Stochastic Parameter Regression Models (Quantitative Applications in the Social Sciences)

✍ Scribed by Paul Newbold, Theodore Bos

Publisher: Sage Publications, Inc
Year: 1985
Tongue: English
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

This excellent introduction to stochastic parameter regression models is more advanced and technically difficult than other papers in this series. These models allow relationships to vary through time, rather than requiring them to be fixed, without forcing the analyst to specify and analyze the causes of the time-varying relationships. This volume will be most useful to those with a good working knowledge of standard regression models and who wish to understand methods which deal with relationships that vary slowly over time, but for which the exact causes of variation cannot be identified.

📜 SIMILAR VOLUMES

Quantile Regression (Quantitative Applic

📁 Quantile Regression (Quantitative Applications in the Social Sciences) (v. 149)

✍ Lingxin Hao, Daniel Q. Naiman 📂 Library 📅 2007 🌐 English

Quantile Regression, the first book of Hao and Naiman's two-book series, establishes the seldom recognized link between inequality studies and quantile regression models. Though separate methodological literature exists for each subject, the authors seek to explore the natural connections between th

Applied Regression: An Introduction (Qua

📁 Applied Regression: An Introduction (Quantitative Applications in the Social Sciences)

✍ Michael S. Lewis-Beck 📂 Library 📅 1980 🏛 Sage Publications, Inc 🌐 English

Applied regression allows social scientists who are not specialists in quantitative techniques to arrive at clear verbal explanations of their numerical results. Provides a lucid discussion of more specialized subjects: analysis of residuals, interaction effects, specification error, multicollineari

Applied Logistic Regression Analysis (Qu

📁 Applied Logistic Regression Analysis (Quantitative Applications in the Social Sciences)

✍ Scott William Menard 📂 Library 📅 1995 🏛 Sage Publications, Inc 🌐 English

Emphasizing the parallels between linear and logistic regression, Scott Menard explores logistic regression analysis and demonstrates its usefulness in analyzing dichotomous, polytomous nominal, and polytomous ordinal dependent variables. The book is aimed at readers with a background in bivariate a

Applied Regression: An Introduction (Qua

📁 Applied Regression: An Introduction (Quantitative Applications in the Social Sciences)

✍ Michael S. Lewis-Beck 📂 Library 📅 1980 🏛 Sage Publications, Inc 🌐 English

Logistic Regression Models for Ordinal R

📁 Logistic Regression Models for Ordinal Response Variables (Quantitative Applications in the Social Sciences)

✍ Ann Aileen O'Connell 📂 Library 📅 2005 🌐 English

Logistic Regression Models for Ordinal Response Variables provides applied researchers in the social, educational, and behavioral sciences with an accessible and comprehensive coverage of analyses for ordinal outcomes. The content builds on a review of logistic regression, and extends to details of

Applied Logistic Regression Analysis (Qu

📁 Applied Logistic Regression Analysis (Quantitative Applications in the Social Sciences) (v. 106)

✍ Dr. Scott Menard 📂 Library 📅 2001 🏛 Sage Publications, Inc 🌐 English

The focus in this Second Edition is again on logistic regression models for individual level data, but aggregate or grouped data are also considered. The book includes detailed discussions of goodness of fit, indices of predictive efficiency, and standardized logistic regression coefficients, and ex