Spatiotemporal linear mixed effects modeling for the mass-univariate analysis of longitudinal neuroimage data

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Spatiotemporal linear mixed effects modeling for the mass-univariate analysis of longitudinal neuroimage data

We present an extension of the Linear Mixed Effects (LME) modeling approach to be applied to the mass-univariate analysis of longitudinal neuroimaging (LNI) data. The proposed method, called spatiotemporal LME or ST-LME, builds on the flexible LME framework and exploits the spatial structure in image data. We instantiated ST-LME for the analysis of cortical surface measurements (e.g. thickness)...

متن کامل

Statistical analysis of longitudinal neuroimage data with Linear Mixed Effects models

Longitudinal neuroimaging (LNI) studies are rapidly becoming more prevalent and growing in size. Today, no standardized computational tools exist for the analysis of LNI data and widely used methods are sub-optimal for the types of data encountered in real-life studies. Linear Mixed Effects (LME) modeling, a mature approach well known in the statistics community, offers a powerful and versatile...

متن کامل

Statistical Analysis of Longitudinal Neuroimage Data with Linear Mixed Effects Models Jorge

Statistical Analysis of Longitudinal Neuroimage Data with Linear Mixed Effects Models Jorge L. Bernal-Rusiel, Douglas N. Greve, Martin Reuter , Bruce Fischl, and Mert R. Sabuncu; for the Alzheimer’s Disease Neuroimaging Initiative* 1 Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School/Massachusetts General Hospital, Charlestown, MA Department of Mechanical Engineering, M...

متن کامل

Event time analysis of longitudinal neuroimage data

This paper presents a method for the statistical analysis of the associations between longitudinal neuroimaging measurements, e.g., of cortical thickness, and the timing of a clinical event of interest, e.g., disease onset. The proposed approach consists of two steps, the first of which employs a linear mixed effects (LME) model to capture temporal variation in serial imaging data. The second s...

متن کامل

Longitudinal Data: Simple Univariate Methods of Analysis

These notes descibe various simple models and methods for analysis of longitudinal data and show how the analyses can be carried out using SAS. The descriptions require some knowledge of analysis of variance, also with random eeects as in split-plot experiments, in particular. Knowledge of multivariate analysis is not required, and the plain multivariate analysis of variance , treating each ser...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: NeuroImage

سال: 2013

ISSN: 1053-8119

DOI: 10.1016/j.neuroimage.2013.05.049