Familial Longitudinal Models for Binary Data
In the familial longitudinal setup, binary responses along with a set of multidimensional time-dependent covariates are collected from the members of a large number of independent families. For example, in a clinical study, the asthma status of each of the family members of a large number of independent families may be collected every year over a period of four years. Also, the covariates such as gender, age, education level, and life style of the individual member may be collected. In this setup, it is likely that the responses from the members of the same family at a given year will be correlated. This is due to the fact that every member of the family shares certain common family effects which are latent or invisible. Also, the repeated asthma status collected over several years will be longitudinally correlated. It is of interest to take these two types of familial and longitudinal correlations into account and then find the effects of the covariates on the responses.
KeywordsBinary Data Binary Response Good Linear Unbiased Prediction Asymptotic Covariance Matrix Independent Family
Unable to display preview. Download preview PDF.
- 1.Best, J. A, Brown, K. S., Cameron, R., Manske, S. M., & Santi, S. (1995). Gender and predisposing attributes as predictors of smoking onset: Implications for theory and practice. J. Health Educ., 26, S52−−S60.Google Scholar
- 2.Brown, K. S. & Cameron, R. (1997). Long-term evaluation of an elementary and secondary school smoking intervention. Final Report to the National Health Research and Development Program (Canada).Google Scholar
- 3.Breslow, N. E. & Clayton, D. G. (1993). Approximate inference in generalized linear mixed models. . J. Amer. Statist. Assoc., 88, 9−25.Google Scholar
- 6.Fahrmeier, L. & Tutz, G. T.(1994): Multivariate Statistical Modelling Based on Generalized Linear Models, New York: Springer-Verlag.Google Scholar
- 9.Mardia, K. V., Kent, J. T. & Bibby, J. M. (1979). Multivariate Analysis. London: Academic Press.Google Scholar