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Neonatal Brain Volumetric Studies: Regression Analysis and Interpretation: In Reply

lap with the influence of a different covariate, which makes the combination tested crucial. In regard to the regression model, it is a good exploratory approach to enter and test the possible covariates initially 1 by 1. This can be followed by a stepwise regression that involves the more statistically significant ones. It is safer to use larger P values (eg, .1 or .2) for entry criteria in the stepwise regression than for exit (eg, .05 or .1). The covariates that have the most influence on the primary outcome (cumulative effect if 1) should stay in the model, and then the primary outcome measurements can be adjusted accordingly. It is important to note whether comparisons for the primary outcome were statistically significant before and after the regression analysis. With respect to the above and in terms of cortical volume, along with postmenstrual age at scan, scaling effects and size differences between subjects and groups at scan could have an influence on neonatal cerebral volumes and be a significant covariate. Also, uncomplicated germinal matrix-intraventricular hemorrhage could be a significant covariate for the cortical volume.3 For the reader, understanding is benefited from adequate details on the demographic and clinical characteristics of the subjects. The presentation of the raw data and their statistics, before adjustments, is also essential for the interpretation of neonatal brain volume studies.