title: Medication adherence: tailoring the analysis to the data.
abstract: The purpose of this paper is to explore more comprehensive methods to analyze antiretroviral non-adherence data. Using illustrative data and simulations, we investigated the value of using binary logistic regression (LR; dichotomized at 0% non-adherence) versus a hurdle model (combination of LR plus generalized linear model for >0% non-adherence) versus a zero-inflated negative binomial (ZINB) model (simultaneously modeling 0% non-adherence and >0% non-adherence). In simulation studies, the hurdle and ZINB models had similar power but both had higher power in comparison to LR alone. The hurdle model had higher power than ZINB in settings where covariate effects were restricted to one or the other part of the model (0% non-adherence or degree of non-adherence). Use of the hurdle and ZINB models are powerful and valuable approaches in analyzing adherence data which yield a more complete picture than LR alone. We recommend adoption of this methodology for future antiretroviral adherence research.
authors.affiliation: Department of Medicine, University of California, San Francisco, 94105, USA. parya.saberi@ucsf.edu
authors.forename: Parya
authors.initials: P
authors.lastname: Saberi
authors.forename: Mallory O
authors.initials: MO
authors.lastname: Johnson
authors.forename: Charles E
authors.initials: CE
authors.lastname: McCulloch
authors.forename: Eric
authors.initials: E
authors.lastname: Vittinghoff
authors.forename: Torsten B
authors.initials: TB
authors.lastname: Neilands
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D044966:Anti-Retroviral Agents / Q000627:therapeutic use*; D005260:Female; D015658:HIV Infections / Q000188:drug therapy*; D006801:Humans; D008297:Male; D055118:Medication Adherence; D008875:Middle Aged; D015233:Models, Statistical; D016032:Randomized Controlled Trials as Topic; D013223:Statistics as Topic; D055815:Young Adult
chemical_list: D044966:Anti-Retroviral Agents