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Fig. 2 | BMC Bioinformatics

Fig. 2

From: Propensity scores as a novel method to guide sample allocation and minimize batch effects during the design of high throughput experiments

Fig. 2

Maximum absolute bias under the alternative hypothesis. In order to understand performance of the optimal allocation algorithm under the alternative hypothesis, bias was estimated at a gene (CAPN13) that was associated with both age and HbA1c in the true dataset. Maximum absolute bias represents the maximum absolute difference between the true betas (prior to adding the batch effects) and the beta estimates under each experimental scenario (Table 1) across all of the 1000 simulation iterations. Maximum absolute bias was estimated for \({\upbeta }_{2}\) (panel A, parameter estimate representing the association between age and gene expression), and \({\upbeta }_{3}\) (panel B, parameter estimate representing the association between HbA1c and gene expression. Opt = optimal allocation strategy, R = simple randomization strategy, SR = stratified randomization strategy

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BMC Bioinformatics

ISSN: 1471-2105

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