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!
) of the secondary risk factor and the primary risk factor.
We used conditional logistic regression to model the risk of IL-6 on delirium incidence.
Simulation was used to generate a sample of cohort data on which unconditional multivariable logistic regression was used, and the results were compared to those of the conditional logistic regression.
The main exposure was IL-6 concentration (pg/ml) from blood sampled at three time points before delirium occurred.
We used nonparametric signed ranked test to test for the median of the paired differences.
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.
The origin of the NCC design came from the desire to reduce computational costs of collecting and analyzing data for all subjects in a cohort study.
Mantel proposed to sample the controls randomly from a finite cohort, and originally called this design “synthetic” case-control study .