Conditional Likelihood Inference in a Case-Cohort Design: An Application to Haplotype Analysis

Saarela Olli and Kulathinal Sangita
Additional contact information
Saarela Olli: International CVD Epidemiology Unit, Department of Health Promotion and Chronic Disease Prevention, National Public Health Institute, Mannerheimintie 166, 00300 Helsinki, Finland
Kulathinal Sangita: IC Health Scientific Secretariat, Centre for Chronic Disease Control, T-7, Green Park Extension, New Delhi – 110016, India

The International Journal of Biostatistics, 2007, vol. 3, issue 1, 23

Abstract: 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 (search for similar items in EconPapers)
Date: 2007
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.2202/1557-4679.1021 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bpj:ijbist:v:3:y:2007:i:1:n:1

Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/ijb/html

DOI: 10.2202/1557-4679.1021

Access Statistics for this article

The International Journal of Biostatistics is currently edited by Antoine Chambaz, Alan E. Hubbard and Mark J. van der Laan

More articles in The International Journal of Biostatistics from De Gruyter
Bibliographic data for series maintained by Peter Golla ().