Hostname: page-component-586b7cd67f-t8hqh Total loading time: 0 Render date: 2024-11-25T11:40:23.017Z Has data issue: false hasContentIssue false
  • English
  • Français

THE PERFORMANCE OF SOME STATISTICAL PROCEDURES USED IN CASE-CONTROL STUDIES AND METHYLOMICS

Part of: Parametric inference

Published online by Cambridge University Press:  08 January 2020

RUPERT E. H. KUVEKE Open the ORCID record for RUPERT E. H. KUVEKE [Opens in a new window]
RUPERT E. H. KUVEKE*
Affiliation:
Department of Mathematics and Statistics, La Trobe University, Bundoora3086, Victoria, Australia email [email protected]
Rights & Permissions [Opens in a new window]

Abstract

An abstract is not available for this content so a preview has been provided. As you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'

Keywords

post-model-selection confidence intervalcoverage probabilitygeneral regression modelDNA methylation analysis

MSC classification

Primary: 62F03: Hypothesis testing
Secondary: 92D20: Protein sequences, DNA sequences
Type
Abstracts of Australasian PhD Theses
Information
Bulletin of the Australian Mathematical Society , Volume 101 , Issue 2 , April 2020 , pp. 342 - 344
Copyright
© 2020 Australian Mathematical Publishing Association Inc.

Footnotes

Thesis submitted to La Trobe University in March 2019; degree approved on 14 August 2019; principal supervisor Paul Kabaila, co-supervisor Agus Salim.

References

Hjort, N. L. and Claeskens, G., ‘Frequentist model average estimators’, J. Amer. Statist. Assoc. 98(464) (2003), 879–899.CrossRefGoogle Scholar
Hurvich, C. M. and Tsai, C.-L., ‘The impact of model selection on inference in linear regression’, Amer. Statist. 44(3) (1990), 214–217.Google Scholar
Kabaila, P. and Kuveke, R. E. H., ‘The large sample coverage probability of confidence intervals in general regression models after a preliminary hypothesis test’, Scand. J. Stat. 46(2) (2019), 432–445.CrossRefGoogle Scholar
Korthauer, K. D., Chakraborty, S., Benjamini, Y. and Irizarry, R. A., ‘Detection and accurate false discovery rate control of differentially methylated regions from whole genome bisulfite sequencing’, Biostatistics 20(3) (2018), 367–383.CrossRefGoogle Scholar
Shafi, A., Mitrea, C., Nguyen, T. and Draghici, S., ‘A survey of the approaches for identifying differential methylation using bisulfite sequencing data’, Brief. Bioinform. 19(5) (2018), 737–753.CrossRefGoogle ScholarPubMed