analysis in the Behaviorial Sciences
Volume 1: Methodological Issues Volume 2: Statistical Issues
Statistical methodology is often conceived by social scientists in a technical manner; they use it for support rather than for illumination. This two-volume set attempts to provide some partial remedy to the problems that have led to this state of affairs. Both traditional issues, such as analysis of variance and the general linear model, as well as more novel methods like exploratory dataOrdinal Methods for Behavioral Data Analysis
This book was written with the belief that ordinal statistical methods--sometimes discussed under the title of "nonparametric statistics"--deserve much more serious attention as research tools than they have traditionally had. There are three classes of reasons for this: *Many behavioral variables constitute only ordinal scales, not interval measurements that are required for traditional