The first book to provide a unified framework for both single-level and multilevel modeling of ordinal categorical data, Applied Ordinal Logistic Regression Using Stata helps readers learn how to conduct analyses, interpret the results from Stata output, and present those results in scholarly writing. Using step-by-step instructions, this non-technical, applied book leads students, applied researchers, and practitioners to a deeper understanding of statistical concepts by closely connecting the underlying theories of models with the application of real-world data using statistical software. Available with Perusall—an eBook that makes it easier to prepare for class Perusall is an award-winning eBook platform featuring social annotation tools that allow students and instructors to collaboratively mark up and discuss their SAGE textbook. Backed by research and supported by technological innovations developed at Harvard University, this process of learning through collaborative annotation keeps your students engaged and makes teaching easier and more effective. Learn more.
The first book to provide a unified framework for both single-level and multilevel modeling of ordinal categorical data, Applied Ordinal Logistic Regression Using Stata helps readers learn how to conduct analyses, interpret the results from ...
... 0.006 ZIP 0.052 1 0.014 ZINB -0.019 3 0.008 Third, countfit provides an expanded comparison of observed and predicted counts for each of the four models. PRM: Predicted and actual probabilities Count Actual Predicted |Diff| Pearson ...
Ordinal measures provide a simple and convenient way to distinguish among possible outcomes. The book provides practical guidance on using ordinal outcome models.
A companion website for this book contains datasets and R commands used in the book for students, and solutions for the end-of-chapter exercises on the instructor site.
The book begins with an excellent introduction to Stata and then provides a general treatment of estimation, testing, fit, and interpretation in this class of models.
'Tis better to use a logit or probit link function than to inappropriately use ordinary least squares regression with binary or categorical dependent variables . . .” —attributed to Warren Shakespeare, William's younger statistician ...
This is the sixth edition of a popular textbook on multivariate analysis.
Hillsdale, NJ: Lawrence Erlbaum. Cohen, J., Cohen, P., West, S., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences. Mahwah, NJ: Lawrence Erlbaum. DeGroot, A. D., & Spiekerman, J. A. ...
This book provides clear and simple examples illustrating how to interpret and visualize a wide variety of regression models.
This book explains what ordered and multinomial models are and also shows how to apply them to analysing issues in the social sciences.