Biostatistics Commons^™

Ranked Set Sampling Based On Binary Water Quality Data With Covariates, Paul Kvam

Department of Math & Statistics Faculty Publications

A ranked set sample (RSS) is composed of independent order statistics, formed by collecting and ordering independent subsamples, then measuring only one item from each subsample. If the cost of sampling is dominated by data measurement rather than collection or ranking, the RSS technique is known to be superior to ordinary sampling. Experiments based on binary data are not designed to exploit the advantages of ranked set sampling because categorical data typically are as easily measured as ranked, making RSS methods impractical. However, in some environmental and biological studies, the success probability of a bivariate outcome is related to one …

Estimation Of Parameters In Replicated Time Series Regression Models, Genming Shi

Mathematics & Statistics Theses & Dissertations

The time series regression model was widely studied in the literature by several authors. However, statistical analysis of replicated time series regression models has received little attention. In this thesis, we study the application of quasi-least squares, a relatively new method, to estimate the parameters in replicated time series models with general ARMA( p, q) correlation structure. We also study several established methods for estimating the parameters in those models, including the maximum likelihood, method of moments, and the GEE method. Asymptotic comparisons of the methods are made bV fixing the number of repeated measurements in each series, and …

Geographic Variation In The Morphology Of Crotalus Horridus (Serpentes: Viperidae), John Robert Allsteadt

Biological Sciences Theses & Dissertations

The Timber Rattlesnake (Crotalus horridus) occurs in discontinuous populations throughout the eastern and central United States. The species exhibits high levels of polymorphism in morphological traits, especially in coloration and pattern. Previous studies recognized either distinct northern and southern subspecies or three regional morphs (northern, southern, and western), but conflicting data sets and limited geographic sampling of previous studies have left the relationships among those regional variants unclear. In this study, univariate and multivariate statistics, together with a geographic information system, were used to analyze geographic variation in 36 morphological characters recorded from 2,420 specimens of C. horridus …

Cultural And Psychological Influences On Diabetic Adherence, Keikilani Mcmillin-Williams

Loma Linda University Electronic Theses, Dissertations & Projects

Diabetes mellitus is a serious disease that poses a particular healthcare challenge because progression is considered controllable (Cox, et al, 1985; Vinicor, et al, 1996) yet treatment adherence, and thus outcome, is very poor (Gonder-Frederick, Cox, & Ritterband, 2002; Goodall, 1991). Culture is a lethal risk factor for diabetic contraction and treatment maintenance. Latinos within the United States are two-to-three times more likely to develop complications and die than non-Latinos (Haffner et al, 1996; Rubin, Peyrot, & Saudek, 1991) and are less likely to adhere to treatment (Lipton, Losey, Giachello, Mendez, & Girotti, 1998). Efforts to eliminate health disparities have …

An Application In Bioinformatics : A Comparison Of Affymetrix And Compugen Human Genome Microarrays, Milind Misra

Theses

The human genome microarrays from Compugen® and Affymetrix® were compared in the context of the emerging field of computational biology. The two premier database servers for genomic sequence data, the National Center for Biotechnology Information and the European Bioinformatics Institute, were described in detail. The various databases and data mining tools available through these data servers were also discussed. Microarrays were examined from a historical perspective and their main current applications-expression analysis, mutation analysis, and comparative genomic hybridization-were discussed. The two main types of microarrays, cDNA spotted microarrays and high-density spotted microarrays were analyzed by exploring the human genome microarray …

A Method For Developing In-Silico Protein Homologs, Susan Mcclatchy

Theses

Computational methods for identifying and screening the most promising drug receptor candidates in the human genome are of great interest to drug discovery researchers. Successful methods will accurately identify and narrow the field of potential drug receptor candidates. This study details one such method.

The method described here begins with the assumption that novel drug receptors have high sequence similarity to established drug receptors. The similarity search program FASTA3 aligns translated sequences of the human genome to known drug receptor sequences and ranks these alignments by measuring their statistical significance. Query results returned by FASTA3 are assembled into "in-silico proteins" …

Analysis Of Gene Expression Data Using Expressionist 3.1 And Genespring 4.2, Indu Shrivastava

Theses

The purpose of this study was to determine the differences in the gene expression analysis methods of two data mining tools, Expressionistic^TM 3.1 and GeneSpring^TM 4.2 with focus on basic statistical analysis and clustering algorithms. The data for this analysis was derived from the hybridization of Rattus norvegicus RNA to the Affymetrix RG34A GeneChip. This analysis was derived from experiments designed to identify changes in gene expression patterns that were induced in vivo by an experimental treatment.

The tools were found to be comparable with respect to the list of statistically significant genes that were up-regulated by more …

Selective Multiple Imputation Of Keys For Statistical Disclosure Control In Microdata, Rod Little, Fang Liu

The University of Michigan Department of Biostatistics Working Paper Series

The fundamental tension in statistical disclosure control (SDC) of microdata is the trade-off between the protection of individual respondents and the release of enough information for statistical inferences. We consider microdata that include key variables that contain identifying information and target variables that include sensitive information. Releasing the original data may expose some individuals in the sample to high risk of disclosure; deleting key variables is a common approach, but this loses information for some statistical analysis. This paper proposes selective multiple imputation of key variables (SMIKe) as an alternative SDC technique between those two extremes, and applies SMIKe to …

Normal Mixture Models For Gene Cluster Identification In Two Dimensional Microarray Data, Eric Scott Harvey

Theses and Dissertations

This dissertation focuses on methodology specific to microarray data analyses that organize the data in preliminary steps and proposes a cluster analysis method which improves the interpretability of the cluster results. Cluster analysis of microarray data allows samples with similar gene expression values to be discovered and may serve as a useful diagnostic tool. Since microarray data is inherently noisy, data preprocessing steps including smoothing and filtering are discussed. Comparing the results of different clustering methods is complicated by the arbitrariness of the cluster labels. Methods for re-labeling clusters to assess the agreement between the results of different clustering techniques …