How to adjust a covariate in a paired Wilcoxon signed-rank test? I am trying to study the difference in a biomarker (ANG7) levels pre and post bariatric surgery (a weight-loss surgery). I am using paired Wilcoxon signed-rank test for this analysis. The test shows there is a significant reduction in ANG7 after the surgery. But the ANG7 is also associated with BMI, so I want to control BMI to say that "there is a significant reduction in ANG7 after the bariatric surgery". My question is, how to control a covariate in a paired data design, what is the appropriate test to do this? Any help is highly appreciated.

To account for covariates, use a regression model instead of a statistical test. It turns out that models generalize tests [1, 2]. In your case you would regress post-surgery ANG7 on pre-surgery ANG7 and BMI. Since you want to generalize the Wilcoxon signed-rank test, use ordinal regression (aka proportional odds logistic regression or POLR).

References
[1] Biostatistics for Biomedical Research course notes. Available online 
[2] Inference of nonparametric tests as linear models. 
More about the covarite BMI:

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*Analyze log(BMI) instead of BMI because BMI is a ratio of two quantities, weight and height (squared).

*Even better, if you have those measurements, you can substitute log(BMI) with log(weight) and log(height).

