TY - JOUR
T1 - Methodological Challenges in Research on Sexual Risk Behavior
T2 - I. Item Content, Scaling, and Data Analytical Options
AU - Schroder, Kerstin E.E.
AU - Carey, Michael P.
AU - Vanable, Peter A.
N1 - Funding Information:
This work was supported by National Institute of Mental Health Grants R01–MH54929 and K02–MH01582 to Michael P. Carey. We thank Kate B. Carey, Martin J. Sliwinski, Dan Neal, and the anonymous reviewers for their comments on earlier versions of this article.
PY - 2003
Y1 - 2003
N2 - Investigation of sexual behavior involves many challenges, including how to assess sexual behavior and how to analyze the resulting data. Sexual behavior can be assessed using absolute frequency measures (also known as counts) or with relative frequency measures (e.g., rating scales that range from never to always). We discuss these 2 assessment approaches in the context of research on HIV risk behavior. We conclude that these 2 approaches yield nonredundant information and, more important, that only data yielding information about the absolute frequency of risk behavior have the potential to serve as valid indicators of HIV contraction risk. However, analyses of count data may be challenging because of non-normal distributions with many outliers. Therefore, we identify new and powerful data analytical solutions that have been developed recently to analyze count data and discuss limitations of a commonly applied method (viz., analysis of covariance using baseline scores as covariates).
AB - Investigation of sexual behavior involves many challenges, including how to assess sexual behavior and how to analyze the resulting data. Sexual behavior can be assessed using absolute frequency measures (also known as counts) or with relative frequency measures (e.g., rating scales that range from never to always). We discuss these 2 assessment approaches in the context of research on HIV risk behavior. We conclude that these 2 approaches yield nonredundant information and, more important, that only data yielding information about the absolute frequency of risk behavior have the potential to serve as valid indicators of HIV contraction risk. However, analyses of count data may be challenging because of non-normal distributions with many outliers. Therefore, we identify new and powerful data analytical solutions that have been developed recently to analyze count data and discuss limitations of a commonly applied method (viz., analysis of covariance using baseline scores as covariates).
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U2 - 10.1207/S15324796ABM2602_02
DO - 10.1207/S15324796ABM2602_02
M3 - Review article
C2 - 14534027
AN - SCOPUS:0142091332
SN - 0883-6612
VL - 26
SP - 76
EP - 103
JO - Annals of Behavioral Medicine
JF - Annals of Behavioral Medicine
IS - 2
ER -