Inference in regression models of heavily skewed alcohol use data: A comparison of ordinary least squares, generalized linear models, and bootstrap resampling.

Inference in regression models of heavily skewed alcohol use data: A comparison of ordinary least squares, generalized linear models, and bootstrap resampling. Research Abstract Details 

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Inference in regression models of heavily skewed alcohol use data: A comparison of ordinary least squares, generalized linear models, and bootstrap resampling. Abstract Text:

Dan J Neal,Jeffrey S Simons,Dan J Neal,Jeffrey S Simons,

Analysis of alcohol use data and other low base rate risk behaviors using ordinary least squares regression models can be problematic. This article presents 2 alternative statistical approaches, generalized linear models and bootstrapping, that may be more appropriate for such data. First, the basic theory behind the approaches is presented. Then, using a data set of alcohol use behaviors and consequences, results based on these approaches are contrasted with the results from ordinary least squares regression. The less traditional approaches consistently demonstrated better fit with model assumptions, as demonstrated by graphical analysis of residuals, and identified more significant variables potentially resulting in theoretically different interpretations of the models of alcohol use. In conclusion, these models show significant promise for furthering the understanding of alcohol-related behaviors. (PsycINFO Database Record (c) 2007 APA, all rights reserved).

Inference in regression models of heavily skewed alcohol use data: A comparison of ordinary least squares, generalized linear models, and bootstrap resampling. Publishing Authors By Initials

DJ Neal,JS Simons,DJ Neal,JS Simons,

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Inference in regression models of heavily skewed alcohol use data: A comparison of ordinary least squares, generalized linear models, and bootstrap resampling. Journal Published:

PUBLICATION TYPE: Journal Article

Journal: Psychology of addictive behaviors : journal of the

VOLUME: 21

Page Numbers: 441-52

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ISSN: 0893-164X

DAY: 12

MONTH: Dec

YEAR: 2007

Inference in regression models of heavily skewed alcohol use data: A comparison of ordinary least squares, generalized linear models, and bootstrap resampling. Information

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LANGUAGE: eng

NlmUniqueID: 8802734

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Grant and Affiliation Information for Inference in regression models of heavily skewed alcohol use data: A comparison of ordinary least squares, generalized linear models, and bootstrap resampling.

AFFILIATION: Department of Psychology, Kent State University.

Country: United States

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MEDLINETA: Psychol Addict Behav

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