On Parametric Linear Transformation Model with Left-Truncated and Interval-Censored Data
DOI:
https://doi.org/10.32792/jeps.v10i1.37Abstract
In this paper, a parametric linear transformation model is considered with left truncated and interval censored case I data. The maximum likelihood estimators of the regression parameters are computed. The testing of hypotheses regarding to the parameters are also performed. An extensive Monte Carlo simulation technique was used to compute the proposed estimators along with some of their propertiesReferences
- Buse, A. (1982). The Likelihood Ratio, Wald, and Lagrange Multiplier Test: An Expository Note.
(3a), pp: 153-157.
- Cheng, S, C. Wei, L, J.and Ying, Z. (1995). Analysis of transformation models with censored data.
Biometrika (82) pp: 835-845.
- Kim, J. S. (2003). Efficient estimation for the proportional hazards model with left-truncated and case
interval-censored data. Statistica Sinica, 13, pp: 519-537.
-Lu, M. Li, Y. and LiCS. (2018). Efficient Estimation of Linear Transformation Models for Current
Status Data Via Penalized Splines. Stat Method Res, doi:10.1177/06962280218820406.
- McLain, A .C and Ghosh, S.K. (2013). Efficient Sieve Maximum Likelihood Estimation of Time-
Transformation Models. Journal of Statistical Theory and Practice 7(2), pp: 285-303
- Murphy, S. A, Rossini, a.J and van der Vaart, A. W. (1997). Maximum Likelihood Estimation in the
Proportional Odds Model. 92(4390), pp: 968-976.
- Sun, J and Zhang, Z. (2010). Interval censoring. Stat Methods Med Res, pp: 53-70.
- Shao, J. (1999). Mathmatical Statistics. Springer, pp: 384.
- Shen, P. S.(2014a). Aalens additive risk model for left'truncated and rigrt'censored data. Journal of
Statistical Computation and Simulation,43, pp:112-123
- Xiang, L. Hu, T. (2016). Partially Linear Transformation Cure Models for Interval-censored Data.
Statistical papers (93), pp: 257-269
- Xu, D. Zhao, S. Hu, T. Yu, M and Sun, J. (2018). Regression analysis of informative current status
data with the semiparametric linear transformation model. Lifetime Data Analysis 46(2), pp: 187-202.
- Yanqing, Y. Xikui, W. (2011). Comparison of Wald, Score, and Likelihood Ratio Tests for Response
Adaptive Designs. 10, pp: 553-569.
- Zhang, B. Xingwei, T. Zhang, J. Wang, C and Sun, J.(2013) . Efficient Estimation for Linear
Transformation Models with Current Status Data. Communications in Statistics - Theory and Methods
(17), pp:3191-3203.
- Zeng, D. Mao, L. and Lin, D, Y. (2016). Maximum likelihood estimation for semiparametric
transformation models with interval-censored data. Biometrika (103)2, pp: 253-271.
- Shen, P. S. (2014c). A Generalization of Turnbull's estimator for interval-censored and truncated data.
Communications in Statistics-Theory and Methods, 43, 2958-2972.
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