Opening book details…
Can I read Ordinal Data Modeling (Statistics for Social and Behavioral Sciences) on EtoBox?
Ordinal Data Modeling (Statistics for Social and Behavioral Sciences) by Valen E. Johnson, James H. Albert is a social science available to read on EtoBox.
What is Ordinal Data Modeling (Statistics for Social and Behavioral Sciences) about?
<b>Ordinal Data Modeling</b> is a comprehensive treatment of ordinal data models from both likelihood and Bayesian perspectives. Written for graduate students and researchers in the statistical and social sciences, this book describes a coherent framework for understanding binary and ordinal regression models, item response models, graded response models, and ROC analyses, and for exposing the close connection between these models. A unique feature of this text is its emphasis on applications. A
Who reads Ordinal Data Modeling (Statistics for Social and Behavioral Sciences)?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- Valen E. Johnson, James H. Albert
- Publisher
- Springer; Springer-Verlag
- Published
- 1999
- Language
- EN
- ISBN
- 9780387987187
- Category
- social science
- Subjects
- Science, Computer Science, Social Science
- Updated
- 2026-03-24
Other editions & translations
More by Valen E. Johnson, James H. Albert
Browse all works by Valen E. Johnson, James H. Albert
Similar books
- Bayesian Item Response Modeling: Theory and Applications (Statistics for Social and Behavioral Sciences) — Jean-Paul Fox (auth.) (2010)
- Multivariable Modeling and Multivariate Analysis for the Behavioral Sciences (Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences) — Brian S. Everitt (2009)
- Introduction to Applied Bayesian Statistics and Estimation for Social Scientists (Statistics for Social and Behavioral Sciences) — Scott M. Lynch (2007)
- Statistical Test Theory for the Behavioral Sciences (Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences) — Dato N. M. de Gruijter, Leo J. Th. van der Kamp (2007)
- Analysis of Ordinal Categorical Data: Agresti/Analysis — Alan Agresti(auth.) (2010)
- Bayesian Models for Categorical Data (Wiley Series in Probability and Statistics) — Peter D. Congdon (2005)