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Full-Text Articles in Statistics and Probability

Fisheries Occasional Paper No. 20 - Management Of Western Rock Lobster Fishery - Advice To Stakeholders - Assessment Of Southern Zone Resource Sustainability Options, Department Of Fisheries, Western Australia May 2005

Fisheries Occasional Paper No. 20 - Management Of Western Rock Lobster Fishery - Advice To Stakeholders - Assessment Of Southern Zone Resource Sustainability Options, Department Of Fisheries, Western Australia

Fisheries Occasional Publications

The management options presented in this paper have been developed in close cooperation with the rock lobster industry to address the short-term sustainability and economic concerns regarding the level of exploitation and its impact on the breeding stock in the southern region. The main focus in the short-term is to consider options that reduce fishing effort during periods that may be economically inefficient to fish and at the same time reduce the level of exploitation.

The management package does not address the serious long-term sustainability or socioeconomic issues (e.g. cost pressures and related fleet capacity) facing the industry. If the …


Acute Toxicity Testing Without Animals: More Scientific And Less Of A Gamble, Gillian R. Langley Mar 2005

Acute Toxicity Testing Without Animals: More Scientific And Less Of A Gamble, Gillian R. Langley

Application of Alternative Methods Collection

In this report, we argue specifically that acute toxicity data should not be sought from animal tests. The underlying principle of such tests on rats and mice is that the results can be effectively extrapolated to humans. In fact, after nearly 80 years of use of these tests, the predictivity of rodent data for human acute toxic effects has been disputed but never proven.


The Clustering Of Regression Models Method With Applications In Gene Expression Data, Li-Xuan Qin, Steven G. Self Jan 2005

The Clustering Of Regression Models Method With Applications In Gene Expression Data, Li-Xuan Qin, Steven G. Self

UW Biostatistics Working Paper Series

Identification of differentially expressed genes and clustering of genes are two important and complementary objectives addressed with gene expression data. For the differential expression question, many "per-gene" analytic methods have been proposed. These methods can generally be characterized as using a regression function to independently model the observations for each gene; various adjustments for multiplicity are then used to interpret the statistical significance of these per-gene regression models over the collection of genes analyzed. Motivated by this common structure of per-gene models, we propose a new model-based clustering method -- the clustering of regression models method, which groups genes that …


Cluster Analysis Of Genomic Data With Applications In R, Katherine S. Pollard, Mark J. Van Der Laan Jan 2005

Cluster Analysis Of Genomic Data With Applications In R, Katherine S. Pollard, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

In this paper, we provide an overview of existing partitioning and hierarchical clustering algorithms in R. We discuss statistical issues and methods in choosing the number of clusters, the choice of clustering algorithm, and the choice of dissimilarity matrix. In particular, we illustrate how the bootstrap can be employed as a statistical method in cluster analysis to establish the reproducibility of the clusters and the overall variability of the followed procedure. We also show how to visualize a clustering result by plotting ordered dissimilarity matrices in R. We present a new R package, hopach, which implements the hybrid clustering method, …


Knowing When To Draw The Line: Designing More Informative Ecological Experiments, Kathryn L. Cottingham, Jay T. Lennon, Bryan L. Brown Jan 2005

Knowing When To Draw The Line: Designing More Informative Ecological Experiments, Kathryn L. Cottingham, Jay T. Lennon, Bryan L. Brown

Dartmouth Scholarship

Linear regression and analysis of variance (ANOVA) are two of the most widely used statistical techniques in ecology. Regression quantitatively describes the relationship between a response variable and one or more continuous independent variables, while ANOVA determines whether a response variable differs among discrete values of the independent variable(s). Designing experiments with discrete factors is straightforward because ANOVA is the only option, but what is the best way to design experiments involving continuous factors? Should ecologists prefer experiments with few treatments and many replicates analyzed with ANOVA, or experiments with many treatments and few replicates per treatment analyzed with regression? …


State Of The Fisheries Report 2003/04, J. W. Penn, W. J. Fletcher, F. Head Jan 2005

State Of The Fisheries Report 2003/04, J. W. Penn, W. J. Fletcher, F. Head

Status Reports of the Fisheries and Aquatic Resources

The State ofthe Fisheries Report is published annually to provide an additional level of detailed reporting of the management of fish stocks and their environment undertaken by the Department of Fisheries. A summary report from the document is included in the Department's Annual Report to Parliament, which includes the Department's non-financial (fishery) performance indicators.

By summarising management changes, compliance activities and research data including stock assessments and breeding stock levels, this document provides a valuable reference point for Western Australian fisheries of major importance to the commercial and recreational sectors, and the developing aquaculture sector.

This year's State of the …


Multiple Testing Procedures: R Multtest Package And Applications To Genomics, Katherine S. Pollard, Sandrine Dudoit, Mark J. Van Der Laan Dec 2004

Multiple Testing Procedures: R Multtest Package And Applications To Genomics, Katherine S. Pollard, Sandrine Dudoit, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

The Bioconductor R package multtest implements widely applicable resampling-based single-step and stepwise multiple testing procedures (MTP) for controlling a broad class of Type I error rates, in testing problems involving general data generating distributions (with arbitrary dependence structures among variables), null hypotheses, and test statistics. The current version of multtest provides MTPs for tests concerning means, differences in means, and regression parameters in linear and Cox proportional hazards models. Procedures are provided to control Type I error rates defined as tail probabilities for arbitrary functions of the numbers of false positives and rejected hypotheses. These error rates include tail probabilities …


The Effect Of Naocl, Ca(Oh)2, Mta And Mtad On Root Dentin Fracture Resistance, Sunil Ilapogu Dec 2004

The Effect Of Naocl, Ca(Oh)2, Mta And Mtad On Root Dentin Fracture Resistance, Sunil Ilapogu

Loma Linda University Electronic Theses, Dissertations & Projects

Various materials are used for the treatment of immature teeth that have been subjected to trauma or decay. It is not well established what effect these materials may have on the immature root dentin. A concern would be the resistance to fracture of the remaining root dentin. The purpose of this study was to compare the resistance of fracture of bovine teeth treated with sodium hypochlorite, calcium hydroxide, gray MTA and gray MTA in conjunction with MTAD after certain periods of time. One hundred and ninety five freshly extracted, intact bovine incisors were prepared using a modified Haapasalo and Orstavik …


A Bayesian Method For Finding Interactions In Genomic Studies, Wei Chen, Debashis Ghosh, Trivellore E. Raghuanthan, Sharon Kardia Nov 2004

A Bayesian Method For Finding Interactions In Genomic Studies, Wei Chen, Debashis Ghosh, Trivellore E. Raghuanthan, Sharon Kardia

The University of Michigan Department of Biostatistics Working Paper Series

An important step in building a multiple regression model is the selection of predictors. In genomic and epidemiologic studies, datasets with a small sample size and a large number of predictors are common. In such settings, most standard methods for identifying a good subset of predictors are unstable. Furthermore, there is an increasing emphasis towards identification of interactions, which has not been studied much in the statistical literature. We propose a method, called BSI (Bayesian Selection of Interactions), for selecting predictors in a regression setting when the number of predictors is considerably larger than the sample size with a focus …


Laboratory Routines Cause Animal Stress, Jonathan P. Balcombe, Neal D. Barnard, Chad Sandusky Nov 2004

Laboratory Routines Cause Animal Stress, Jonathan P. Balcombe, Neal D. Barnard, Chad Sandusky

Laboratory Experiments Collection

Eighty published studies were appraised to document the potential stress associated with three routine laboratory procedures commonly performed on animals: handling, blood collection, and orogastric gavage. We defined handling as any non-invasive manipulation occurring as part of routine husbandry, including lifting an animal and cleaning or moving an animal's cage. Significant changes in physiologic parameters correlated with stress (e.g., serum or plasma concentrations of corticosterone, glucose, growth hormone or prolactin, heart rate, blood pressure, and behavior) were associated with all three procedures in multiple species in the studies we examined. The results of these studies demonstrated that animals responded with …


Finding Cancer Subtypes In Microarray Data Using Random Projections, Debashis Ghosh Oct 2004

Finding Cancer Subtypes In Microarray Data Using Random Projections, Debashis Ghosh

The University of Michigan Department of Biostatistics Working Paper Series

One of the benefits of profiling of cancer samples using microarrays is the generation of molecular fingerprints that will define subtypes of disease. Such subgroups have typically been found in microarray data using hierarchical clustering. A major problem in interpretation of the output is determining the number of clusters. We approach the problem of determining disease subtypes using mixture models. A novel estimation procedure of the parameters in the mixture model is developed based on a combination of random projections and the expectation-maximization algorithm. Because the approach is probabilistic, our approach provides a measure for the number of true clusters …


Effect Of Misreported Family History On Mendelian Mutation Prediction Models, Hormuzd A. Katki Sep 2004

Effect Of Misreported Family History On Mendelian Mutation Prediction Models, Hormuzd A. Katki

Johns Hopkins University, Dept. of Biostatistics Working Papers

People with familial history of disease often consult with genetic counselors about their chance of carrying mutations that increase disease risk. To aid them, genetic counselors use Mendelian models that predict whether the person carries deleterious mutations based on their reported family history. Such models rely on accurate reporting of each member's diagnosis and age of diagnosis, but this information may be inaccurate. Commonly encountered errors in family history can significantly distort predictions, and thus can alter the clinical management of people undergoing counseling, screening, or genetic testing. We derive general results about the distortion in the carrier probability estimate …


Condylar Remodeling After Distraction Osteogenesis And Bilateral Sagittal Split Osteotomy, Robert Barker Hoffman Sep 2004

Condylar Remodeling After Distraction Osteogenesis And Bilateral Sagittal Split Osteotomy, Robert Barker Hoffman

Loma Linda University Electronic Theses, Dissertations & Projects

The present pilot study is a histological evaluation of mandibular condyles taken from minipigs that underwent either traditional mandibular advancement (bilateral sagittal split osteotomy), or a distraction osteogenesis procedure to advance the mandible. One pig received a bilateral sagittal split osteotomy with an immediate mandibular advancement of 14 mm, while another pig underwent distraction osteogenesis consisting of a gradual advancement of 2 mm per day to advance the mandible the same distance. The control animal received no surgery.

In the present study, the mandibular condyles of the three pigs (2 control, 2 bilateral sagittal split osteotomy, and 2 distraction osteogenesis) …


Significance Analysis Of Time Course Microarray Experiments, John D. Storey, Wenzhong Xiao, Jeffrey T. Leek, Ronald G. Tompkins, Ron W. Davis Aug 2004

Significance Analysis Of Time Course Microarray Experiments, John D. Storey, Wenzhong Xiao, Jeffrey T. Leek, Ronald G. Tompkins, Ron W. Davis

UW Biostatistics Working Paper Series

Characterizing the genome-wide dynamic regulation of gene expression is important and will be of much interest in the future. However, there is currently no established method for identifying differentially expressed genes in a time course study. Here we propose a significance method for analyzing time course microarray studies that can be applied to the typical types of comparisons and sampling schemes. This method is applied to two studies on humans. In one study, genes are identified that show differential expression over time in response to in vivo endotoxin administration. Using our method 7409 genes are called significant at a 1% …


Semiparametric Quantitative-Trait-Locus Mapping: I. On Functional Growth Curves, Ying Qing Chen, Rongling Wu Jul 2004

Semiparametric Quantitative-Trait-Locus Mapping: I. On Functional Growth Curves, Ying Qing Chen, Rongling Wu

U.C. Berkeley Division of Biostatistics Working Paper Series

The genetic study of certain quantitative traits in growth curves as a function of time has recently been of major scientific interest to explore the developmental evolution processes of biological subjects. Various parametric approaches in the statistical literature have been proposed to study the quantitative-trait-loci (QTL) mapping of the growth curves as multivariate outcomes. In this article, we view the growth curves as functional quantitative traits and propose some semiparametric models to relax the strong parametric assumptions which may not be always practical in reality. Appropriate inference procedures are developed to estimate the parameters of interest which characterise the possible …


Semiparametric Quantitative-Trait-Locus Mapping: Ii. On Censored Age-At-Onset, Ying Qing Chen, Chengcheng Hu, Rongling Wu Jul 2004

Semiparametric Quantitative-Trait-Locus Mapping: Ii. On Censored Age-At-Onset, Ying Qing Chen, Chengcheng Hu, Rongling Wu

U.C. Berkeley Division of Biostatistics Working Paper Series

In genetic studies, the variation in genotypes may not only affect different inheritance patterns in qualitative traits, but may also affect the age-at-onset as quantitative trait. In this article, we use standard cross designs, such as backcross or F2, to propose some hazard regression models, namely, the additive hazards model in quantitative trait loci mapping for age-at-onset, although the developed method can be extended to more complex designs. With additive invariance of the additive hazards models in mixture probabilities, we develop flexible semiparametric methodologies in interval regression mapping without heavy computing burden. A recently developed multiple comparison procedures is adapted …


Quantification And Visualization Of Ld Patterns And Identification Of Haplotype Blocks, Yan Wang, Sandrine Dudoit Jun 2004

Quantification And Visualization Of Ld Patterns And Identification Of Haplotype Blocks, Yan Wang, Sandrine Dudoit

U.C. Berkeley Division of Biostatistics Working Paper Series

Classical measures of linkage disequilibrium (LD) between two loci, based only on the joint distribution of alleles at these loci, present noisy patterns. In this paper, we propose a new distance-based LD measure, R, which takes into account multilocus haplotypes around the two loci in order to exploit information from neighboring loci. The LD measure R yields a matrix of pairwise distances between markers, based on the correlation between the lengths of shared haplotypes among chromosomes around these markers. Data analysis demonstrates that visualization of LD patterns through the R matrix reveals more deterministic patterns, with much less noise, than …


Differential Expression With The Bioconductor Project, Anja Von Heydebreck, Wolfgang Huber, Robert Gentleman Jun 2004

Differential Expression With The Bioconductor Project, Anja Von Heydebreck, Wolfgang Huber, Robert Gentleman

Bioconductor Project Working Papers

A basic, yet challenging task in the analysis of microarray gene expression data is the identification of changes in gene expression that are associated with particular biological conditions. We discuss different approaches to this task and illustrate how they can be applied using software from the Bioconductor Project. A central problem is the high dimensionality of gene expression space, which prohibits a comprehensive statistical analysis without focusing on particular aspects of the joint distribution of the genes expression levels. Possible strategies are to do univariate gene-by-gene analysis, and to perform data-driven nonspecific filtering of genes before the actual statistical analysis. …


Nonparametric Methods For Analyzing Replication Origins In Genomewide Data, Debashis Ghosh Jun 2004

Nonparametric Methods For Analyzing Replication Origins In Genomewide Data, Debashis Ghosh

The University of Michigan Department of Biostatistics Working Paper Series

Due to the advent of high-throughput genomic technology, it has become possible to globally monitor cellular activities on a genomewide basis. With these new methods, scientists can begin to address important biological questions. One such question involves the identification of replication origins, which are regions in chromosomes where DNA replication is initiated. In addition, one hypothesis regarding replication origins is that their locations are non-random throughout the genome. In this article, we develop methods for identification of and cluster inference regarding replication origins involving genomewide expression data. We compare several nonparametric regression methods for the identification of replication origin locations. …


Semiparametric Methods For Identification Of Tumor Progression Genes From Microarray Data, Debashis Ghosh, Arul Chinnaiyan Jun 2004

Semiparametric Methods For Identification Of Tumor Progression Genes From Microarray Data, Debashis Ghosh, Arul Chinnaiyan

The University of Michigan Department of Biostatistics Working Paper Series

The use of microarray data has become quite commonplace in medical and scientific experiments. We focus here on microarray data generated from cancer studies. It is potentially important for the discovery of biomarkers to identify genes whose expression levels correlate with tumor progression. In this article, we develop statistical procedures for the identification of such genes, which we term tumor progression genes. Two methods are considered in this paper. The first is use of a proportional odds procedure, combined with false discovery rate estimation techniques to adjust for the multiple testing problem. The second method is based on order-restricted estimation …


The False Discovery Rate: A Variable Selection Perspective, Debashis Ghosh, Wei Chen, Trivellore E. Raghuanthan Jun 2004

The False Discovery Rate: A Variable Selection Perspective, Debashis Ghosh, Wei Chen, Trivellore E. Raghuanthan

The University of Michigan Department of Biostatistics Working Paper Series

In many scientific and medical settings, large-scale experiments are generating large quantities of data that lead to inferential problems involving multiple hypotheses. This has led to recent tremendous interest in statistical methods regarding the false discovery rate (FDR). Several authors have studied the properties involving FDR in a univariate mixture model setting. In this article, we turn the problem on its side; in this manuscript, we show that FDR is a by-product of Bayesian analysis of variable selection problem for a hierarchical linear regression model. This equivalence gives many Bayesian insights as to why FDR is a natural quantity to …


A Graph Theoretic Approach To Testing Associations Between Disparate Sources Of Functional Genomic Data, Raji Balasubramanian, Thomas Laframboise, Denise Scholtens, Robert Gentleman Jun 2004

A Graph Theoretic Approach To Testing Associations Between Disparate Sources Of Functional Genomic Data, Raji Balasubramanian, Thomas Laframboise, Denise Scholtens, Robert Gentleman

Bioconductor Project Working Papers

The last few years have seen the advent of high-throughput technologies to analyze various properties of the transcriptome and proteome of several organisms. The congruency of these different data sources, or lack thereof, can shed light on the mechanisms that govern cellular function. A central challenge for bioinformatics research is to develop a unified framework for combining the multiple sources of functional genomics information and testing associations between them, thus obtaining a robust and integrated view of the underlying biology.

We present a graph theoretic approach to test the significance of the association between multiple disparate sources of functional genomics …


Animal Model Research: The Apples And Oranges Quandary, Kenneth J. Shapiro Jun 2004

Animal Model Research: The Apples And Oranges Quandary, Kenneth J. Shapiro

Experimentation Collection

In this paper, I explore the premises underlying the problem of the evaluation of animal models. I argue that the presence of similarities and differences between the model and the modelled, although historically and currently a dominant antinomy framing evaluation, is not a bottom-line consideration. What is critical is 1) whether we learn and 2) whether we improve treatment through the animal model research. Similarity between model and modelled and the closely related concept of validity are not coterminus with these critical evaluative measures. In fact, differences between the model and modelled also can provide impetus to new understanding and …


Relative Validity Of A Food Frequency Questionnaire Used To Assess Food And Nutrient Intake In A Dietary Intervention Study, Gina Segovia Siapco Jun 2004

Relative Validity Of A Food Frequency Questionnaire Used To Assess Food And Nutrient Intake In A Dietary Intervention Study, Gina Segovia Siapco

Loma Linda University Electronic Theses, Dissertations & Projects

Food frequency questionnaire is a cost effective alternative for measuring dietary intake when conducting large scale surveys. We investigated the validity of a 171-item semi-quantitative food frequency questionnaire in assessing food and nutrient intakes and the prescribed intervention measure during a randomized field trial. Eighty-seven free-living adults (48 females and 39 males) aged 30-72 years provided dietary information by self-administering the Walnut Study Dietary Assessment Questionnaire (WSDAQ), which assessed intake over the past six months, and through seven unannounced non-consecutive 24-hour dietary recalls by telephone. Participants were randomly assigned to either a walnut or habitual diet at baseline. For six …


A Model Based Background Adjustment For Oligonucleotide Expression Arrays, Zhijin Wu, Rafael A. Irizarry, Robert Gentleman, Francisco Martinez Murillo, Forrest Spencer May 2004

A Model Based Background Adjustment For Oligonucleotide Expression Arrays, Zhijin Wu, Rafael A. Irizarry, Robert Gentleman, Francisco Martinez Murillo, Forrest Spencer

Johns Hopkins University, Dept. of Biostatistics Working Papers

High density oligonucleotide expression arrays are widely used in many areas of biomedical research. Affymetrix GeneChip arrays are the most popular. In the Affymetrix system, a fair amount of further pre-processing and data reduction occurs following the image processing step. Statistical procedures developed by academic groups have been successful at improving the default algorithms provided by the Affymetrix system. In this paper we present a solution to one of the pre-processing steps, background adjustment, based on a formal statistical framework. Our solution greatly improves the performance of the technology in various practical applications.

Affymetrix GeneChip arrays use short oligonucleotides to …


Classification Using Generalized Partial Least Squares, Beiying Ding, Robert Gentleman May 2004

Classification Using Generalized Partial Least Squares, Beiying Ding, Robert Gentleman

Bioconductor Project Working Papers

The advances in computational biology have made simultaneous monitoring of thousands of features possible. The high throughput technologies not only bring about a much richer information context in which to study various aspects of gene functions but they also present challenge of analyzing data with large number of covariates and few samples. As an integral part of machine learning, classification of samples into two or more categories is almost always of interest to scientists. In this paper, we address the question of classification in this setting by extending partial least squares (PLS), a popular dimension reduction tool in chemometrics, in …


Fisheries Occasional Publication No. 6 - Anglers Guide To Assessing Reproductive Stage In Fish, Kim Smith, Mike Mackie, Department Of Fisheries Western Australia Apr 2004

Fisheries Occasional Publication No. 6 - Anglers Guide To Assessing Reproductive Stage In Fish, Kim Smith, Mike Mackie, Department Of Fisheries Western Australia

Fisheries Occasional Publications

What is a gonad?

"Gonad" is a general term for a reproductive organ, and is used to describe both ovaries and testes. In male and female fish, the gonad is an elongated organ lying along the upper wall of the gut cavity (i.e. running immediately under the vertebral column). The gonad gonad has 2 lobes. Both lobes are attached to the body near the anus and extend forward inside the gut cavity.

As fish gonads ripen, they become larger, heavier and change colour. Immature and undeveloped adult gonads are very small, strap-like in shape, pinkish in colour and translucent (i.e. …


Mixture Models For Assessing Differential Expression In Complex Tissues Using Microarray Data, Debashis Ghosh Feb 2004

Mixture Models For Assessing Differential Expression In Complex Tissues Using Microarray Data, Debashis Ghosh

The University of Michigan Department of Biostatistics Working Paper Series

The use of DNA microarrays has become quite popular in many scientific and medical disciplines, such as in cancer research. One common goal of these studies is to determine which genes are differentially expressed between cancer and healthy tissue, or more generally, between two experimental conditions. A major complication in the molecular profiling of tumors using gene expression data is that the data represent a combination of tumor and normal cells. Much of the methodology developed for assessing differential expression with microarray data has assumed that tissue samples are homogeneous. In this article, we outline a general framework for determining …


Optimal Sample Size For Multiple Testing: The Case Of Gene Expression Microarrays, Peter Muller, Giovanni Parmigiani, Christian Robert, Judith Rousseau Feb 2004

Optimal Sample Size For Multiple Testing: The Case Of Gene Expression Microarrays, Peter Muller, Giovanni Parmigiani, Christian Robert, Judith Rousseau

Johns Hopkins University, Dept. of Biostatistics Working Papers

We consider the choice of an optimal sample size for multiple comparison problems. The motivating application is the choice of the number of microarray experiments to be carried out when learning about differential gene expression. However, the approach is valid in any application that involves multiple comparisons in a large number of hypothesis tests. We discuss two decision problems in the context of this setup: the sample size selection and the decision about the multiple comparisons. We adopt a decision theoretic approach,using loss functions that combine the competing goals of discovering as many ifferentially expressed genes as possible, while keeping …


Calibrating Observed Differential Gene Expression For The Multiplicity Of Genes On The Array, Yingye Zheng, Margaret S. Pepe Jan 2004

Calibrating Observed Differential Gene Expression For The Multiplicity Of Genes On The Array, Yingye Zheng, Margaret S. Pepe

UW Biostatistics Working Paper Series

In a gene expression array study, the expression levels of thousands of genes are monitored simultaneously across various biological conditions on a small set of subjects. One goal of such studies is to explore a large pool of genes in order to select a subset of genes that appear to be differently expressed for further investigation. Of particular interest here is how to select the top k genes once genes are ranked based on their evidence for differential expression in two tissue types. We consider statistical methods that provide a more rigorous and intuitively appealing selection process for k. We …