Literature DB >> 17726714

Discrete stochastic models for compliance analysis based on an AIDS Clinical Trial Group (ACTG) study.

Junfeng Sun1, H N Nagaraj, Nancy R Reynolds.   

Abstract

Compliance is the extent to which a patient follows the prescribed regimen. Here we investigate the statistical properties of two popular measures of compliance - percentage of compliant days and percentage of doses taken. We use a stationary Markov chain to model the dependence structure of successive data points for each subject. We illustrate our model using discrete compliance data collected from an AIDS Clinical Trial Group study (ACTG 398). We check the model assumptions and evaluate the small sample as well as large sample properties of our estimators. We show that ignoring the within-subject dependence will usually underestimate the standard errors of the estimates of these compliance measures. Our model allows the application of meta-analytic approaches to assess the variation across subjects in these compliance indices and changes in them due to intervention. ((c) 2007 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim).

Entities:  

Mesh:

Substances:

Year:  2007        PMID: 17726714     DOI: 10.1002/bimj.200610368

Source DB:  PubMed          Journal:  Biom J        ISSN: 0323-3847            Impact factor:   2.207


  3 in total

1.  A pharmacokinetic and pharmacodynamic analysis of drug forgiveness.

Authors:  Noel P McAllister; Sean D Lawley
Journal:  J Pharmacokinet Pharmacodyn       Date:  2022-02-13       Impact factor: 2.745

2.  Clustering based on adherence data.

Authors:  Sylvia Kiwuwa-Muyingo; Hannu Oja; Sarah A Walker; Pauliina Ilmonen; Jonathan Levin; Jim Todd
Journal:  Epidemiol Perspect Innov       Date:  2011-03-08

3.  Dynamic logistic regression model and population attributable fraction to investigate the association between adherence, missed visits and mortality: a study of HIV-infected adults surviving the first year of ART.

Authors:  Sylvia Kiwuwa-Muyingo; Hannu Oja; Ann Walker; Pauliina Ilmonen; Jonathan Levin; Andrew Reid; Peter Mugyenyi; Jim Todd
Journal:  BMC Infect Dis       Date:  2013-08-27       Impact factor: 3.090

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.