Semiparametric inference of proportional odds model based on randomly truncated data. (English) Zbl 1153.62361
Summary: This paper studies the estimation in the proportional odds model based on randomly truncated data. The proposed estimators for the regression coefficients include a class of minimum distance estimators defined through weighted empirical odds functions. We have investigated the asymptotic properties like the consistency and the limiting distribution of the proposed estimators under mild conditions. The finite sample properties were investigated through simulation study making comparison of some of the estimators in the class. We conclude with an illustration of our proposed method to a well-known AIDS data.
MSC:
| 62N02 | Estimation in survival analysis and censored data |
| 62G05 | Nonparametric estimation |
| 62G20 | Asymptotic properties of nonparametric inference |
| 62F12 | Asymptotic properties of parametric estimators |
| 62E20 | Asymptotic distribution theory in statistics |
Keywords:
proportional odds model; weighted empirical processes; minimum distance; truncation; survivalReferences:
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