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Risk Behavior Data Analysis: Ordinal or Dichotomous the Choice Is Yours

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Objective: To demonstrate the differences of 2 approaches to data analysis. Methods: Using the South Carolina YRBS data, study focused on contingency tables and ANOVA. Additive chi squares are utilized to illustrate information loss when collapsing a contingency table. Odds ratios are derived from contingency tables or logistic regression. Means are utilized in ANOVA. Five measures of life satisfaction were summed to create a pseudo-continuous response variable that was subsequently trichotomized. All predictors are dichotomized risk variables. Results: Chi squares from subtables added exactly to that of the original table measuring lost information. ANOVA conveyed the same clinical message. Conclusion: Clinically relevant conclusions might be the same even when drawn from any of several different analyses of the same risk-behavior data.
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Document Type: Research Article

Affiliations: 1: Epidemiology & Biostatistics, Family & Preventive Medicine, Schools of Public Health and Medicine, University of South Carolina, Columbia, SC. 2: Education & Behavior, Family & Preventive Medicine, Schools of Public Health and Medicine, University of South Carolina, Columbia SC.

Publication date: 2002-11-01

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  • The American Journal of Health Behavior seeks to improve the quality of life through multidisciplinary health efforts in fostering a better understanding of the multidimensional nature of both individuals and social systems as they relate to health behaviors.

    The Journal aims to provide a comprehensive understanding of the impact of personal attributes, personality characteristics, behavior patterns, social structure, and processes on health maintenance, health restoration, and health improvement; to disseminate knowledge of holistic, multidisciplinary approaches to designing and implementing effective health programs; and to showcase health behavior analysis skills that have been proven to affect health improvement and recovery.

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