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Nonparametric Identifiability Of Finite Mixture Models With Covariates For Estimating Error Rate Without A Gold Standard, Zheyu Wang, Xiao-Hua Zhou 2014 COBRA

Nonparametric Identifiability Of Finite Mixture Models With Covariates For Estimating Error Rate Without A Gold Standard, Zheyu Wang, Xiao-Hua Zhou

UW Biostatistics Working Paper Series

Finite mixture models provide a flexible framework to study unobserved entities and have arisen in many statistical applications. The flexibility of these models in adapting various complicated structures makes it crucial to establish model identifiability when applying them in practice to ensure study validity and interpretation. However, researches to establish the identifiability of finite mixture model are limited and are usually restricted to a few specific model configurations. Conditions for model identifiability in the general case have not been established. In this paper, we provide conditions for both local identifiability and global identifiability of a finite mixture model. The former ...


Statistical Analysis Of Enhanced Ctl Killing Activity Against Irradiated Tumor Cells, Catannian Sanogo 2014 Georgia State University

Statistical Analysis Of Enhanced Ctl Killing Activity Against Irradiated Tumor Cells, Catannian Sanogo

Georgia State Undergraduate Research Conference

No abstract provided.


A Scalable Supervised Subsemble Prediction Algorithm, Stephanie Sapp, Mark J. van der Laan 2014 COBRA

A Scalable Supervised Subsemble Prediction Algorithm, Stephanie Sapp, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

Subsemble is a flexible ensemble method that partitions a full data set into subsets of observations, fits the same algorithm on each subset, and uses a tailored form of V-fold cross-validation to construct a prediction function that combines the subset-specific fits with a second metalearner algorithm. Previous work studied the performance of Subsemble with subsets created randomly, and showed that these types of Subsembles often result in better prediction performance than the underlying algorithm fit just once on the full dataset. Since the final Subsemble estimator varies depending on the data used to create the subset-specific fits, different strategies for ...


Asymptotic Theory For Three Infinite Dimensional Diffusion Processes, Youzhou Zhou 2014 McMaster University

Asymptotic Theory For Three Infinite Dimensional Diffusion Processes, Youzhou Zhou

Open Access Dissertations and Theses

This thesis is centered around three infinite dimensional diffusion processes:

(i). the infinitely-many-neutral-alleles diffusion model [Ethier and Kurtz, 1981],

(ii). the two-parameter infinite dimensional diffusion model [Petrov, 2009] and [Feng and Sun, 2010],

(iii). the infinitely-many-alleles diffusion with symmetric dominance [Ethier and Kurtz, 1998].

The partition structures, the ergodic inequalities and the asymptotic theory of these three models are discussed. In particular, the asymptotic theory turns out to be the major contribution of this thesis.

In Chapter 2, a slightly altered version of Kingman's one-to-one correspondence theorem on partition structures is provided, which in turn becomes a handy tool ...


Likelihood-Based Inferential Methods For Some Flexible Cure Rate Models, Suvra Pal 2014 McMaster University

Likelihood-Based Inferential Methods For Some Flexible Cure Rate Models, Suvra Pal

Open Access Dissertations and Theses

Recently, the Conway-Maxwell Poisson (COM-Poisson) cure rate model has been proposed which includes as special cases some of the well-known cure rate models discussed in the literature. Data obtained from cancer clinical trials are often right censored and the expectation maximization (EM) algorithm can be efficiently used for the determination of the maximum likelihood estimates (MLEs) of the model parameters based on right censored data.

By assuming the lifetime distribution to be exponential, lognormal, Weibull, and gamma, the necessary steps of the EM algorithm are developed for the COM-Poisson cure rate model and some of its special cases. The inferential ...


Nutrition, Childhood Development And Prevalence Of Anemia In Ghanaian Children: Analysis Of Health Survey, Joycelyne E. Ewusie 2014 McMaster University

Nutrition, Childhood Development And Prevalence Of Anemia In Ghanaian Children: Analysis Of Health Survey, Joycelyne E. Ewusie

Open Access Dissertations and Theses

Malnutrition and Anemia in children continue to be major public health challenges in most developing countries, particularly in Africa. Malnutrition and Anemia pervade all aspects of their health, growth, cognitive and social development. They lead to irreversible and lifelong effects that prevent children from realising their full potential. This study was designed to examine the prevalence and determinants of malnutrition and anemia in children under 5 years of age in the Ghanaian population. This research is based on data from the Ghana Demographic and Health Survey (GDHS) 2008, obtained from the Ghana Statistical Service (GSS). The survey is an extensive ...


What Residualizing Predictors In Regression Analyses Does (And What It Does Not Do), Lee H. Wurm, Sebastiano A. Fisicaro 2014 Wayne State University

What Residualizing Predictors In Regression Analyses Does (And What It Does Not Do), Lee H. Wurm, Sebastiano A. Fisicaro

Psychology Faculty Research Publications

Psycholinguists are making increasing use of regression analyses and mixed-effects modeling. In an attempt to deal with concerns about collinearity, a number of researchers orthogonalize predictor variables by residualizing (i.e., by regressing one predictor onto another, and using the residuals as a stand-in for the original predictor). In the current study, the effects of residualizing predictor variables are demonstrated and discussed using ordinary least-squares regression and mixed-effects models. Some of these effects are almost certainly not what the researcher intended and are probably highly undesirable. Most importantly, what residualizing does not do is change the result for the residualized ...


Introduction To Targeted Learning, Laura Balzer 2014 SelectedWorks

Introduction To Targeted Learning, Laura Balzer

Laura B. Balzer

No abstract provided.


A Cellular Automaton Model For Traffic Flow - Investigating The Effect Of Turning, Tracy Finner, Matthew A. Beauregard 2014 Indiana University – Purdue University Fort Wayne

A Cellular Automaton Model For Traffic Flow - Investigating The Effect Of Turning, Tracy Finner, Matthew A. Beauregard

American Journal of Undergraduate Research

A cellular automaton model is proposed, modeling vehicular traffic flow on a two dimensional lattice in which the vehicles turn at an intersection with a given probability. It is shown that the introduction of turning reduces the long-term average velocity, and can be predicted by a power law depending on the probability of a vehicle turning and the density of cars. The reduction in speed decreases rapidly once the light cycle length surpasses a certain threshold, the value of which can be predicted from the observed power law.


Leslie Matrices And Women Population In The United States Of America, Brittney Nelson, Denise T. Reid, Antonija Tangar, Jos´E V´Elez-Marulanda 2014 Indiana University – Purdue University Fort Wayne

Leslie Matrices And Women Population In The United States Of America, Brittney Nelson, Denise T. Reid, Antonija Tangar, Jos´E V´Elez-Marulanda

American Journal of Undergraduate Research

This research tests the accuracy of the Leslie matrix, which is a discrete age-structured method that uses fertility and survival rates, as a tool for predicting women population. Based on available data for the year 2000, we have constructed a Leslie matrix that predicts female population in the United States for every five years from the years 2000 to 2020. To test the accuracy of this method, we compare the aforementioned obtained projected data for the year 2010 with the actual data for women population in the United States obtained by the 2010 U.S. Census.


Bounds To Evaluate The Pure/Natural Direct Effect Without Cross-World Counterfactual Independence, Eric Tchetgen Tchetgen, Kelesitse Phiri 2014 COBRA

Bounds To Evaluate The Pure/Natural Direct Effect Without Cross-World Counterfactual Independence, Eric Tchetgen Tchetgen, Kelesitse Phiri

Harvard University Biostatistics Working Paper Series

No abstract provided.


A Global Partial Likelihood Estimator Of The Time-Varying Effects For Time-Dependent Treatment, Huazhen Lin, Zhe Fei, Yi Li 2014 COBRA

A Global Partial Likelihood Estimator Of The Time-Varying Effects For Time-Dependent Treatment, Huazhen Lin, Zhe Fei, Yi Li

The University of Michigan Department of Biostatistics Working Paper Series

The timing of time-dependent treatment - e.g., when to perform kidney transplantation - is an important factor for evaluating treatment efficacy. A naive comparison between the treatment and nontreatment groups, while ignoring the timing of treatment, typically yields results that might biasedly favor the treatment group, as only patients who survive long enough will get treated. On the other hand, studying the effect of time-dependent treatment is often complex, as it involves modeling treatment history and accounting for the possible time-varying nature of the treatment effect. We propose a varying-coefficient Cox model that investigates the efficacy of time-dependent treatment by utilizing ...


A Unification Of Mediation And Interaction: A Four-Way Decomposition, Tyler J. VanderWeele 2014 COBRA

A Unification Of Mediation And Interaction: A Four-Way Decomposition, Tyler J. Vanderweele

Harvard University Biostatistics Working Paper Series

It is shown that the overall effect of an exposure on an outcome, in the presence of a mediator with which the exposure may interact, can be decomposed into four components: (i) the effect of the exposure in the absence of the mediator, (ii) the interactive effect when the mediator is left to what it would be in the absence of exposure, (iii) a mediated interaction, and (iv) a pure mediated effect. These four components, respectively, correspond to the portion of the effect that is due to neither mediation nor interaction, to just interaction (but not mediation), to both mediation ...


Computing And Approximation Methods For The Distribution Of Multivariate Aggregate Claims, Tao Jin 2014 Western University

Computing And Approximation Methods For The Distribution Of Multivariate Aggregate Claims, Tao Jin

University of Western Ontario - Electronic Thesis and Dissertation Repository

Insurance companies typically face multiple sources (types) of claims. Therefore, modeling dependencies among different types of risks is extremely important for evaluating the aggregate claims of an insurer. In the first part of this thesis, we consider three classes of bivariate counting distributions and the corresponding compound distributions introduced in a 1996 paper by Hesselager. We implement the recursive methods for computing the joint probability functions derived by Hesselager and then compare the results with those obtained from fast Fourier transform (FFT) methods. In applying the FFT methods, we extend the concept of exponential tilting for univariate FFT proposed by ...


Understanding Underrepresentation: Women In Mathematics And Related Fields, Cathy Kessel 2014 SelectedWorks

Understanding Underrepresentation: Women In Mathematics And Related Fields, Cathy Kessel

Cathy Kessel

No abstract provided.


Efficiently Identifying Failures Using Quantitative Tests, Matrix-Pooling And The Em-Algorithm, Brett Hanscom, Susanne May, Jim Hughes 2014 COBRA

Efficiently Identifying Failures Using Quantitative Tests, Matrix-Pooling And The Em-Algorithm, Brett Hanscom, Susanne May, Jim Hughes

UW Biostatistics Working Paper Series

Pooled-testing methods can greatly reduce the number of tests needed to identify failures in a collection of samples. Existing methodology has focused primarily on binary tests, but there is a clear need for improved efficiency when using expensive quantitative tests, such as tests for HIV viral load in resource-limited settings. We propose a matrix-pooling method which, based on pooled-test results, uses the EM algorithm to identify individual samples most likely to be failures. Two hundred datasets for each of a wide range of failure prevalence were simulated to test the method. When the measurement of interest was normally distributed, at ...


Inter-Adapt - An Interactive Tool For Designing And Evaluating Randomized Trials With Adaptive Enrollment Criteria, Aaron Joel Fisher, Harris Jaffee, Michael Rosenblum 2014 COBRA

Inter-Adapt - An Interactive Tool For Designing And Evaluating Randomized Trials With Adaptive Enrollment Criteria, Aaron Joel Fisher, Harris Jaffee, Michael Rosenblum

Johns Hopkins University, Dept. of Biostatistics Working Papers

We consider the problem of designing a randomized trial when there is prior evidence that the experimental treatment may be more effective for certain groups of participants, such as those with a certain biomarker or risk score at baseline. Randomized trial designs have been proposed that dynamically adapt enrollment criteria based on accrued data, with the goal of learning if the treatment benefits the overall population, only a certain subpopulation, or neither. We introduce the interAdapt software tool, a Shiny application which provides a user friendly interface for constructing and evaluating certain adaptive trial designs. These designs are automatically compared ...


Interpretation And Prediction Of A Logistic Model, Joseph M. Hilbe 2014 SelectedWorks

Interpretation And Prediction Of A Logistic Model, Joseph M. Hilbe

Joseph M Hilbe

A basic overview of how to model and interpret a logistic regression model, as well as how to obtain the predicted probability or fit of the model and calculate its confidence intervals. R code used for all examples; some Stata is provided as a contrast.


A Predictive Enrichment Procedure To Identify Potential Responders To A New Therapy For Randomized, Comparative, Controlled Clinical Studies, Junlong Li, Lihui Zhao, Lu Tian, Tianxi Cai, Brian Claggett, Andrea Callegaro, Benjamin Dizier, Bart Spiessens, Fernando Ulloa-Montoya, L. J. Wei 2014 COBRA

A Predictive Enrichment Procedure To Identify Potential Responders To A New Therapy For Randomized, Comparative, Controlled Clinical Studies, Junlong Li, Lihui Zhao, Lu Tian, Tianxi Cai, Brian Claggett, Andrea Callegaro, Benjamin Dizier, Bart Spiessens, Fernando Ulloa-Montoya, L. J. Wei

Harvard University Biostatistics Working Paper Series

No abstract provided.


Asymmetric Empirical Similarity, Joshua C. Teitelbaum 2014 Georgetown University Law Center

Asymmetric Empirical Similarity, Joshua C. Teitelbaum

Georgetown Law Faculty Publications and Other Works

The paper offers a formal model of analogical legal reasoning and takes the model to data. Under the model, the outcome of a new case is a weighted average of the outcomes of prior cases. The weights capture precedential influence and depend on fact similarity (distance in fact space) and precedential authority (position in the judicial hierarchy). The empirical analysis suggests that the model is a plausible model for the time series of U.S. maritime salvage cases. Moreover, the results evince that prior cases decided by inferior courts have less influence than prior cases decided by superior courts.


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