A Simulation Study of the Cox Proportional Hazards Model and the Nested Case-Control Study Design
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ndltd-OhioLink-oai-etd.ohiolink.edu-ucin13073214952021-08-03T06:14:49Z A Simulation Study of the Cox Proportional Hazards Model and the Nested Case-Control Study Design Bertke, Stephen J. Statistics cox proportional hazards nested case control efficiency bias measurement error chen's estimate The Cox proportional hazards model is commonly used to analyze the exposure-response relationship in occupational cohort studies. This analysis involves identifying cases (those who experience the outcome of interest) and forming risk-sets for each case. The risk-set for a case is the set of cohort members whose failure times are at least as large as the case’s failure time and are under observation immediately before the case’s failure time. Thomas proposed the idea of randomly sampling controls from each risk-set to use for analysis, which results in a nested case-control study. It has been shown that the analysis using the full risk-sets and the analysis using the sampled risk-sets produce asymptotically unbiased results. Also, the asymptotic relative efficiency between analyzing the full risk-sets and using Thomas’ estimator to analyze the sampled risk-sets (sampling m controls per case) is m/(m+1) when there is no exposure-response relationship. A simulation study investigated the non-asymptotic properties of the nested case-control study design and found that the relative efficiency decreased as the number of cases in the cohort decreased, the true exposure-response parameter increased, and the skewness of the exposure distribution of the risk-sets increased. There also appeared to be some bias in a nested case-control study and this bias tended to be away from the null, however, this was not a major issue. In fact, when 10 or more controls were matched with each case, the bias was never more than 10%. A second simulation study compared the estimates obtained from a nested case-control analysis for a given cohort to the estimate obtained from analyzing the full cohort with Cox proportional hazards regression. The nested case-control estimate generally overestimated the full cohort estimate and the size of this discrepancy varied from cohort to cohort. Also, the sample variance of the estimates from a nested case-control study for a given cohort decreased dramatically as the case: control ratio increased. An alternative estimator for a nested case-control study was proposed by Chen and a set of simulations compared the performance of this estimator to that of the traditional Thomas estimator. Chen’s estimator requires the user to define a function named phi. It was shown that the performance of Chen’s estimator is somewhat sensitive to the definition of phi. In particular, if the support of phi was small, Chen’s estimator performed poorly. However, for larger definitions of the support of phi, Chen’s estimator performed comparable, if not better than Thomas’ estimator in terms of the bias and relative efficiency. Finally, a simulation study investigated the effect of classical measurement error on the Cox proportional hazards model. The simulations suggest that the introduction of measurement error may change the perceived shape of the exposure-response curve. In fact, the curve was more likely to level-off in the high exposure range which is commonly seen in occupational cohort studies and this effect became more severe as the magnitude of the error increased. 2011-09-19 English text University of Cincinnati / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=ucin1307321495 http://rave.ohiolink.edu/etdc/view?acc_num=ucin1307321495 unrestricted This thesis or dissertation is protected by copyright: some rights reserved. It is licensed for use under a Creative Commons license. Specific terms and permissions are available from this document's record in the OhioLINK ETD Center. |
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language |
English |
sources |
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topic |
Statistics cox proportional hazards nested case control efficiency bias measurement error chen's estimate |
spellingShingle |
Statistics cox proportional hazards nested case control efficiency bias measurement error chen's estimate Bertke, Stephen J. A Simulation Study of the Cox Proportional Hazards Model and the Nested Case-Control Study Design |
author |
Bertke, Stephen J. |
author_facet |
Bertke, Stephen J. |
author_sort |
Bertke, Stephen J. |
title |
A Simulation Study of the Cox Proportional Hazards Model and the Nested Case-Control Study Design |
title_short |
A Simulation Study of the Cox Proportional Hazards Model and the Nested Case-Control Study Design |
title_full |
A Simulation Study of the Cox Proportional Hazards Model and the Nested Case-Control Study Design |
title_fullStr |
A Simulation Study of the Cox Proportional Hazards Model and the Nested Case-Control Study Design |
title_full_unstemmed |
A Simulation Study of the Cox Proportional Hazards Model and the Nested Case-Control Study Design |
title_sort |
simulation study of the cox proportional hazards model and the nested case-control study design |
publisher |
University of Cincinnati / OhioLINK |
publishDate |
2011 |
url |
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1307321495 |
work_keys_str_mv |
AT bertkestephenj asimulationstudyofthecoxproportionalhazardsmodelandthenestedcasecontrolstudydesign AT bertkestephenj simulationstudyofthecoxproportionalhazardsmodelandthenestedcasecontrolstudydesign |
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