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Modeling Incomplete Longitudinal Data, Hakan Demirtas

Journal of Modern Applied Statistical Methods

This article presents a review of popular parametric, semiparametric and ad-hoc approaches for analyzing incomplete longitudinal data.

Aligned Rank Tests As Robust Alternatives For Testing Interactions In Multiple Group Repeated Measures Designs With Heterogeneous Covariances, Xiaosheng Lei, Janet K. Holt, T. Mark Beasley

Journal of Modern Applied Statistical Methods

Data simulation was used to investigate whether tests performed on aligned ranks (Beasley, 2002) could be used as robust alternatives to parametric methods for testing a split-plot interaction with non-normal data and heterogeneous covariance matrices. Results indicated the aligned rank method do not have any distinct advantage over parametric methods in this situation.

Multivariate And Multistrata Nonparametric Tests: The Nonparametric Combination Method, Livio Corain, Luigi Salmaso

Journal of Modern Applied Statistical Methods

Researchers and practitioners in many scientific disciplines and industrial fields are often faced with complex problems when dealing with comparisons between two or more groups using classical parametric methods. The data arising from real problems rarely are in agreement with stringent parametric assumptions. The NonParametric Combination (NPC) methodology frees the researcher from stringent assumptions of parametric methods and allows a more flexible analysis, both in terms of specification of multivariate hypotheses and in terms of the nature of the variables involved in the analysis. An outline of NPC methodology is given, along with case studies.

On Comparison Of Hypothesis Tests In The Bayesian Framework Without Loss Function, Vladimir Gercsik, Mark Kelbert

Journal of Modern Applied Statistical Methods

The problem is how to compare the quality of different hypothesis tests in a Bayesian framework without introducing a loss function. Three different linear orders on the set of all possible hypothesis tests are studied. The most natural order estimates the Fisher information between indicators of event and decision.

The President’S Problem, Jann-Huei Jinn

Journal of Modern Applied Statistical Methods

A solution is offered in response to a complex combination problem challenged by Blom, Englund, and Sandell (1998). The problem is to determine the probability that a random permutation of the word BILLCLINTON has no equal neighbors.

A Conversation With R. Clifford Blair On The Occasion Of His Retirement, Shlomo S. Sawilowsky

Journal of Modern Applied Statistical Methods

An interview was conducted on 23 November 2003 with R. Clifford Blair on the occasion on his retirement from the University of South Florida. This article is based on that interview. Biographical sketches and images of members of his academic genealogy are provided.

Appeal Rates And Outcomes In Tried And Nontried Cases: Further Exploration Of Anti-Plaintiff Appellate Outcomes, Theodore Eisenberg

Cornell Law Faculty Publications

Federal data sets covering district court and appellate court civil cases for cases terminating in fiscal years 1988 through 2000 are analyzed. Appeals are filed in 10.9 percent of filed cases, and 21.0 percent of cases if one limits the sample to cases with a definitive judgment for plaintiff or defendant. The appeal rate is 39.6 percent in tried cases compared to 10.0 percent of nontried cases. For cases with definitive judgments, the appeal filing rate is 19.0 percent in nontried cases and 40.9 percent in tried cases. Tried cases with definitive judgments are appealed to a conclusion on the …

Multivariate Stochastic Volatility Models: Bayesian Estimation And Model Comparison, Jun Yu, Renate Meyer

Research Collection School Of Economics

In this paper we show that fully likelihood-based estimation and comparison of multivariate stochastic volatility (SV) models can be easily performed via a freely available Bayesian software called WinBUGS. Moreover, we introduce to the literature several new specifications which are natural extensions to certain existing models, one of which allows for time varying correlation coefficients. Ideas are illustrated by fitting, to a bivariate time series data of weekly exchange rates, nine multivariate SV models, including the specifications with Granger causality in volatility, time varying correlations, heavy-tailed error distributions, additive factor structure, and multiplicative factor structure. Empirical results suggest that the …

Bayesian Hierarchical Distributed Lag Models For Summer Ozone Exposure And Cardio-Respiratory Mortality, Yi Huang, Francesca Dominici, Michelle L. Bell

Johns Hopkins University, Dept. of Biostatistics Working Papers

In this paper, we develop Bayesian hierarchical distributed lag models for estimating associations between daily variations in summer ozone levels and daily variations in cardiovascular and respiratory (CVDRESP) mortality counts for 19 U.S. large cities included in the National Morbidity Mortality Air Pollution Study (NMMAPS) for the period 1987 - 1994.

At the first stage, we define a semi-parametric distributed lag Poisson regression model to estimate city-specific relative rates of CVDRESP associated with short-term exposure to summer ozone. At the second stage, we specify a class of distributions for the true city-specific relative rates to estimate an overall effect by …

Multiple Testing And Data Adaptive Regression: An Application To Hiv-1 Sequence Data, Merrill D. Birkner, Sandra E. Sinisi, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

Analysis of viral strand sequence data and viral replication capacity could potentially lead to biological insights regarding the replication ability of HIV-1. Determining specific target codons on the viral strand will facilitate the manufacturing of target specific antiretrovirals. Various algorithmic and analysis techniques can be applied to this application. We propose using multiple testing to find codons which have significant univariate associations with replication capacity of the virus. We also propose using a data adaptive multiple regression algorithm to obtain multiple predictions of viral replication capacity based on an entire mutant/non-mutant sequence profile. The data set to which these techniques …

Gllamm Manual, Sophia Rabe-Hesketh, Anders Skrondal, Andrew Pickles

U.C. Berkeley Division of Biostatistics Working Paper Series

This manual describes a Stata program gllamm that can estimate Generalized Linear Latent and Mixed Models (GLLAMMs). GLLAMMs are a class of multilevel latent variable models for (multivariate) responses of mixed type including continuous responses, counts, duration/survival data, dichotomous, ordered and unordered categorical responses and rankings. The latent variables (common factors or random effects) can be assumed to be discrete or to have a multivariate normal distribution. Examples of models in this class are multilevel generalized linear models or generalized linear mixed models, multilevel factor or latent trait models, item response models, latent class models and multilevel structural equation models. …

Data Adaptive Estimation Of The Treatment Specific Mean, Yue Wang, Oliver Bembom, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

An important problem in epidemiology and medical research is the estimation of the causal effect of a treatment action at a single point in time on the mean of an outcome, possibly within strata of the target population defined by a subset of the baseline covariates. Current approaches to this problem are based on marginal structural models, i.e., parametric models for the marginal distribution of counterfactural outcomes as a function of treatment and effect modifiers. The various estimators developed in this context furthermore each depend on a high-dimensional nuisance parameter whose estimation currently also relies on parametric models. Since misspecification …

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 …

Semiparametric Methods For The Binormal Model With Multiple Biomarkers, Debashis Ghosh

The University of Michigan Department of Biostatistics Working Paper Series

Abstract: In diagnostic medicine, there is great interest in developing strategies for combining biomarkers in order to optimize classification accuracy. A popular model that has been used when one biomarker is available is the binormal model. Extension of the model to accommodate multiple biomarkers has not been considered in this literature. Here, we consider a multivariate binormal framework for combining biomarkers using copula functions that leads to a natural multivariate extension of the binormal model. Estimation in this model will be done using rank-based procedures. We also discuss adjustment for covariates in this class of models and provide a simple …

Cholesky Residuals For Assessing Normal Errors In A Linear Model With Correlated Outcomes: Technical Report, E. Andres Houseman, Louise Ryan, Brent Coull

Harvard University Biostatistics Working Paper Series

Despite the widespread popularity of linear models for correlated outcomes (e.g. linear mixed models and time series models), distribution diagnostic methodology remains relatively underdeveloped in this context. In this paper we present an easy-to-implement approach that lends itself to graphical displays of model fit. Our approach involves multiplying the estimated margional residual vector by the Cholesky decomposition of the inverse of the estimated margional variance matrix. The resulting "rotated" residuals are used to construct an empirical cumulative distribution function and pointwise standard errors. The theoretical framework, including conditions and asymptotic properties, involves technical details that are motivated by Lange and …

Semiparametric Methods For Semi-Competing Risks Problem With Censoring And Truncation, Hongyu Jiang, Jason Fine, Richard J. Chappell

Harvard University Biostatistics Working Paper Series

Studies of chronic life-threatening diseases often involve both mortality and morbidity. In observational studies, the data may also be subject to administrative left truncation and right censoring. Since mortality and morbidity may be correlated and mortality may censor morbidity, the Lynden-Bell estimator for left truncated and right censored data may be biased for estimating the marginal survival function of the non-terminal event. We propose a semiparametric estimator for this survival function based on a joint model for the two time-to-event variables, which utilizes the gamma frailty specification in the region of the observable data. Firstly, we develop a novel estimator …

Censored Linear Regression For Case-Cohort Studies, Bin Nan, Menggang Yu, Jack Kalbfleisch

The University of Michigan Department of Biostatistics Working Paper Series

Right censored data from a classical case-cohort design and a stratified case-cohort design are considered. In the classical case-cohort design, the subcohort is obtained as a simple random sample of the entire cohort, whereas in the stratified design, the subcohort is selected by independent Bernoulli sampling with arbitrary selection probabilities. For each design and under a linear regression model, methods for estimating the regression parameters are proposed and analyzed. These methods are derived by modifying the linear ranks tests and estimating equations that arise from full-cohort data using methods that are similar to the "pseudo-likelihood" estimating equation that has been …

Fabrication Method For Adhesive Pressure Bonding Two Components Together With Closed-Loop Control, Gary B. Hughes, James P. Mcdonald, Arthur V. Schweidler, Lloyd D. Ingle

Statistics

Two components are bonded together in a bonding apparatus using a bonding medium of malleable metallic spheres and a curable adhesive. The two components are bonded by positioning the components in a facing-but-spaced-apart relation in the bonding apparatus with the spheres and the adhesive between the first component and the second component. The bonding apparatus forces the first component toward the second component with sufficient force to bond the spheres to the first component and to the second component, while monitoring at least one measured bonding reaction of the first component and the second component, and controlling the bonding apparatus …

Student Fact Book, Fall 2004, Twenty-Eighth Annual Edition, Wright State University, Office Of Student Information Systems, Wright State University

Wright State University Student Fact Books

The student fact book has general demographic information on all students enrolled at Wright State University for Fall Quarter, 2004.

Infinite Prandtl Number Limit Of Rayleigh-Bénard Convection, Xiaoming Wang

Mathematics and Statistics Faculty Research & Creative Works

We rigorously justify the infinite Prandtl number model of convection as the limit of the Boussinesq approximation to the Rayleigh-Bénard convection as the Prandtl number approaches infinity. This is a singular limit problem involving an initial layer. © 2004 Wiley Periodicals, Inc.

Random Walks On The Torus With Several Generators, Timothy Prescott '02, Francis E. Su

All HMC Faculty Publications and Research

Given n vectors {_i} ∈ [0, 1)^d, consider a random walk on the d-dimensional torus ^d = ℝ^d/ℤ^d generated by these vectors by successive addition and subtraction. For certain sets of vectors, this walk converges to Haar (uniform) measure on the torus. We show that the discrepancy distance D(Q*^k) between the kth step distribution of the walk and Haar measure is bounded below by D(Q*^k) ≥ C₁k^−n/2, where C₁ = C(n, d) is …

Technical Note: Comparative Static Analysis Of Information Value In A Canonical Decision Problem, Jeffrey Keisler

Management Science and Information Systems Faculty Publication Series

To gain insight into the behavior of the value of information, this paper identifies specific rules for a canonical decision problem: the two-act linear loss decision with normal prior probability distributions. Conditions are derived for which the expected value of perfect information increases when mean and standard deviation are both linear functions of an exogenous variable. A variety of richer decision problems can be adapted to the problem, so that the general results obtained here can be immediately applied to understand drivers of information value.

Modulation Of Airway Inflammation By Immunostimulatory Cpg Oligodeoxynucleotides In A Murine Model Of Allergic Aspergillosis, Banani Banerjee, Kevin J. Kelly, Jordan N. Fink, James D. Henderson Jr., Naveen K. Bansal, Viswanath P. Kurup

Mathematics, Statistics and Computer Science Faculty Research and Publications

Allergic aspergillosis is a Th2 T-lymphocyte-mediated pulmonary complication in patients with atopic asthma and cystic fibrosis. Therefore, any therapeutic strategy that selectively inhibits Th2 T-cell activation may be useful in downregulating allergic lung inflammation in asthma. In the present study, we developed a CpG oligodeoxynucleotide (ODN)-based immune intervention of allergic inflammation in a mouse model of allergic aspergillosis. Four different groups of mice were used in a short-term immunization protocol. Three experimental groups of animals (groups 1 to 3) were sensitized with Aspergillus fumigatus antigens. Animals in group 1 were immunized with A. fumigatus antigen alone, while those in group …

The Merciful Capital Juror, Theodore Eisenberg, Stephen P. Garvey

Cornell Law Faculty Publications

We examine the role of mercy in capital sentencing along three dimensions. We first explain why mercy is a philosophically problematic virtue, and second, why it presently holds an ambiguous status within constitutional doctrine. Finally, we draw on interviews with jurors who served on capital cases in order better to understand how the behavior of merciful jurors compares to the behavior of their less merciful counterparts. Among other things, we find that merciful jurors tend to be better educated and to attend religious services regularly. We also find that merciful jurors are, as one might reasonably expect, more apt to …

Deadline Analysis Of Interrupt-Driven Software, Dennis Brylow, Jens Palsberg

Mathematics, Statistics and Computer Science Faculty Research and Publications

Real-time, reactive, and embedded systems are increasingly used throughout society (e.g., flight control, railway signaling, vehicle management, medical devices, and many others). For real-time, interrupt-driven software, timely interrupt handling is part of correctness. It is vital for software verification in such systems to check that all specified deadlines for interrupt handling are met. Such verification is a daunting task because of the large number of different possible interrupt arrival scenarios. For example, for a Z86-based microcontroller, there can be up to six interrupt sources and each interrupt can arrive during any clock cycle. Verification of such systems has traditionally relied …

Bottleneck Analysis Of Cports, Sreekalyana Chakravarthy Kajuluri

Electrical & Computer Engineering Theses & Dissertations

CPortS is a transportation logistics simulation that models the flow of military cargo through a seaport and the interaction of the cargo with the port resources and infrastructure. It provides information about the seaport's capabilities, how the cargo has been handled, how many days the cargo took to clear a particular port area, and the overall throughput of the seaport. The model is highly data intensive since it models the huge traffic in a real seaport.

Bottlenecks reduce system performance. Systems that are traffic intensive or simulations of systems, which are data intensive, encounter bottlenecks, which reduce their performance. In …

Estimating The Retransformed Mean In A Heteroscedastic Two-Part Model, Alan H. Welsh, Xiao-Hua Zhou

UW Biostatistics Working Paper Series

Two distribution free estimators are proposed to estimate the mean of a dependent variable after fitting a semiparametric two-part heteroscedastic regression model to a transformation of the dependent variable. We show that the proposed estimators are consistent and have asymptotic normal distributions. We also compare their finite-sample performance in a simulation study. Finally, we illustrate the proposed methods in a real-world example of predicting in-patient health care costs.

History-Adjusted Marginal Structural Models And Statically-Optimal Dynamic Treatment Regimes, Mark J. Van Der Laan, Maya L. Petersen

U.C. Berkeley Division of Biostatistics Working Paper Series

Marginal structural models (MSM) provide a powerful tool for estimating the causal effect of a treatment. These models, introduced by Robins, model the marginal distributions of treatment-specific counterfactual outcomes, possibly conditional on a subset of the baseline covariates. Marginal structural models are particularly useful in the context of longitudinal data structures, in which each subject's treatment and covariate history are measured over time, and an outcome is recorded at a final time point. However, the utility of these models for some applications has been limited by their inability to incorporate modification of the causal effect of treatment by time-varying covariates. …

A Hypothesis Test For The End Of A Common Source Outbreak, Ron Brookmeyer, Xiaojun You

Johns Hopkins University, Dept. of Biostatistics Working Papers

The objective of this paper is to develop a hypothesis testing procedure to determine whether a common source outbreak has ended. We do not assume that the calendar date of exposure to the pathogen is known. We assume an underlying parametric model for the incubation period distribution of a 2-paramter exponential model with a guarantee time, although the parameters are not assumed to be known. The hypothesis testing procedure is based on the spacings between ordered calendar dates of disease onset of the cases. A simulation study was performed to evaluate the robustness of the methods to a lognormal model …

Optimal Sampling Times In Bioequivalence Studies Using A Simulated Annealing Algorithm , Leena Choi, Brian Caffo, Charles Rohde

Johns Hopkins University, Dept. of Biostatistics Working Papers

In pharmacokinetic (PK) studies, blood samples are taken over time on subjects after the administration of a drug to measure the time-course of the plasma drug concentrations. In bioequivalence studies, the trapezoidal rule on the sampled time points is often used to estimate the area under the plasma concentration-time curve, a quantity of principle interest. This manuscript investigates the choice of sampling time points to estimate the area under the curve. In particular, we explore the relative merits of several objective functions, those functions which are minimized with respect to the sampling times to obtain an optimal study design. We …