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AIDS and Behavior
Published in: AIDS and Behavior 7/2011

01-10-2011 | Original Paper

Medication Adherence: Tailoring the Analysis to the Data

Authors: Parya Saberi, Mallory O. Johnson, Charles E. McCulloch, Eric Vittinghoff, Torsten B. Neilands

Published in: AIDS and Behavior | Issue 7/2011

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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.
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Metadata
Title
Medication Adherence: Tailoring the Analysis to the Data
Authors
Parya Saberi
Mallory O. Johnson
Charles E. McCulloch
Eric Vittinghoff
Torsten B. Neilands
Publication date
01-10-2011
Publisher
Springer US
Published in
AIDS and Behavior / Issue 7/2011
Print ISSN: 1090-7165
Electronic ISSN: 1573-3254
DOI
https://doi.org/10.1007/s10461-011-9951-9

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Live Webinar | 27-06-2024 | 18:00 (CEST)

Keynote webinar | Spotlight on medication adherence

Reserve your place

Live: Thursday 27th June 2024, 18:00-19:30 (CEST)

WHO estimates that half of all patients worldwide are non-adherent to their prescribed medication. The consequences of poor adherence can be catastrophic, on both the individual and population level.

Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.

Prof. Kevin Dolgin
Prof. Florian Limbourg
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Developed by: Springer Medicine
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