Abstract
In alcohol studies, drinking outcomes such as number of days of any alcohol drinking (DAD) over a period of time do not precisely capture the differences among subjects in a study population of interest. For example, the value of 0 on DAD could mean that the subject was continually abstinent from drinking such as lifetime abstainers or the subject was alcoholic, but happened not to use any alcohol during the period of interest. In statistics, zeros of the first kind are called structural zeros, to distinguish them from the sampling zeros of the second type. As the example indicates, the structural and sampling zeros represent two groups of subjects with quite different psychosocial outcomes. In the literature on alcohol use, although many recent studies have begun to explicitly account for the differences between the two types of zeros in modeling drinking variables as a response, none has acknowledged the implications of the different types of zeros when such modeling drinking variables are used as a predictor. This paper serves as the first attempt to tackle the latter issue and illustrate the importance of disentangling the structural and sampling zeros by using simulated as well as real study data.
Highlights
In alcohol studies or more generally in behavioral and psychosocial studies, it is important, both conceptually and methodologically, to pay special attention to structural zeros in count variables
Beyond the field of alcohol research, another example of a predictor variable with structural zeros is the number of sexual partners in HIV/AIDS research, where structural zeros refer to those with lifetime celibacy or sexual problems, while random zeros are associated with those sexually active individuals who happened to have no sex during the study time
If c1 and c2 have the same sign, say both are positive, c1, c2 > 0, the mean of the at-risk subgroup defined by positive X > the mean of the at-risk group defined by random zeros of X < the mean of the non-risk group defined by structure zeros of X
Summary
In alcohol studies or more generally in behavioral and psychosocial studies, it is important, both conceptually and methodologically, to pay special attention to structural zeros in count variables. Become, continually abstinent from drinking during a given time period form the non-risk subgroup of individuals with structural zeros in such drinking outcomes, while the remaining subjects constitute the at-risk subgroup Such a partition of the study population is supported by the excess number of zeros observed in the distributions of drinking scores from many epidemiologic studies focusing on alcohol and related substance use (see Section 3.2), and conceptually needed to serve as a basis for causal inference. Beyond the field of alcohol research, another example of a predictor variable with structural zeros is the number of sexual partners in HIV/AIDS research, where structural zeros refer to those with lifetime celibacy or sexual problems, while random zeros are associated with those sexually active individuals who happened to have no sex during the study time
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
