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Wavelet-Domain Regression And Predictive Inference In Psychiatric Neuroimaging, Philip T. Reiss, Lan Huo, Yihong Zhao, Clare Kelly, R. Todd Ogden
Wavelet-Domain Regression And Predictive Inference In Psychiatric Neuroimaging, Philip T. Reiss, Lan Huo, Yihong Zhao, Clare Kelly, R. Todd Ogden
Philip T. Reiss
An increasingly important goal of psychiatry is the use of brain imaging data to develop predictive models. Here we present two contributions to statistical methodology for this purpose. First, we propose and compare a set of wavelet-domain procedures for fitting generalized linear models with scalar responses and image predictors: sparse variants of principal component regression and of partial least squares, and the elastic net. Second, we consider assessing the contribution of image predictors over and above available scalar predictors, in particular via permutation tests and an extension of the idea of confounding to the case of functional or image predictors. …
Quantile Rank Maps: A New Tool For Understanding Individual Brain Development, Huaihou Chen, Clare Kelly, F. Xavier Castellanos, Ye He, Xi-Nian Zuo, Philip T. Reiss
Quantile Rank Maps: A New Tool For Understanding Individual Brain Development, Huaihou Chen, Clare Kelly, F. Xavier Castellanos, Ye He, Xi-Nian Zuo, Philip T. Reiss
Philip T. Reiss
We propose a novel method for neurodevelopmental brain mapping that displays how an individual’s values for a quantity of interest compare with age-specific norms. By estimating smoothly age-varying distributions at a set of brain regions of interest, we derive age-dependent region-wise quantile ranks for a given individual, which can be presented in the form of a brain map. Such quantile rank maps could potentially be used for clinical screening. Bootstrap-based confidence intervals are proposed for the quantile rank estimates. We also propose a recalibrated Kolmogorov-Smirnov test for detecting group differences in the age-varying distribution. This test is shown to be …