The Experts below are selected from a list of 249 Experts worldwide ranked by ideXlab platform
William T Longstreth - One of the best experts on this subject based on the ideXlab platform.
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recursive partitioning for the identification of disease risk subgroups a case control study of subarachnoid hemorrhage
Journal of Clinical Epidemiology, 1998Co-Authors: Lorene M. Nelson, Daniel A Bloch, William T LongstrethAbstract:Abstract Recursive partitioning is a Nonparametric Technique that produces a classification tree in which subjects are assigned to mutually exclusive subsets according to a set of predictor variables. We examined the utility of recursive partitioning as a supplement to logistic regression for the multivariable analysis of data from case-control studies, demonstrating the Technique using data from women enrolled in a population-based study of subarachnoid hemorrhage. The classification tree produced by recursive partitioning consisted of three main risk subgroups: (1) elderly women who had long-standing hypertension and who were not smokers, (2) middle-aged women who were cigarette smokers and frequent binge drinkers, and (3) women in whom risk variables indicate relative estrogen deficiency (i.e., postmenopausal status, no recent exposure to hormone replacement therapy, cigarette smoking). As a supplemental method, recursive partitioning not only identifies subgroups with varying risks, but also may uncover interactions between variables that may be overlooked in the traditional application of logistic regression to case-control data.
Anthony S David - One of the best experts on this subject based on the ideXlab platform.
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a systematic review and quantitative appraisal of fmri studies of verbal fluency role of the left inferior frontal gyrus
Human Brain Mapping, 2006Co-Authors: Sergi G Costafreda, Lucy Lee, Brian S Everitt, Michael Brammer, Anthony S DavidAbstract:The left inferior frontal gyrus (LIFG) has consistently been associated with both phonologic and semantic operations in functional neuroimaging studies. Two main theories have proposed a different functional organization in the LIFG for these processes. One theory suggests an anatomic parcellation of phonologic and semantic operations within the LIFG. An alternative theory proposes that both processes are encompassed within a supramodal executive function in a single region in the LIFG. To test these theories, we carried out a systematic review of functional magnetic resonance imaging studies employing phonologic and semantic verbal fluency tasks. Seventeen articles meeting our pre-established criteria were found, consisting of 22 relevant experiments with 197 healthy subjects and a total of 41 peak activations in the LIFG. We determined 95% confidence intervals of the mean location (x, y, and z coordinates) of peaks of blood oxygenation level-dependent (BOLD) responses from published phonologic and semantic verbal fluency studies using the Nonparametric Technique of bootstrap analysis. Significant differences were revealed in dorsal-ventral (z-coordinate) localizations of the peak BOLD response: phonologic verbal fluency peak BOLD response was significantly more dorsal to the peak associated with semantic verbal fluency (confidence interval of difference: 1.9-17.4 mm). No significant differences were evident in antero-posterior (x-coordinate) or medial-lateral (y-coordinate) positions. The results support distinct dorsal-ventral locations for phonologic and semantic processes within the LIFG. Current limitations to meta-analytic integration of published functional neuroimaging studies are discussed.
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a systematic review and quantitative appraisal of fmri studies of verbal fluency role of the left inferior frontal gyrus
Human Brain Mapping, 2006Co-Authors: Sergi G Costafreda, Brian S Everitt, Michael Brammer, Cynthia H Y Fu, Anthony S DavidAbstract:The left inferior frontal gyrus (LIFG) has consistently been associated with both phonologic and semantic operations in functional neuroimaging studies. Two main theories have proposed a different functional organization in the LIFG for these processes. One theory suggests an anatomic parcellation of phonologic and semantic operations within the LIFG. An alternative theory proposes that both processes are encompassed within a supramodal executive function in a single region in the LIFG. To test these theories, we carried out a systematic review of functional magnetic resonance imaging studies employing phonologic and semantic verbal fluency tasks. Seventeen articles meeting our pre-established criteria were found, consisting of 22 relevant experiments with 197 healthy subjects and a total of 41 peak activations in the LIFG. We determined 95% confidence intervals of the mean location (x, y, and z coordinates) of peaks of blood oxygenation level-dependent (BOLD) responses from published phonologic and semantic verbal fluency studies using the Nonparametric Technique of bootstrap analysis. Significant differences were revealed in dorsal–ventral (z-coordinate) localizations of the peak BOLD response: phonologic verbal fluency peak BOLD response was significantly more dorsal to the peak associated with semantic verbal fluency (confidence interval of difference: 1.9–17.4 mm). No significant differences were evident in antero–posterior (x-coordinate) or medial–lateral (y-coordinate) positions. The results support distinct dorsal–ventral locations for phonologic and semantic processes within the LIFG. Current limitations to meta-analytic integration of published functional neuroimaging studies are discussed. Hum Brain Mapp, 2006. © 2006 Wiley-Liss, Inc.
Terrance J. Fulp - One of the best experts on this subject based on the ideXlab platform.
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A stochastic Nonparametric Technique for space‐time disaggregation of streamflows
Water Resources Research, 2007Co-Authors: James Prairie, Balaji Rajagopalan, Upmanu Lall, Terrance J. FulpAbstract:[1] Stochastic disaggregation models are used to simulate streamflows at multiple sites preserving their temporal and spatial dependencies. Traditional approaches to this problem involve transforming the streamflow data of each month and at every location to a Gaussian structure and subsequently fitting a linear model in the transformed space. The simulations are then back transformed to the original space. The main drawbacks of this approach are (1) transforming marginals to Gaussian need not lead to the correct multivariate distribution particularly if the dependence across variables is nonlinear, and (2) the number of parameters to be estimated for a traditional disaggregation model grows rapidly with an increase in space or time components. We present a K-nearest-neighbor approach to resample monthly flows conditioned on an annual value in a temporal disaggregation or multiple upstream locations conditioned on a downstream location for a spatial disaggregation. The method is parsimonious, as the only parameter to estimate is K (the number of nearest neighbors to be used in resampling). Simulating space-time flow scenarios conditioned upon large-scale climate information (e.g., El Nino–Southern Oscillation, etc.) can be easily achieved. We demonstrate the utility of this methodology by applying it for space-time disaggregation of streamflows in the Upper Colorado River basin. The method appropriately captures the distributional and spatial dependency properties at all the locations.
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a stochastic Nonparametric Technique for space time disaggregation of streamflows
Water Resources Research, 2007Co-Authors: James Prairie, Balaji Rajagopalan, Upmanu Lall, Terrance J. FulpAbstract:[1] Stochastic disaggregation models are used to simulate streamflows at multiple sites preserving their temporal and spatial dependencies. Traditional approaches to this problem involve transforming the streamflow data of each month and at every location to a Gaussian structure and subsequently fitting a linear model in the transformed space. The simulations are then back transformed to the original space. The main drawbacks of this approach are (1) transforming marginals to Gaussian need not lead to the correct multivariate distribution particularly if the dependence across variables is nonlinear, and (2) the number of parameters to be estimated for a traditional disaggregation model grows rapidly with an increase in space or time components. We present a K-nearest-neighbor approach to resample monthly flows conditioned on an annual value in a temporal disaggregation or multiple upstream locations conditioned on a downstream location for a spatial disaggregation. The method is parsimonious, as the only parameter to estimate is K (the number of nearest neighbors to be used in resampling). Simulating space-time flow scenarios conditioned upon large-scale climate information (e.g., El Nino–Southern Oscillation, etc.) can be easily achieved. We demonstrate the utility of this methodology by applying it for space-time disaggregation of streamflows in the Upper Colorado River basin. The method appropriately captures the distributional and spatial dependency properties at all the locations.
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Statistical Nonparametric Model for Natural Salt Estimation
Journal of Environmental Engineering, 2005Co-Authors: James Prairie, Balaji Rajagopalan, Terrance J. Fulp, Edith ZagonaAbstract:Many rivers in the Western U.S. suffer from high salinity content due to both natural and human-induced causes. Computer simulation models are often used to estimate future salinity levels and identify mitigation needs. To date, estimation of future natural salt loading has utilized linear relationships between natural flow and natural salt. We develop a Nonparametric regression Technique to fit a functional relationship between natural flow and natural salt. The main advantages of the Nonparametric Technique are: (1) No prior assumptions have to be made as to the underlying form of the relationship and (2) any arbitrary relationship (linear or nonlinear) can be modeled. In addition, we develop a resampling scheme to provide confidence intervals of the natural salt estimates from the Nonparametric model. We apply this model to data from a stream gauge at Glenwood Springs, Colo., on the Colorado River. We show that the new natural salt model reduces the average overprediction of salt mass shown in the existing natural salt model for the period 1941-1995 by approximately 15% s78,000 metric tonsd.
Sarfraz Ahmad - One of the best experts on this subject based on the ideXlab platform.
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Reference Ranges of the Dilute Tissue Thromboplastin Inhibition and Dilute Russell's Viper Venom Tests Revisited
Clinical and applied thrombosis hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis Hemostasis, 2002Co-Authors: Rolandas Gerbutavicius, Jawed Fareed, Harry L. Messmore, Omer Iqbal, Debra Hoppensteadt, William H. Wehrmacher, Muzaffer Demir, Peter Piccolo, Sarfraz AhmadAbstract:Reference ranges for two well-recognized tests for the lupus anticoagulant were determined utilizing 98 healthy subjects. The purpose of the study was to compare the reference ranges for the dilute tissue thromboplastin inhibition test on this group of healthy subjects calculated by parametric and Nonparametric statistical methods, and to compare these results with results obtained on subsets of 20 and 40 randomly selected individuals from the group of 98. The same procedures were followed for the dilute Russell's viper venom test. Results were recorded in seconds of clotting times and in ratios (subject/mean of that set or subset). Statistical analysis revealed Gaussian distribution of the results in the large group as well as in each subset for both tests. The results showed more variation between sets of the dilute tissue thromboplastin inhibition test than of the dilute Russell's viper venom test. Nonparametrically calculated reference ranges were wider than those determined by a parametric method, especially if confidence intervals are provided for both reference ranges in the group of 94 controls or in a subset of 40 subjects. The Nonparametric Technique utilizes all data for the calculation of reference ranges of such sample sizes no matter how wide the results are spread. There was no significant difference between the reference ranges of subsets and the whole group (p > 0.05) calculated by both statistical Techniques.
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Reference intervals of the dilute tissue thromboplastin inhibition and dilute Russell's viper venom tests revisited.
Clinical and applied thrombosis hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis Hemostasis, 2002Co-Authors: Rolandas Gerbutavicius, Jawed Fareed, Harry L. Messmore, Omer Iqbal, Debra Hoppensteadt, William H. Wehrmacher, Muzaffer Demir, Peter Piccolo, Sarfraz AhmadAbstract:Reference intervals for two well-recognized tests for the lupus anticoagulant were determined using 98 healthy subjects. The purpose of the study was to compare the reference intervals for the dilute tissue thromboplastin inhibition test on this group of healthy subjects calculated by parametric and Nonparametric statistical methods, and to compare these results with results obtained on subsets of 20 and 40 randomly selected individuals from the group of 98. The same procedures were followed for the dilute Russell's viper venom test. Results were recorded in seconds of clotting times and in ratios (subject/mean of that set or subset). Statistical analysis revealed Gaussian distribution of the results in the large group as well as in each subset for both tests. The results showed more variation between sets of the dilute tissue thromboplastin inhibition test than of the dilute Russell's viper venom test. Nonparametrically calculated reference intervals were wider than those determined by the parametric method, especially if confidence intervals are provided for both reference limits in a group of 94 controls or in a subset of 40 subjects. The Nonparametric Technique uses all data for the calculation of reference interval of such sample sizes no matter how widely spread the results are. There was no significant difference between the reference intervals of subsets and the whole group (p > 0.05) calculated by both statistical Techniques. Very few outliers were observed among these subjects in both tests.
Lorene M. Nelson - One of the best experts on this subject based on the ideXlab platform.
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recursive partitioning for the identification of disease risk subgroups a case control study of subarachnoid hemorrhage
Journal of Clinical Epidemiology, 1998Co-Authors: Lorene M. Nelson, Daniel A Bloch, William T LongstrethAbstract:Abstract Recursive partitioning is a Nonparametric Technique that produces a classification tree in which subjects are assigned to mutually exclusive subsets according to a set of predictor variables. We examined the utility of recursive partitioning as a supplement to logistic regression for the multivariable analysis of data from case-control studies, demonstrating the Technique using data from women enrolled in a population-based study of subarachnoid hemorrhage. The classification tree produced by recursive partitioning consisted of three main risk subgroups: (1) elderly women who had long-standing hypertension and who were not smokers, (2) middle-aged women who were cigarette smokers and frequent binge drinkers, and (3) women in whom risk variables indicate relative estrogen deficiency (i.e., postmenopausal status, no recent exposure to hormone replacement therapy, cigarette smoking). As a supplemental method, recursive partitioning not only identifies subgroups with varying risks, but also may uncover interactions between variables that may be overlooked in the traditional application of logistic regression to case-control data.
