Skip to main content
Figure 5 | BMC Medical Research Methodology

Figure 5

From: Detecting and correcting the bias of unmeasured factors using perturbation analysis: a data-mining approach

Figure 5

Perturbation diagnostics for a hypothetical data ( n  = 200) taken from Table  1 (A: perturbation adjustment for positive confounding; B: perturbation adjustment for negative confounding). The perturbation variables have an f PV of 0.025 and are dependent of one another through a first-order Markov chain with an odds ratio of 10.0 between successive perturbation variables. Bootstrap was done for a total of 10000 times.

Back to article page