Robust Regression Analysis of Longitudinal Data under Censoring

Somnath Datta

Abstract


We consider regression analysis of longitudinal data when the temporal correlation is modeled by an autoregressive process. Robust R estimators of regression and autoregressive parameters are obtained. Our estimators are valid under censoring caused by detection limits. Efficient computation of the estimators is discussed. Theoretical and simulation studies of the estimators are presented. We analyze a real data set on air pollution using our methodology.

Full Text:

PDF

References


Aalen O.O. (1989). ``A Linear Regression Model for the Analysis of

Lifetimes.'' Statistics in Medicine, 8, 907--925.

Datta S. and Beck J.D. (2014). ``Robust Estimation of Marginal Regression Parameters in Clustered Data.'' Statistical Modelling, 14, 489--501.

Datta S. and Satten G.A. (2002). ``Estimation of Integrated Transition Hazards and Stage Occupation Probabilities for Non-Markov Systems under Stage Dependent Censoring.'' Biometrics, 58, 792--802.

Hettmansperger T.P. and McKean J.W. (2011). Robust Nonparametric Statistical Methods, 2nd ed.. New York: Chapman & Hall.

Toonkel L.E. (1981). Appendix to Environmental Measurements Laboratory Environmental Report, New York: U.S. Department of Energy (available from the National Technical Information Service, U.S. Department of Commerce, Springfield, VA).

Vasudaven M. and Nair M.G. and Sithole M.M. (1996). ``On Estimation for Censored Autoregressive Data.'' Statistics & Probability Letters, 31, 97--105.

Zeger S.L. and Brookmeyer R. (1986). ``Regression Analsis with Censored Autocorrelated Data.'' Journal of the American Statistical Association, 81, 722--729.




DOI: http://dx.doi.org/10.17713/ajs.v46i3-4.666

Refbacks

  • There are currently no refbacks.


@Matthias Templ (usingĀ Open Journal Systems) -- see previous editions at http://www.stat.tugraz.at/AJS/Editions.html