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The International Journal of Biostatistics

Ed. by Chambaz, Antoine / Hubbard, Alan E. / van der Laan, Mark J.


IMPACT FACTOR 2018: 1.309

CiteScore 2018: 1.11

SCImago Journal Rank (SJR) 2018: 1.325
Source Normalized Impact per Paper (SNIP) 2018: 0.715

Mathematical Citation Quotient (MCQ) 2018: 0.03

Online
ISSN
1557-4679
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Conditional Likelihood Inference in a Case-Cohort Design: An Application to Haplotype Analysis

Olli Saarela
  • International CVD Epidemiology Unit, Department of Health Promotion and Chronic Disease Prevention, National Public Health Institute, Mannerheimintie 166, 00300 Helsinki, Finland
  • Other articles by this author:
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/ Sangita Kulathinal
  • IC Health Scientific Secretariat, Centre for Chronic Disease Control, T-7, Green Park Extension, New Delhi – 110016, India
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2007-01-28 | DOI: https://doi.org/10.2202/1557-4679.1021

Under the setting of a case-cohort design, covariate values are ascertained for a smaller subgroup of the original study cohort which typically is a representative sample from a population. Individuals with a specific event outcome are selected to the second stage study group as cases and an additional subsample is selected to act as a control group. We carry out analysis of such a design using conditional likelihood where the likelihood expression is conditioned on the ascertainment to the second stage study group. Such likelihood expression involves the probability of ascertainment which need to be expressed in terms of the model parameters. We present examples of conditional likelihoods for models for categorical response and time-to-event response. We show that the conditional likelihood inference leads to valid estimation of population parameters. Our application considers joint estimation of haplotype-event association parameters and population haplotype frequencies based on SNP genotype data collected under a case-cohort design.

Keywords: ascertainment correction; case-cohort design; conditional likelihood; haplotypes; multinomial regression; Weibull regression

About the article

Published Online: 2007-01-28


Citation Information: The International Journal of Biostatistics, Volume 3, Issue 1, ISSN (Online) 1557-4679, DOI: https://doi.org/10.2202/1557-4679.1021.

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[1]
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[2]
Olli Saarela, Sangita Kulathinal, and Juha Karvanen
Journal of Probability and Statistics, 2012, Volume 2012, Page 1

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