A sequential logistic regression classifier based on mixed effects with applications to longitudinal data. (English) Zbl 1468.62231
Summary: Making an early classification in longitudinal data is highly desirable. For this purpose, a sequential classifier that incorporates a neutral zone framework is proposed. The classification procedure evaluates each subject sequentially at each longitudinal time point. If there is not adequate confidence in making a classification at a given time point, the decision will wait until the next time point where another measurement is collected. This process continues until there is enough confidence of making a classification or until the last time point where data can be collected is reached. It is demonstrated that the proposed sequential classifier maintains competitive error rates while reducing the overall cost when the cost of time is taken into account. The classifier is applied to a real example of identifying patients that are vulnerable to kidney dysfunction on the basis of up to 7 blood draws sequentially taken from each patient.
MSC:
| 62-08 | Computational methods for problems pertaining to statistics |
| 62H30 | Classification and discrimination; cluster analysis (statistical aspects) |
| 62J12 | Generalized linear models (logistic models) |
| 62P12 | Applications of statistics to environmental and related topics |
References:
| [1] | Benecke, S.; Jeske, D. R.; Reugger, P.; Borneman, J., Bayes neutral zone classifiers with applications to nonparametric unsupervised settings, J. Agric. Biol. Environ. Stat., 18, 39-52, (2013) · Zbl 1302.62243 |
| [2] | Harville, D. A., Extension of the Gauss-Markov theorem to include the estimation of random effects, Ann. Statist., 4, 384-395, (1976) · Zbl 0323.62043 |
| [3] | Harville, D. A., Maximum likelihood approaches to variance component estimation and to related problems, J. Amer. Statist. Assoc., 72, 320-340, (1977) · Zbl 0373.62040 |
| [4] | Henderson, C. R., Estimation of genetic parameters, Ann. Math. Statist., 21, 309-310, (1950) |
| [5] | James, G. M., Generalized linear models with functional predictor variables, J. R. Stat. Soc. Ser. B, 64, 411-432, (2002) · Zbl 1090.62070 |
| [6] | James, G. M.; Hastie, T. J., Functional linear discriminant analysis for irregularly sampled curves, J. R. Stat. Soc. Ser. B, 63, 533-550, (2001) · Zbl 0989.62036 |
| [7] | Jeske, D. R.; Liu, Z.; Bent, E.; Borneman, J., Classification rules that include neutral zones and their application to microbial community profiling, Comm. Statist. Theory Methods, 36, 1965-1980, (2007) · Zbl 1124.62078 |
| [8] | Luts, J.; Molenberghs, G.; Verbeke, G.; Van Huffel, S.; Suykens, J. A.K., A mixed effects least squares support vector machine model for classification of longitudinal data, Comput. Statist. Data Anal., 56, 611-628, (2012) · Zbl 1239.62077 |
| [9] | Marshall, G.; Barón, A. E., Linear discriminant models for unbalanced longitudinal data, Stat. Med., 19, 1969-1981, (2000) |
| [10] | Verbeke, G.; Lesaffre, E., A linear mixed-effects model with heterogeneity in the random-effects population, J. Amer. Statist. Assoc., 91, 433, 217-221, (1996) · Zbl 0870.62057 |
| [11] | Wu, H.; Zhang, J., Nonparametric regression methods for longitudinal data analysis: mixed effects modeling approaches, (2006), Wiley-Interscience · Zbl 1127.62041 |
| [12] | Yu, H.; Jeske, D. R.; Ruegger, P.; Borneman, J., A three-class neutral zone classifier using a decision-theoretic approach with application to dan array analyses, J. Agric. Biol. Environ. Stat., 15, 474-490, (2010) · Zbl 1306.62371 |
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.
