179
Views
0
CrossRef citations to date
0
Altmetric
Articles

Inference on semi-parametric transformation model with a pairwise likelihood based on left-truncated and interval-censored data

, &
Pages 38-55 | Received 11 Feb 2022, Accepted 14 Oct 2022, Published online: 26 Oct 2022

References

  • Chen, K., Jin, Z., and Ying, Z. (2002), ‘Semiparametric Analysis of Transformation Models with Censored Data’, Biometrika, 89, 659–668.
  • De Gruttola, V., and Lagakos, S. (1989), ‘Analysis of Doubly-censored Survival Data, with Application to AIDS’, Biometrics, 45, 1–11.
  • Efron, B., and Tibshirani, R.J. (1993), An Introduction to the Bootstrap, CRC Press.
  • Fine, J., Ying, Z., and Wei, L. (1998), ‘On the Linear Transformation Model for Censored Data’, Biometrika, 85, 980–986.
  • Frydman, H.A. (1994), ‘A Note on Nonparametric Estimation of the Distribution Function from Interval-censored and Truncated Observations’, Journal of the Royal Statistical Society, Series B, 56, 71–74.
  • Gao, F., and Chan, K.C.G. (2019), ‘Semiparametric Regression Analysis of Length-biased Interval-censored Data’, Biometrics, 75, 121–132.
  • Hazelrig, J.B., Turner, M.E., and Blackstone, E.H. (1982), ‘Parametric Survival Analysis Combining Longitudinal and Cross-sectional-censored and Interval-censored Data with Concomitant Information’, Biometrics, 38, 1–15.
  • Huang, J. (1996), ‘Efficient Estimation for the Proportional Hazards Model with Interval Censoring’, The Annals of Statistics, 24, 540–568.
  • Huang, C.Y., and Qin, J. (2012), ‘Composite Partial Likelihood Estimation Under Length-biased Sampling, with Application to A Prevalent Cohort Study of Dementia’, Journal of the American Statistical Association, 107, 946–957.
  • Huang, C.Y., and Qin, J. (2013), ‘Semiparametric Estimation for the Additive Hazards Model with Left-truncated and Right-censored Data’, Biometrika, 100, 877–888.
  • Huang, J., and Rossini, A. (1997), ‘Sieve Estimation for the Proportional-odds Failure-time Regression Model with Interval Censoring’, Journal of the American Statistical Association, 92, 960–967.
  • Huang, J., and Wellner, J.A. (1993), 'Regression Models with Interval Censoring', in Probability Theory and Mathematical Statistics, pp. 269–296.
  • Huang, J., and Wellner, J.A. (1997), ‘Interval Censored Survival Data: A Review of Recent Progress’, in Biostatistics Proceedings of the First Seattle Symposium, pp. 123–169.
  • Kalbfleisch, J.D., and Prentice, R.L. (2011), The Statistical Analysis of Failure Time Data, John Wiley & Sons.
  • Kim, J.S. (2003), ‘Efficient Estimation for the Proportional Hazards Model with Left-truncated and Case 1 Interval-censored Data’, Statistica Sinica, 13, 519–537.
  • Kim, M.Y., De Gruttola, V., and Lagakos, S. (1993), ‘Analyzing Doubly Censored Data with Covariates with Application to AIDS’, Biometrics, 49, 13–22.
  • Li, J., and Ma, S. (2010), ‘Interval-censored Data with Repeated Measurements and a Cured Subgroup’, Journal of the Royal Statistical Society, Series C, 59, 693–705.
  • Liang, K.Y., and Qin, J. (2000), ‘Regression Analysis Under Non-standard Situations: A Pairwise Pseudo Likelihood Approach’, Journal of the Royal Statistical Society, Series B, 62, 773–786.
  • Louis, T.A. (1982), ‘Finding the Observed Information Matrix When Using the EM Algorithm’, Journal of the Royal Statistical Society, Series B, 44, 226–233.
  • Marshall, M.L. (1974), ‘Fitting the Two-term Mixed Exponential and Two-parameter Lognormal Distributions to Grouped and Censored Data’, Applied Statistics, 23, 313–322.
  • Odell, P.M., Anderson, K.M., and D'Agostino, R.B. (1992), ‘Maximum Likelihood Estimation for Interval-censored Data Using a Weibull-based Accelerated Failure Time Model’, Biometrics, 48, 951–959.
  • Pan, W., and Chappell, R. (1999), ‘A Note on Inconsistency of NPMLE of the Distribution Function from Left Truncated and Case I Interval-censored Data’, Lifetime Data Analysis, 5, 281–291.
  • Pan, W., and Chappell, R. (2002), ‘Estimation in the Cox Proportional Hazards Model with Left-truncated and Interval-censored Data’, Biometrics, 58, 64–70.
  • Rossini, A., and Tsiatis, A. (1996), ‘A Semiparametric Proportional Odds Regression Model for the Analysis of Current Status Data’, Journal of the American Statistical Association, 91, 713–721.
  • Shen, X. (1998), ‘Proportional Odds Regression and Sieve Maximum Likelihood Estimation’, Biometrika, 85, 165–177.
  • Shen, P. (2014), ‘Proportional Hazards Regression with Interval-censored and Left-truncated Data’, Journal of Statistical Computation and Simulation, 84, 264–272.
  • Shen, P., Chen, H., Pan, W., and Chen, C. (2019), ‘Semiparametric Regression Analysis for Left-truncated and Interval-censored Data without or with a Cure Fraction’, Computational Statistics & Data Analysis, 140, 74–87.
  • Sun, J. (2006), The Statistical Analysis of Interval-censored Failure Time Data, New York: Springer.
  • Wang, P., Li, D., and Sun, J. (2021), ‘A Pairwise Pseudo-likelihood Approach for Left-truncated and Interval-censored Data Under the Cox Model’, Biometrics, 77, 1303–1314.
  • Wang, P., Tong, X., Zhao, S., and Sun, J. (2015), ‘Efficient Estimation for the Additive Hazards Model in the Presence of Left-truncation and Interval Censoring’, Statistics and Its Interface, 8, 391–402.
  • Wang, P., Zhao, H., Du, M., and Sun, J. (2018), ‘Inference on Semiparametric Transformation Model with General Interval-censored Failure Time Data’, Journal of Nonparametric Statistics, 30, 758–773.
  • Wu, F., Kim, S., Qin, J., Saran, R., and Li, Y. (2018), ‘A Pairwise Likelihood Augmented Cox Estimator for Left-truncated Data’, Biometrics, 74, 100–108.
  • Xu, D., Zhao, S., Hu, T., and Sun, J. (2019), ‘Regression Analysis of Informatively Interval-censored Failure Time Data with Semiparametric Linear Transformation Model’, Journal of Nonparametric Statistics, 31, 663–679.
  • Zeng, D., Mao, L., and Lin, D. (2016), ‘Maximum Likelihood Estimation for Semiparametric Transformation Models with Interval-censored Data’, Biometrika, 103, 253–271.
  • Zhang, Z., Sun, L., Zhao, X., and Sun, J. (2005), ‘Regression Analysis of Interval-censored Failure Time Data with Linear Transformation Models’, Canadian Journal of Statistics, 33, 61–70.
  • Zhang, Z., and Zhao, Y. (2013), ‘Empirical Likelihood for Linear Transformation Models with Interval-censored Failure Time Data’, Journal of Multivariate Analysis, 116, 398–409.
  • Zhou, Q., Hu, T., and Sun, J. (2017), ‘A Sieve Semiparametric Maximum Likelihood Approach for Regression Analysis of Bivariate Interval-censored Failure Time Data’, Journal of the American Statistical Association, 112, 664–672.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.