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Nonetheless, with careful selection of the match algorithm, match factors, and analysis methods, this design is cost effective and, for our study, yields estimates that are similar to those from a prospective cohort study design.Nested case-control study (NCC) design within a prospective cohort study is used when the outcome data are available for all subjects, but the exposure of interest has not been collected, and is difficult or prohibitively expensive to obtain for all subjects [1,2,3].The counter-matched study design is used to specifically assess the impact of this risk factor; it is especially good for assessing the potential interaction (effect modification!
If the match procedure is carried out properly, and the selected controls are representative of the controls in the cohort study, then NCC loses little efficiency compared to the full cohort analysis .
NCC could offer better validity than the full cohort study because the match procedure allows for adjustment for both measured, and for unmeasured confounders .
In terms of the interpretation of the analysis results, in the case of a binary outcome and a binary exposure, one can compute the odds ratio for the outcome, or the odds ratio for the exposure, and these two odds ratio estimators have been shown to be equivalent .
However, in the case of a binary outcome, and a continuous exposure (such as in biomarker discovery studies where the exposure is the level of putative marker concentration in plasma), it is not clear that the outcome odds ratio is equivalent to the mean or median of the paired differences (between the case and control in a selected pair).
For a NCC with matching, Cornfield , Mantel and Haenszel , Breslow , Rubin , Rothman and Greenland  have pointed out that the match algorithm, the match factors, and their association with the outcome and the exposure play a critical role in validity and efficiency.
In addition, caution is needed to avoid overmatching, since this could introduce bias and inefficiency into the estimators.
Subsequently the use of matching to select the controls allowed for the implementation of the conditional likelihood functions and the demonstration of asymptotic consistency and efficiency property of the risk ratio estimates .
NCC has been used in many biomarker studies where it is expensive to collect and process biological samples for all subjects in the cohort study.
At the crux of the NCC design is the quality of the match procedure and the appropriate analysis that accounts for the match design.
Algorithms used in match procedures such as the greedy algorithm, propensity score algorithm, and optimal algorithm are some of the most often used in NCC studies.