Abstract
Case I interval censored or current status data arise in many areas such as demography, economics, epidemiology and medical science. We introduce a partially linear single-index proportional odds model to analyze these types of data. Polynomial smoothing spline method is applied to estimate the nuisance parameters of our model including the baseline log-odds function and the nonparametric link function with and without monotonicity constraint, respectively. Then, we propose a simultaneous sieve maximum likelihood estimation (SMLE). It is also shown that the resultant estimator of regression parameter vector is asymptotically normal and achieves the semiparametric information bound, considering that the nonparametric link function is truly a spline. A simulation experiment presents the finite sample performance of the proposed estimation method, and an analysis of renal function recovery data is performed for the illustration.
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Pordeli, P., Lu, X. (2016). A Proportional Odds Model for Regression Analysis of Case I Interval-Censored Data. In: Chen, DG., Chen, J., Lu, X., Yi, G., Yu, H. (eds) Advanced Statistical Methods in Data Science. ICSA Book Series in Statistics. Springer, Singapore. https://doi.org/10.1007/978-981-10-2594-5_6
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DOI: https://doi.org/10.1007/978-981-10-2594-5_6
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