Exploring Rating Scale Functioning For Survey Research
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Exploring Rating Scale Functioning for Survey Research
Author: Stefanie A. Wind
language: en
Publisher: SAGE Publications
Release Date: 2022-12-19
Items with ordered response categories are common in survey research, such as when respondents are asked how much they agree with certain statements. But how large are the differences between categories of response, and how well do they distinguish between respondents? This volume is the first to introduce the evaluation of rating scales to an audience of survey researchers. Evaluating Rating Scale Functioning for Survey Research provides researchers with an overview of rating scale analysis along with practical guidance on how to conduct such analyses with their own survey data. Author Stefanie A. Wind presents three categories of methods: Rasch models; non-Rasch Item Response Theory (IRT) models; and non-parametric models, together with practical examples. Tutorials, datasets, and software code (R and Facets) to accompany the book are available on the book’s website.
The Practice of Survey Research
Focusing on the use of technology in survey research, this book integrates both theory and application and covers important elements of survey research including survey design, implementation and continuing data management.
Modeling Nonlinearity and Interaction in Regression Analysis Using Spline Variables
Author: Roger A. Wojtkiewicz
language: en
Publisher: SAGE Publications
Release Date: 2025-05-22
"Spline variables and their interactions play a crucial role in the field of social science. This book offers a comprehensive and detailed exploration of this method, providing valuable insights and information for researchers in the field." --Man-Kit Lei, The University of Georgia This volume addresses the issue of linear constraints in regression modeling. Author Roger A. Wojtkiewicz uses the method of knotted spline variables (also known as piecewise linear regression) and a new method involving group spline variables to model nonlinearity in a variety of situations. Using spline variables to model nonlinearity allows researchers to specify unrestricted models for models that involve interval variables, allowing for greater flexibility in modeling any possible interaction.