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Semiparametric likelihood‐based inference for biased and truncated data when the total sample size is known

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  • Gang Li
  • Jing Qin

Abstract

Biased and truncated data arise in many practical areas. Many efficient statistical methods have been studied in the literature. This paper discusses likelihood‐based inferences for the two types of data in the presence of auxiliary information of known total sample size. It is shown that this information improves inference about the underlying distribution and its parameters in which we are interested. A semiparametric likelihood ratio confidence interval technique is employed. Also some simulation results are reported.

Suggested Citation

  • Gang Li & Jing Qin, 1998. "Semiparametric likelihood‐based inference for biased and truncated data when the total sample size is known," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 60(1), pages 243-254.
    • Handle: RePEc:bla:jorssb:v:60:y:1998:i:1:p:243-254
    DOI: 10.1111/1467-9868.00122
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    Cited by:

    1. Esmeralda Ramalho, 2004. "Binary models with misclassification in the variable of interest," Economics Working Papers 3_2004, University of Évora, Department of Economics (Portugal).
    2. Esmerelda A. Ramalho & Richard Smith, 2003. "Discrete choice non-response," CeMMAP working papers 07/03, Institute for Fiscal Studies.
    3. José Cristóbal & José Alcalá, 2001. "An overview of nonparametric contributions to the problem of functional estimation from biased data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 10(2), pages 309-332, December.
    4. Yidan Shi & Leilei Zeng & Mary E. Thompson & Suzanne L. Tyas, 2021. "Augmented likelihood for incorporating auxiliary information into left-truncated data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 27(3), pages 460-480, July.
    5. Esmeralda A. Ramalho & Richard J. Smith, 2013. "Discrete Choice Non-Response," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 80(1), pages 343-364.

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