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Full-Text Articles in Statistics and Probability

Simultaneous Confidence Bands For The Coefficient Function In Functional Regression, Philip T. Reiss Aug 2008

Simultaneous Confidence Bands For The Coefficient Function In Functional Regression, Philip T. Reiss

Philip T. Reiss

No abstract provided.


Inferring Group Differences In Brain Connectivity From Functional Magnetic Resonance Images, Philip T. Reiss Jul 2008

Inferring Group Differences In Brain Connectivity From Functional Magnetic Resonance Images, Philip T. Reiss

Philip T. Reiss

No abstract provided.


Reliability Of Functional Connectivity Networks: How Can We Assess It?, Philip T. Reiss Jul 2008

Reliability Of Functional Connectivity Networks: How Can We Assess It?, Philip T. Reiss

Philip T. Reiss

No abstract provided.


Microproteomics: Analysis Of Protein Diversity In Small Samples, Howard B. Gutstein, Jeffrey S. Morris, Suresh P. Annangudi, Jonathan V. Sweedler Feb 2008

Microproteomics: Analysis Of Protein Diversity In Small Samples, Howard B. Gutstein, Jeffrey S. Morris, Suresh P. Annangudi, Jonathan V. Sweedler

Jeffrey S. Morris

Proteomics, the large-scale study of protein expression in organisms, offers the potential to evaluate global changes in protein expression and their post-translational modifications that take place in response to normal or pathological stimuli. One challenge has been the requirement for substantial amounts of tissue in order to perform comprehensive proteomic characterization. In heterogeneous tissues, such as brain, this has limited the application of proteomic methodologies. Efforts to adapt standard methods of tissue sampling, protein extraction, arraying, and identification are reviewed, with an emphasis on those appropriate to smaller samples ranging in size from several microliters down to single cells. The …


Using The Estimated Penetrances To Determine The Range Of The Underlying Genetic Model In Case-Control Design, Mark J. Meyer, Neal Jeffries, Gang Zheng Jan 2008

Using The Estimated Penetrances To Determine The Range Of The Underlying Genetic Model In Case-Control Design, Mark J. Meyer, Neal Jeffries, Gang Zheng

Mark J Meyer

It is well known that the penetrance cannot be estimated using the retrospective case- control samples without making additional assumptions. In the literature the estimation of the penetrance is based on the assumptions that either the disease is rare or the disease prevalence is known. We propose an alternative approach to estimate the penetrance by assuming an underlying genetic model even though it is unknown. With this assumption, we can obtain the point estimates of the penetrances as functions of the genetic model, from which the range of underlying genetic models can be determined. We examine the performance of our …


Functional Generalized Linear Models With Applications To Neuroimaging, Philip T. Reiss, R. Todd Ogden Dec 2007

Functional Generalized Linear Models With Applications To Neuroimaging, Philip T. Reiss, R. Todd Ogden

Philip T. Reiss

No abstract provided.