Abstract
In Chapter 11 we introduced some contemporary approaches to analyzing longitudinal data for which the responses are continuous measurements. In fact, most people imply continuous responses when they refer to longitudinal data. The analysis of discrete longitudinal data is a relatively new, though active, subject. Readers who are interested in methodological developments may find many unanswered questions in this chapter. The purpose of this chapter is to shed some light on this growing subject. In the statistical literature, the topic may be tagged with clustered or correlated discrete/binary outcomes. So far, most progress has been made toward the binary outcomes; hence, therein lies the focus of this chapter.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
A. Babiker and J. Cuzick. A simple frailty model for family studies with covariates. Statistics in Medicine, 13:1679–1692, 1994.
G.E. Bonney. Regression logistic models for familial disease and other binary traits. Biometrics, 42:611–625, 1986.
C. Cannings, E.A. Thompson, and M.H. Skolnick. Probability functions on complex pedigrees. Advances in Applied Probability, 10:26– 61, 1978.
A.P. Dempster, N.M. Laird, and D.B. Rubin. Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society-B, 39:1–22, 1977.
P.J. Diggle, K.Y. Liang, and S.L. Zeger. Analysis of Longitudinal Data. Oxford Science Publications, Oxford, 1991.
B.G. Ferris, F.E. Speizer, J.D. Spengler, D.W. Dockery, Y.M.M. Bishop, M. Wolfson, and C. Humble. Effects of sulfur oxides and respirable particles on human health. American Review of Respiratory Disease, 120:767–779, 1979.
G.M. Fitzmaurice and N.M. Laird. A likelihood-based method for analysing longitudinal binary responses. Biometrika, 80:141–151, 1993.
G.M. Fitzmaurice, N.M. Laird, and A.G. Rotnitzky. Regression models for discrete longitudinal responses. Statistical Science, 8:284–299, 1993.
V.P. Godambe. An optimum property of regular maximum likelihood estimation. Annals of Mathematical Statistics, 31:1209–1211, 1960.
D.G. Kleinbaum, L.L. Kupper, and K.E. Muller. Applied Regression Analysis and Other Multivariable Methods. Duxbury Press, Belmont, California, 1988.
K.Y. Liang and S.L. Zeger. Longitudinal data analysis using generalized linear models. Biometrika, 73:13–22, 1986.
K.Y. Liang, S.L. Zeger, and B. Qaqish. Multivariate regression analyses for categorical data. Journal of the Royal Statistical Society-B, 54:3–24, 1992.
P. McCullagh and J.A. Nelder. Generalized Linear Models. Chapman and Hall, London, 1989.
R.M. Royall. Model robust inference using maximum likelihood estimators. International Statistical Review, 54:221–226, 1986.
J. Scourfield, D.E. Stevens, and K.R. Merikangas. Substance abuse, comorbidity, and sensation seeking: gender difference. Comprehensive Psychiatry, 37:384–392, 1996.
A. Sommer, J. Katz, and I. Tarwotjo. Increased risk of respiratory disease and diarrhea in children with preexisting mild vitamin A deficiency. American Journal of Clinical Nutrition, 40:1090–1095, 1984.
A. Sommer, I. Tarwotjo, G. Hussaini, and D. Susanto. Increased mortality in children with mild vitamin A deficiency. Lancet, 2:585– 588, 1983.
A. Sommer, J.M. Tielsch, J. Katz, H.A. Quigley, J.D. Gottsch, J.C. Javitt, J.F. Martone, R.M. Royall, K.A. Witt, and S. Ezrine. Racial differences in the cause-specific prevalence of blindness in east Baltimore. New England Journal of Medicine, 325:1412–1417, 1991.
J.H. Ware, D.W. Dockery, A. Spiro, F.E. Speizer, and B.G. Ferris. Passive smoking, gas cooking, and respiratory health of children living in six cities. American Review of Respiratory Disease, 129:366–374, 1984.
S.L. Zeger, K.Y. Liang, and P.S. Albert. Models for longitudinal data: A generalized estimating equation approach. Biometrics, 44:1049– 1060, 1988.
H.P. Zhang. Classification trees for multiple binary responses. Journal of the American Statistical Association, 93:180–193, 1998a.
H.P. Zhang and Y. Ye. A tree-based method for modeling a mul-tivariate ordinal response. Statistics and Its Interface, 1:169–178, 2008.
L.P. Zhao and R.L. Prentice. Correlated binary regression using a quadratic exponential model. Biometrika, 77:642–648, 1990.
K.Y. Liang and S.L. Zeger. Longitudinal data analysis using generalized linear models. Biometrika, 73:13–22, 1986.
P. McCullagh and J.A. Nelder. Generalized Linear Models. Chapman and Hall, London, 1989.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2010 Springer Science+Business Media, LLC
About this chapter
Cite this chapter
Zhang, H., Singer, B.H. (2010). Analysis of Multiple Discrete Responses. In: Recursive Partitioning and Applications. Springer Series in Statistics, vol 0. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-6824-1_12
Download citation
DOI: https://doi.org/10.1007/978-1-4419-6824-1_12
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4419-6823-4
Online ISBN: 978-1-4419-6824-1
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)