[论文解读] Categorical Data Analysis

Dandan Chen, Carolyn Anderson|arXiv (Cornell University)|Aug 24, 2024

Advanced Statistical Methods and Models被引用 6

一句话总结

本文提供了一个关于分析分类数据的基本概念和方法的章节概览，并通过三个数据集进行了示例。

ABSTRACT

Categorical data are common in educational and social science research; however, methods for its analysis are generally not covered in introductory statistics courses. This chapter overviews fundamental concepts and methods in categorical data analysis. It describes and illustrates the analysis of contingency tables given different sampling processes and distributions, estimation of probabilities, hypothesis testing, measures of associations, and tests of no association with nominal variables, as well as the test of linear association with ordinal variables. Three data sets illustrate fatal police shootings in the United States, clinical trials of the Moderna vaccine, and responses to General Social Survey questions.

研究动机与目标

• Introduce fundamental concepts in categorical data analysis.
• Describe how to analyze contingency tables under different sampling processes and distributions.
• Explain estimation of probabilities and hypothesis testing for nominal and ordinal data.
• Summarize measures of association and tests of no association for nominal variables and linear association for ordinal variables.
• Illustrate methods with real data examples from diverse study contexts.

提出的方法

• Discuss contingency table analysis under varying sampling schemes and distributions.
• Present estimation techniques for probabilities associated with categorical outcomes.
• Explain hypothesis testing procedures for nominal data and for linear association in ordinal data.
• Introduce measures of association and tests of no association for nominal variables.
• Provide practical illustrations using real data sets.

实验结果

研究问题

• RQ1 What are the essential concepts and methods for analyzing categorical data in educational and social science research?
• RQ2 How can contingency table analyses be conducted under different sampling processes and distributions?
• RQ3 What are appropriate estimation, testing, and measures of association for nominal and ordinal categorical data?

主要发现

• The chapter outlines fundamental concepts for analyzing categorical data.
• It describes and illustrates contingency table analysis under various sampling processes and distributions.
• It covers estimation of probabilities and hypothesis testing for nominal data and for ordinal data with linear association.
• It discusses measures of association and tests of no association for nominal variables.
• Three data sets are used to illustrate the methods: fatal police shootings in the United States, Moderna vaccine clinical trials, and General Social Survey responses.