Ciprian M. Crainiceanu

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We consider the problem of testing null hypotheses that include restrictions on the variance component in a linear mixed model with one variance component. We derive the finite sample and asymptotic distribution of the likelihood ratio test (LRT) and the restricted likelihood ratio test (RLRT). The spectral representations of the LRT and RLRT statistics are(More)
The Sleep Heart Health Study (SHHS) is a comprehensive landmark study of sleep and its impacts on health outcomes. A primary metric of the SHHS is the in-home polysomnogram, which includes two electroencephalographic (EEG) channels for each subject, at two visits. The volume and importance of this data presents enormous challenges for analysis. To address(More)
Subdural electrocorticographic (ECoG) recordings in patients undergoing epilepsy surgery have shown that functional activation is associated with event-related broadband gamma activity in a higher frequency range (>70 Hz) than previously studied in human scalp EEG. To investigate the utility of this high gamma activity (HGA) for mapping language cortex, we(More)
We develop fast fitting methods for generalized functional linear models. The functional predictor is projected onto a large number of smooth eigenvectors and the coefficient function is estimated using penalized spline regression; confidence intervals based on the mixed model framework are obtained. Our method can be applied to many functional data designs(More)
Penalized splines can be viewed as BLUPs in a mixed model framework, which allows the use of mixed model software for smoothing. Thus, software originally developed for Bayesian analysis of mixed models can be used for penalized spline regression. Bayesian inference for nonparametric models enjoys the flexibility of nonparametric models and the exact(More)
A new method (Event-Related Causality, ERC) is proposed for the investigation of functional interactions between brain regions during cognitive processing. ERC estimates the direction, intensity, spectral content, and temporal course of brain activity propagation within a cortical network. ERC is based upon the short-time directed transfer function (SDTF),(More)
Penalized splines have become an increasingly popular tool for nonparametric smoothing because of their use of low-rank spline bases, which makes computations tractable while maintaining accuracy as good as smoothing splines. This article extends penalized spline methodology by both modeling the variance function nonparametrically and using a spatially(More)
BACKGROUND Microcystic macular oedema (MMO) of the retinal inner nuclear layer (INL) has been identified in patients with multiple sclerosis (MS) by use of optical coherence tomography (OCT). We aimed to determine whether MMO of the INL, and increased thickness of the INL are associated with disease activity or disability progression. METHODS This(More)
BACKGROUND AND PURPOSE Detecting incidence and enlargement of lesions is essential in monitoring the progression of MS. In clinical trials, lesion load is observed by manually segmenting and comparing serial MR images, which is time consuming, costly, and prone to inter- and intraobserver variability. Subtracting images from consecutive time points nulls(More)
We introduce models for the analysis of functional data observed at multiple time points. The dynamic behavior of functional data is decomposed into a time-dependent population average, baseline (or static) subject-specific variability, longitudinal (or dynamic) subject-specific variability, subject-visit-specific variability and measurement error. The(More)