Comparing a Binary Dependent Variable Across Cultural Groups Using Applied Logistic Regression

T. Tran, Keith T Chan
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Abstract

This chapter reviews the basic ideas of logistic regression involving a binary dependent regressed on independent variables, along with assumptions for analysis and interpretations of results. It provides strategies and practical guides for data analysis using Stata and explains the basic assumptions of logistic regression and its applications for cross-cultural data analysis. The chapter also provides examples of logistic regression models for cross-cultural comparison, and outlines the techniques for testing the equivalence of effects across groups. The text includes examples of charts and graphs that can be used to explain differences in effects across cultural groups.
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使用应用逻辑回归比较跨文化群体的二元因变量
本章回顾了逻辑回归的基本思想,包括对自变量的二元依赖回归,以及分析和解释结果的假设。它为使用Stata进行数据分析提供了策略和实用指南,并解释了逻辑回归的基本假设及其在跨文化数据分析中的应用。本章还提供了跨文化比较的逻辑回归模型的例子,并概述了测试跨群体效应等效性的技术。文中包括图表和图形的例子,可以用来解释不同文化群体的影响差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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Applied Hierarchical Linear Modeling for Cross-Cultural Comparison Comparing a Binary Dependent Variable Across Cultural Groups Using Applied Logistic Regression Culture and Social Work Conclusion and Future Directions Introduction to Applied Cross-Cultural Data Analysis
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