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Articles 1 - 6 of 6
Full-Text Articles in Statistics and Probability
Simultaneous Confidence Bands For The Coefficient Function In Functional Regression, Philip T. Reiss
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
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
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
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
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
Functional Generalized Linear Models With Applications To Neuroimaging, Philip T. Reiss, R. Todd Ogden
Philip T. Reiss
No abstract provided.