Regression Analysis of Sparse Asynchronous Longitudinal Data

Description

Estimation of regression models for sparse asynchronous longitudinal observations, where time-dependent response and covariates are mismatched and observed intermittently within subjects. Kernel weighted estimating equations are used for generalized linear models with either time-invariant or time-dependent coefficients.

Details

Author(s)

Hongyuan Cao, Jason P. Fine, Jialiang Li, Donglin Zeng, and Shannon T. Holloway Maintainer: Shannon T. Holloway <sthollow@ncsu.edu>

References

Cao, H., Zeng, D., and Fine, J. P. (2015) Regression Analysis of sparse asynchronous longitudinal data. Journal of the Royal Statistical Society: Series B, 77, 755-776.

Cao, H., Li, Jialiang, and Fine, J. P. (2015). On last observation carried forward and asynchronous longitudinal regression analysis. Electronic Journal of Statistics, submitted.

See Also

asynchTD, asynchTI, asynchLV

Results