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- Functional connectivity (2)
- Functional data analysis (2)
- Model selection (2)
- Quantile regression (2)
- Resting state (2)
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- Seed region (2)
- Aging (1)
- Alzheimer's Disease (1)
- Developmental trajectory (1)
- Function-on-scalar regression (1)
- HIV epidemiology (1)
- HIV/AIDS (1)
- Incidecne (1)
- Massively parallel nonparametrics (1)
- Pointwise degrees of freedom (1)
- Prevalecne (1)
- Prevalence (1)
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- Publication
Articles 1 - 7 of 7
Full-Text Articles in Medical Sciences
Introducing Functional Data Analysis To Neuroimaging, And Vice Versa, Philip T. Reiss
Introducing Functional Data Analysis To Neuroimaging, And Vice Versa, Philip T. Reiss
Philip T. Reiss
No abstract provided.
Massively Parallel Nonparametrics [Hds 2011 Slides], Philip T. Reiss, Lei Huang
Massively Parallel Nonparametrics [Hds 2011 Slides], Philip T. Reiss, Lei Huang
Philip T. Reiss
No abstract provided.
Flexible Dependence Of Functional Responses On Scalar Predictors, Philip T. Reiss, Lei Huang
Flexible Dependence Of Functional Responses On Scalar Predictors, Philip T. Reiss, Lei Huang
Philip T. Reiss
No abstract provided.
Extracting Information From Functional Connectivity Maps Via Function-On-Scalar Regression, Philip T. Reiss, Maarten Mennes, Eva Petkova, Lei Huang, Matthew J. Hoptman, Bharat B. Biswal, Stanley J. Colcombe, Xi-Nian Zuo, Michael P. Milham
Extracting Information From Functional Connectivity Maps Via Function-On-Scalar Regression, Philip T. Reiss, Maarten Mennes, Eva Petkova, Lei Huang, Matthew J. Hoptman, Bharat B. Biswal, Stanley J. Colcombe, Xi-Nian Zuo, Michael P. Milham
Lei Huang
Functional connectivity of an individual human brain is often studied by acquiring a resting state functional magnetic resonance imaging scan, and mapping the correlation of each voxel's BOLD time series with that of a seed region. As large collections of such maps become available, including multisite data sets, there is an increasing need for ways to distill the information in these maps in a readily visualized form. Here we propose a two-step analytic strategy. First, we construct connectivity-distance profiles, which summarize the connectivity of each voxel in the brain as a function of distance from the seed, a functional relationship …
National Estimates Of The Prevalence Of Alzheimer's Disease In The United States, Ron Brookmeyer, Denis Evans, Liesi Hebert, Langa Kenneth, Heeringa Steven, Plassman Brenda, Kukull Kenneth
National Estimates Of The Prevalence Of Alzheimer's Disease In The United States, Ron Brookmeyer, Denis Evans, Liesi Hebert, Langa Kenneth, Heeringa Steven, Plassman Brenda, Kukull Kenneth
Ron Brookmeyer
Several methods of estimating prevalence of dementia are presented in this article. For both Brookmeyer and the Chicago Health and Aging project (CHAP), the estimates of prevalence are derived statistically, forward calculating from incidence and survival figures. The choice of incidence rates on which to build the estimates may be critical. Brookmeyer used incidence rates from several published studies, whereas the CHAP investigators applied the incidence rates observed in their own cohort. The Aging, Demographics, and Memory Study (ADAMS) and the East Boston Senior Health Project (EBSHP) were sample surveys designed to ascertain the prevalence of Alzheimer’s disease and dementia. …
Statistical Considerations In Determining Hiv Incidence From Changes In Hiv Prevalence, Ron Brookmeyer, Jacob Konikoff
Statistical Considerations In Determining Hiv Incidence From Changes In Hiv Prevalence, Ron Brookmeyer, Jacob Konikoff
Ron Brookmeyer
The development of methods for estimating HIV incidence is critical for tracking the epidemic and for designing, targeting and evaluating HIV prevention efforts. One method for estimating incidence is based on changes in HIV prevalence. That method is attracting increased attention because national population-based HIV prevalence surveys, such as Demographic and Health Surveys, are being conducted throughout the world. Here, we consider some statistical issues associated with estimating HIV incidence from two population-based HIV prevalence surveys conducted at two different points in time. We show that the incidence estimator depends on the relative survival rate. We evaluate the sensitivity of …
Extracting Information From Functional Connectivity Maps Via Function-On-Scalar Regression, Philip T. Reiss, Maarten Mennes, Eva Petkova, Lei Huang, Matthew J. Hoptman, Bharat B. Biswal, Stanley J. Colcombe, Xi-Nian Zuo, Michael P. Milham
Extracting Information From Functional Connectivity Maps Via Function-On-Scalar Regression, Philip T. Reiss, Maarten Mennes, Eva Petkova, Lei Huang, Matthew J. Hoptman, Bharat B. Biswal, Stanley J. Colcombe, Xi-Nian Zuo, Michael P. Milham
Philip T. Reiss
Functional connectivity of an individual human brain is often studied by acquiring a resting state functional magnetic resonance imaging scan, and mapping the correlation of each voxel's BOLD time series with that of a seed region. As large collections of such maps become available, including multisite data sets, there is an increasing need for ways to distill the information in these maps in a readily visualized form. Here we propose a two-step analytic strategy. First, we construct connectivity-distance profiles, which summarize the connectivity of each voxel in the brain as a function of distance from the seed, a functional relationship …