运行和解释二元逻辑回归分析的注意事项-一份研究笔记

Emma Beacom
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引用次数: 0

摘要

本研究报告讨论了使用皮尔逊卡方和二元逻辑回归分析分类数据的关键考虑因素。它借鉴了国家一级家庭调查(北爱尔兰健康调查2014/15)的分析经验,使用SPSSv25检查了家庭粮食不安全状况与确定的人口预测因素之间的关系,使用皮尔逊卡方检验来检查关联,并使用二元逻辑回归来推导预测模型。本说明概述了这两种检验必须满足的假设,以确保检验是适当的,讨论了在使用二元逻辑回归之前使用皮尔逊卡方检验作为初步检验的有用性,并概述了如何解释二元逻辑回归模型的输出。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Considerations for running and interpreting a binary logistic regression analysis – a research note
This research note discusses key considerations for analysis of categorical data using a Pearson’s chi-square and binary logistic regression. It draws on experience from analysis of a country-level household survey (Northern Ireland Health Survey 2014/15), using SPSSv25, that examined the relationship between household food insecurity status and identified demographic predictors, using Pearson’s Chi-Square test to check associations and binary logistic regressions to derive the predictive models. This note presents an overview of the assumptions for both tests which must be satisfied to ensure the tests are appropriate, discusses the usefulness of using Pearson’s Chi-Square test as a preliminary test before using binary logistic regression, and presents an overview of how to interpret the output from a binary logistic regression model.
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