Adjusting for confounders in cross-correlation analysis: an application to resting state networks

DOI10.1007/s13571-017-0138-xOpenAlexW2742260313MaRDI QIDQ721615

Rao P. Gullapalli, Anindya Roy, Deepak Nag Ayyala, Junyong Park

Publication date: 19 July 2018

Published in: Sankhyā. Series B (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s13571-017-0138-x

zbMATH Keywords

regions of interestfMRI scansMANOVA formulationresting state networksWald-type test

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to biology and medical sciences; meta analysis (62P10) Hypothesis testing in multivariate analysis (62H15) Image analysis in multivariate analysis (62H35)

Uses Software

• BET

Cites Work

• Unnamed Item
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• The uniform convergence of autocovariances
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• On some test criteria for covariance matrix
• Distribution of likelihood ratio statistic for testing equality of covariance matrices of multivariate Gaussian models
• Asymptotic covariance structure of serial correlations in multivariate time series
• CONSISTENT ESTIMATION OF THE ASYMPTOTIC COVARIANCE STRUCTURE OF MULTIVARIATE SERIAL CORRELATIONS
• An Asymptotic | chi 2 Test for the Equality of Two Correlation Matrices

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