An alternative classification to mixture modeling for longitudinal counts or binary measures
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AbstractClassifying patients according to longitudinal measures, or trajectory classification, has become frequent in clinical research. The k-means algorithm is increasingly used for this task in case of continuous variables with standard deviations that do not depend on the mean. One feature of count and binary data modeled by Poisson or logistic regression is that the variance depends on the mean; hence, the within-group variability changes from one group to another depending on the mean trajectory level. Mixture modeling could be used here for classification though its main purpose is to model the data. The results obtained may change according to the main objective. This article presents an extension of the k-means algorithm that takes into account the features of count and binary data by using the deviance as distance metric. This approach is justified by its analogy with the classification likelihood. Two applications are presented with binary and count data to show the differences between the classifications obtained with the usual Euclidean distance versus the deviance distance.
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- Issue date: 2017 Mar 16
- [Long term adherence to HAART in Senegal].
- Authors: Bastard M, Fall MB, groupe d’étude de la Cohorte ANRS 1215.
- Issue date: 2014 Oct
- Criteria for initiating highly active antiretroviral therapy and short-term immune response among HIV-1-infected patients in Côte d'Ivoire.
- Authors: Diabaté S, Alary M
- Issue date: 2009 Nov
- Preventive measures to prevent loss to follow-up in highly active antiretroviral therapy (HAART): implementing a strategy in Ziguinchor (Casamance, Senegal) in 2014.
- Authors: Randé H, Rouffy D
- Issue date: 2016 May 1
- Estimating treatment efficacy over time: a logistic regression model for binary longitudinal outcomes.
- Authors: Choi L, Dominici F, Zeger SL, Ouyang P
- Issue date: 2005 Sep 30