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Articles 1 - 11 of 11
Full-Text Articles in Multivariate Analysis
Loss-Based Estimation With Cross-Validation: Applications To Microarray Data Analysis And Motif Finding, Sandrine Dudoit, Mark J. Van Der Laan, Sunduz Keles, Annette M. Molinaro, Sandra E. Sinisi, Siew Leng Teng
Loss-Based Estimation With Cross-Validation: Applications To Microarray Data Analysis And Motif Finding, Sandrine Dudoit, Mark J. Van Der Laan, Sunduz Keles, Annette M. Molinaro, Sandra E. Sinisi, Siew Leng Teng
U.C. Berkeley Division of Biostatistics Working Paper Series
Current statistical inference problems in genomic data analysis involve parameter estimation for high-dimensional multivariate distributions, with typically unknown and intricate correlation patterns among variables. Addressing these inference questions satisfactorily requires: (i) an intensive and thorough search of the parameter space to generate good candidate estimators, (ii) an approach for selecting an optimal estimator among these candidates, and (iii) a method for reliably assessing the performance of the resulting estimator. We propose a unified loss-based methodology for estimator construction, selection, and performance assessment with cross-validation. In this approach, the parameter of interest is defined as the risk minimizer for a suitable …
Comparison Of Bracket Bond Strength By Total, Self-Etch And Laser Treatment, Kyo Sung Shawn Kim
Comparison Of Bracket Bond Strength By Total, Self-Etch And Laser Treatment, Kyo Sung Shawn Kim
Loma Linda University Electronic Theses, Dissertations & Projects
Laser etching of enamel surfaces alters the physical and chemical characteristics of the enamel. These changes in characteristics enhance the bonding to enamel. The purpose of this study was to compare the shear and tensile bond strength of Er,Cr:YSGG hydrokinetic laser system (Biolase) with 37% phosphoric acid and self etching primer 30 minutes and 72 hours after bonding. Four different laser power output setting was observed: 1.5W, 2.0W, 2.5W, and 3.0W. Two hundred forty bovine teeth free of defect, caries, and dentin exposure were mounted in acrylic resin and divided into 24 groups of 10 teeth. Sixteen groups of 10 …
A Bond Strength Comparison Of Led And Halogen Light Curing Units, John Richard Kavanagh
A Bond Strength Comparison Of Led And Halogen Light Curing Units, John Richard Kavanagh
Loma Linda University Electronic Theses, Dissertations & Projects
The purpose of this research was to compare the tensile bond strength of orthodontic flat based buttons bonded to bovine teeth with four commercial light-emitting diode (LED) curing lights and one conventional quartz tungsten halogen (QTH) curing light.
The dental market has recently been introduced to a number of commercially available light-emitting diode (LED) curing lights. Tensile bond strength was evaluated for LED curing lights (Rembrandt® AllegroTM, Den-Mat Corp, Santa Maria, CA), (LEDemetron, Kerr/Demetron Corp, Danbury, Conn), (Ortholux LED, 3MTMESPETM, St. Paul, MN),and (FLASH-lite 1001, Discus Dental, Culver City, CA) are compared with one …
A Nested Unsupervised Approach To Identifying Novel Molecular Subtypes, Elizabeth Garrett, Giovanni Parmigiani
A Nested Unsupervised Approach To Identifying Novel Molecular Subtypes, Elizabeth Garrett, Giovanni Parmigiani
Johns Hopkins University, Dept. of Biostatistics Working Papers
In classification problems arising in genomics research it is common to study populations for which a broad class assignment is known (say, normal versus diseased) and one seeks to find undiscovered subclasses within one or both of the known classes. Formally, this problem can be thought of as an unsupervised analysis nested within a supervised one. Here we take the view that the nested unsupervised analysis can successfully utilize information from the entire data set for constructing and/or selecting useful predictors. Specifically, we propose a mixture model approach to the nested unsupervised problem, where the supervised information is used to …
Tree-Based Multivariate Regression And Density Estimation With Right-Censored Data , Annette M. Molinaro, Sandrine Dudoit, Mark J. Van Der Laan
Tree-Based Multivariate Regression And Density Estimation With Right-Censored Data , Annette M. Molinaro, Sandrine Dudoit, Mark J. Van Der Laan
U.C. Berkeley Division of Biostatistics Working Paper Series
We propose a unified strategy for estimator construction, selection, and performance assessment in the presence of censoring. This approach is entirely driven by the choice of a loss function for the full (uncensored) data structure and can be stated in terms of the following three main steps. (1) Define the parameter of interest as the minimizer of the expected loss, or risk, for a full data loss function chosen to represent the desired measure of performance. Map the full data loss function into an observed (censored) data loss function having the same expected value and leading to an efficient estimator …
The Psychological Characteristics Of Obese Children, Thomas Taylor Mitchell
The Psychological Characteristics Of Obese Children, Thomas Taylor Mitchell
Loma Linda University Electronic Theses, Dissertations & Projects
Several studies along with the surgeon general of the United States have identified obesity as a national health issue. Research indicates that adult obesity treatment has relatively poor long-term effects. Consequently increased attention has been given to addressing obesity in children. This focus is particularly vital due to the fact that children are one of the populations showing the most rapid increase in overweight and obesity. The purpose of this study was to identify the some of the unique psychological characteristics of obese children by analyzing the intake data of children and adolescents attending the Loma Linda University Growing Fit …
The Radiopacity Of 29 Resin Restorative Materials Compared To Enamel, Peter Lubisich Iv
The Radiopacity Of 29 Resin Restorative Materials Compared To Enamel, Peter Lubisich Iv
Loma Linda University Electronic Theses, Dissertations & Projects
The radiodensity of a composite resin can greatly influence a clinician's ability to analyze a restoration for failure. The purpose of this study was to determine the relative radiopacities of 29 resin restorative materials compared to enamel, and to verify the comparable radiopacity between shades of 23 of the restorative composite resin materials. Composite resin discs measuring >5mm in diameter and 2 mm in thickness were made and polymerized. Radiographs were taken of the composite resin discs, which included an aluminum step wedge for calibration and a densitometer was used to measure the radiodensity of the composite resin samples. The …
Quantification Of Bone Deposition In Onlay Bone Grafting, Gregory Alan Kammeyer
Quantification Of Bone Deposition In Onlay Bone Grafting, Gregory Alan Kammeyer
Loma Linda University Electronic Theses, Dissertations & Projects
The purpose of this study was to quantitatively evaluate; 1) mandibular posterior mono-cortical block onlay bone graft success rates 2) the amount of grafted bone retained after initial resorption in radiographic projections. Seven consecutive patients with 14 mandibular posterior implant sites requiring bone augmentation for implants of a standard 3.8mm x 10mm dimension were sought. Mono-cortical block bone grafts from the ipsilateral ascending ramus were placed then observed with two standardized CT scans, dividing them into two groups: Group A had the first CT at 4 weeks after graft placement and a second taken before Prosthodontic reconstruction, 36.7 weeks later. …
Cluster Stability Scores For Microarray Data In Cancer Studies, Mark Smolkin, Debashis Ghosh
Cluster Stability Scores For Microarray Data In Cancer Studies, Mark Smolkin, Debashis Ghosh
The University of Michigan Department of Biostatistics Working Paper Series
A potential benefit of profiling of tissue samples using microarrays is the generation of molecular fingerprints that will define subtypes of disease. Hierarchical clustering has been the primary analytical tool used to define disease subtypes from microarray experiments in cancer settings. Assessing cluster reliability poses a major complication in analyzing output from these procedures. While much work has been done on assessing the global question of number of clusters in a dataset, relatively little research exists on assessing stability of individual clusters. A potential benefit of profiling of tissue samples using microarrays is the generation of molecular fingerprints that will …
Selecting Differentially Expressed Genes From Microarray Experiments, Margaret S. Pepe, Gary M. Longton, Garnet L. Anderson, Michel Schummer
Selecting Differentially Expressed Genes From Microarray Experiments, Margaret S. Pepe, Gary M. Longton, Garnet L. Anderson, Michel Schummer
UW Biostatistics Working Paper Series
High throughput technologies, such as gene expression arrays and protein mass spectrometry, allow one to simultaneously evaluate thousands of potential biomarkers that distinguish different tissue types. Of particular interest here is cancer versus normal organ tissues. We consider statistical methods to rank genes (or proteins) in regards to differential expression between tissues. Various statistical measures are considered and we argue that two measures related to the Receiver Operating Characteristic Curve are particularly suitable for this purpose. We also propose that sampling variability in the gene rankings be quantified and suggest using the “selection probability function”, the probability distribution of rankings …
Semi-Parametric Regression For The Area Under The Receiver Operating Characteristic Curve, Lori E. Dodd, Margaret S. Pepe
Semi-Parametric Regression For The Area Under The Receiver Operating Characteristic Curve, Lori E. Dodd, Margaret S. Pepe
UW Biostatistics Working Paper Series
Medical advances continue to provide new and potentially better means for detecting disease. Such is true in cancer, for example, where biomarkers are sought for early detection and where improvements in imaging methods may pick up the initial functional and molecular changes associated with cancer development. In other binary classification tasks, computational algorithms such as Neural Networks, Support Vector Machines and Evolutionary Algorithms have been applied to areas as diverse as credit scoring, object recognition, and peptide-binding prediction. Before a classifier becomes an accepted technology, it must undergo rigorous evaluation to determine its ability to discriminate between states. Characterization of …