Statistical Models Commons^™

Locally Efficient Estimation With Bivariate Right Censored Data , Christopher M. Quale, Mark J. Van Der Laan, James M. Robins

U.C. Berkeley Division of Biostatistics Working Paper Series

Estimation for bivariate right censored data is a problem that has had much study over the past 15 years. In this paper we propose a new class of estimators for the bivariate survivor function based on locally efficient estimation. The locally efficient estimator takes bivariate estimators Fn and Gn of the distributions of the time variables T1,T2 and the censoring variables C1,C2, respectively, and maps them to the resulting estimator. If Fn and Gn are consistent estimators of F and G, respectively, then the resulting estimator will be nonparametrically efficient (thus the term ``locally efficient''). However, if either Fn or …

An Empirical Study Of Marginal Structural Models For Time-Independent Treatment, Tanya A. Henneman, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

In non-randomized treatment studies a significant problem for statisticians is determining how best to adjust for confounders. Marginal structural models (MSMs) and inverse probability of treatment weighted (IPTW) estimators are useful in analyzing the causal effect of treatment in observational studies. Given an IPTW estimator a doubly robust augmented IPTW (AIPTW) estimator orthogonalizes it resulting in a more e±cient estimator than the IPTW estimator. One purpose of this paper is to make a practical comparison between the IPTW estimator and the doubly robust AIPTW estimator via a series of Monte- Carlo simulations. We also consider the selection of the optimal …

The Kpss Test With Seasonal Dummies, Sainan Jin, Sainan Jin

Research Collection School Of Economics

It is shown that the KPSS test for stationarity may be applied without change to regressions with seasonal dummies. In particular, the limit distribution of the KPSS statistic is the same under both the null and alternative hypotheses whether or not seasonal dummies are used.

Accelerated Hazards Model: Method, Theory And Applications, Ying Qing Chen, Nicholas P. Jewell, Jingrong Yang

U.C. Berkeley Division of Biostatistics Working Paper Series

In an accelerated hazards model, the hazard functions of a failure time are related through the time scale-change, which is often a function of covariates and associated parameters. When the hazard functions have special properties, such as monotonicity in time, the parameters may be clinically meaningful in measuring a treatment effect. This paper reviews methodological and theoretical development of this model. Applications of the accelerated hazards model including sample size calculation in clinical trials, are also explored.

Locally Efficient Estimation Of Regression Parameters Using Current Status Data, Chris Andrews, Mark J. Van Der Laan, James M. Robins

U.C. Berkeley Division of Biostatistics Working Paper Series

In biostatistics applications interest often focuses on the estimation of the distribution of a time-variable T. If one only observes whether or not T exceeds an observed monitoring time C, then the data structure is called current status data, also known as interval censored data, case I. We consider this data structure extended to allow the presence of both time-independent covariates and time-dependent covariate processes that are observed until the monitoring time. We assume that the monitoring process satisfies coarsening at random.

Our goal is to estimate the regression parameter beta of the regression model T = Z*beta+epsilon where the …

Why Prefer Double Robust Estimates? Illustration With Causal Point Treatment Studies, Romain Neugebauer, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

In point treatment marginal structural models with treatment A, outcome Y and covariates W, causal parameters can be estimated under the assumption of no unobserved confounders. Three estimates can be used: the G-computation, Inverse Probability of Treatment Weighted (IPTW) or Double Robust (DR) estimates. The properties of the IPTW and DR estimates are known under an assumption on the treatment mechanism that we name "Experimental Treatment Assignment" (ETA) assumption. We show that the DR estimating function is unbiased when the ETA assumption is violated if the model used to regress Y on A and W is correctly specified. The practical …

Semiparametric Regression Analysis On Longitudinal Pattern Of Recurrent Gap Times, Ying Qing Chen, Mei-Cheng Wang, Yijian Huang

U.C. Berkeley Division of Biostatistics Working Paper Series

In longitudinal studies, individual subjects may experience recurrent events of the same type over a relatively long period of time. The longitudinal pattern of the gaps between the successive recurrent events is often of great research interest. In this article, the probability structure of the recurrent gap times is first explored in the presence of censoring. According to the discovered structure, we introduce the proportional reverse-time hazards models with unspecified baseline functions to accommodate heterogeneous individual underlying distributions, when the ongitudinal pattern parameter is of main interest. Inference procedures are proposed and studied by way of proper riskset construction. The …

Visualization Methods: A Comparative Study Of New, Traditional And Robust Procedures, Kimberly Crimin

Dissertations

Two major goals in discriminant analysis are discrimination and classification. In discrimination, the goal is to describe graphically (visualization) different features of several known groups. In classification, the goal is to allocate unknown observations to one of several known groups. We have developed new visualization procedures based on traditional estimating procedures and also on robust estimating procedures. We have further developed robust classification procedures. We propose several robust classification procedures based on coordinatewise and affine equivariant, rank-based robust estimates. Empirical studies are performed over many different error distributions. These studies result in empirical efficiencies of the robust and traditional procedures. …

Nonlinear Regression Based On Ranks, Asheber Abebe

Dissertations

This study presents robust methods for estimating parameters of nonlinear regression models. The proposed methods obtain estimates by minimizing rankbased dispersions instead of the Euclidean norm. We focus on the Wilcoxon and generalized signed-rank dispersion functions. Asymptotic properties of the estimators are established under mild regularity conditions similar to those used in least squares and least absolute deviations estimation. The study also shows that by considering the generalized signed-rank dispersion we obtain a class of estimators that encompasses most of the existing popular nonlinear regression estimators. As in linear models, these rank-based procedures provide estimators that are highly efficient. This …

Inference For Proportional Mean Residual Life Model In The Presence Of Censoring, Ying Q. Chen, Nicholas P. Jewell

U.C. Berkeley Division of Biostatistics Working Paper Series

As a function of time t, mean residual life is defined as remaining life expectancy of a subject given its survival to t. It plays an important role in many research areas to characterise stochastic behavior of survival over time. Similar to the Cox proportional hazard model, the proportional mean residual life model were proposed in statistical literature to study association between the mean residual life and individual subject's explanatory covariates. In this article, we will study this model and develop appropriate inference procedures in presence of censoring. Numerical studies including simulation and real data analysis are presented as well.

Regression Analysis Of Recurrent Gap Times With Time-Dependent Covariates, Ying Qing Chen, Mei-Cheng Wang, Yijian Huang

U.C. Berkeley Division of Biostatistics Working Paper Series

Individual subjects may experience recurrent events of same type over a relatively long period of time in a longitudinal study. Researchers are often interested in the distributional pattern of gaps between the successive recurrent events and their association with certain concomitant covariates as well. In this article, their probability structure is investigated in presence of censoring. According to the identified structure, we introduce the proportional reverse-time hazards models that allow arbitrary baseline function for every individual in the study, when the time-dependent covariates effect is of main interest. Appropriate inference procedures are proposed and studied to estimate the parameters of …

Estimating Causal Parameters In Marginal Structural Models With Unmeasured Confounders Using Instrumental Variables, Tanya A. Henneman, Mark Johannes Van Der Laan, Alan E. Hubbard

U.C. Berkeley Division of Biostatistics Working Paper Series

For statisticians analyzing medical data, a significant problem in determining the causal effect of a treatment on a particular outcome of interest, is how to control for unmeasured confounders. Techniques using instrumental variables (IV) have been developed to estimate causal parameters in the presence of unmeasured confounders. In this paper we apply IV methods to both linear and non-linear marginal structural models. We study a specific class of generalized estimating equations that is appropriate to these data, and compare the performance of the resulting estimator to the standard IV method, a two-stage least squares procedure. Our results are applied to …

Marginal Regression Of Gaps Between Recurrent Events, Yijian Huang, Ying Qing Chen

U.C. Berkeley Division of Biostatistics Working Paper Series

Recurrent event data typically exhibit the phenomenon of intra-individual correlation, owing to not only observed covariates but also random effects. In many applications, the population can be reasonably postulated as a heterogeneous mixture of individual renewal processes, and the inference of interest is the effect of individual-level covariates. In this article, we suggest and investigate a marginal proportional hazards model for gaps between recurrent events. A connection is established between observed gap times and clustered survival data, however, with informative cluster size. We then derive a novel and general inference procedure for the latter, based on a functional formulation of …

Identification Of Regulatory Elements Using A Feature Selection Method, Sunduz Keles, Mark J. Van Der Laan, Michael B. Eisen

U.C. Berkeley Division of Biostatistics Working Paper Series

Many methods have been described to identify regulatory motifs in the transcription control regions of genes that exhibit similar patterns of gene expression across a variety of experimental conditions. Here we focus on a single experimental condition, and utilize gene expression data to identify sequence motifs associated with genes that are activated under this experimental condition. We use a linear model with two way interactions to model gene expression as a function of sequence features (words) present in presumptive transcription control regions. The most relevant features are selected by a feature selection method called stepwise selection with monte carlo cross …

Theater-Level Stochastic Air-To-Air Engagement Modeling Via Event Occurrence Networks Using Piecewise Polynomial Approximation, David R. Denhard

Theses and Dissertations

This dissertation investigates a stochastic network formulation termed an event occurrence network (EON). EONs are graphical representations of the superposition of several terminating counting processes. An EON arc represents the occurrence of an event from a group of (sequential) events before the occurrence of events from other event groupings. Events between groups occur independently, but events within a group occur sequentially. A set of arcs leaving a node is a set of competing events, which are probabilistically resolved by order relations. An important EON metric is the probability of being at a particular node or set of nodes at time …

Mixture Hazards Models With Additive Random Effects Accounting For Treatment Effectiveness Lag Time, Ying Qing Chen, C. A. Rohde, M.-C. Wang

U.C. Berkeley Division of Biostatistics Working Paper Series

In many clinical trials to evaluate treatment efficacy, it is believed that there may exist latent treatment effectiveness lag times after which medical treatment procedure or chemical compound would be in full effect. In this article, semiparametric regression models are proposed and studied for estimating the treatment effect accounting for such latent lag times. The new models take advantage of the invariance property of the additive hazards model in marginalising over an additive latent variable; parameters in the models are thus easily estimated and interpreted, while the flexibility of not having to specify the baseline hazard function is preserved. Monte …

A Class Of Semiparametric Scale-Change Hazards Regression Models And Its Adequacy For Censored Survival Data, Ying Qing Chen

U.C. Berkeley Division of Biostatistics Working Paper Series

A class of semiparametric hazards regression models called the accelerated hazards models was introduced to identify the covariate effect characterized by the scale-change between hazard functions. In this article, we compare the accelerated hazards models with several other popular classes of regression models in statistical literature for censored survival data. We also propose and study some test statistics to assess the models' adequacy. Simulation studies are conducted to evaluate the performance of the test statistics. Actual clinical trials data are analyzed to demonstrate the proposed models and test statistics.

Monte Carlo Simulation In Environmental Risk Assessment--Science, Policy And Legal Issues, Susan R. Poulter

RISK: Health, Safety & Environment (1990-2002)

Dr. Poulter notes that agencies should anticipate judicial requirements for justification of Monte Carlo simulations and, meanwhile, should consider, e.g., whether their use will make risk assessment policy choices more opaque or apparent.

Mark-Recapture Creel Survey And Survival Models, Shampa Saha

Mathematics & Statistics Theses & Dissertations

In this dissertation, we consider a model based approach to the estimation of exploitation rate of a fish population by combining mark-recapture procedures with a creel survey. We also consider the analysis of a proportional hazards survival model for randomly censored observations, known as the Koziol-Green model. The model assumes that the lifetime survivor function is a power of the censored time survivor function.

In Chapter 2, we introduce the model based approach to the estimation of the exploitation rate of a fish population by combining mark-recapture procedures with a creel survey. We assume that in the beginning of a …

A Monte Carlo Model Of Uncertainty In A Deterministic Hazardous Waste Transportation Risk Assessment, Michael A. Cowen

Masters Theses

This thesis is aimed at developing and applying advanced modeling tools in the prediction of risk to the general public from transportation of chemical waste on public highways. The modeling tools developed can then be used to compare alternative waste management scenarios. The application considered is related to the transport of hazardous waste generated by the United States Department of Energy (DOE) to current treatment, storage, and disposal facilities. DOE is currently considering four different scenarios.

The application considered can be more specifically defined as an analysis of the risk to the general public from transporting the 63 shipments of …

A New Soft Tissue Analysis : To Establish Facial Esthetic Norms In Young Adult Females, Anne Béress

Loma Linda University Electronic Theses, Dissertations & Projects

Two hundred and fifty-five articles, books, and masters theses were reviewed for the most frequently applied soft tissue measurements in the literature in order to develop a new soft tissue analysis computer program that includes established soft tissue measurements and the newly developed globe analysis. A meta analysis of 20 normal occlusion studies, was performed to obtain mean values and standard deviations to form a large sample size. Inclusion criteria for articles in the meta analysis were normal occlusion, no orthodontic treatment, pleasing faces, statement on age, race, and lip position of the population. For the lateral view, angular and …

Effects Of Tactical Responses And Risk Aversion On Farm Wheat Supply, Ross S. Kingwell

Natural Resources Research Articles

A discrete stochastic programming model of the farming system of the eastern wheatbelt of Western Australia is used to examine the effect of tactical responses and risk aversion on wheat supply. Including within-season tactical changes to wheat areas decreases the own-price elasticity of supply. By contrast, introducing risk aversion has no consistent effect on the own-price elasticity of supply. The implications for supply models are discussed.

Predicting Utility Bills For Air Combat Command A Study Of Forecasting Techniques, William L. Luthie

Engineering Management & Systems Engineering Theses & Dissertations

Many companies use forecasting techniques as a tool in managing their assets. Trends in such items as sales, population and inventory levels have all been determined at one time or another using forecasting, yet research indicates that these tools have not been utilized to predict utility budgets. This research was conducted to determine if such techniques could be applied to the specific task of predicting the utility bill at an Air Force base. Three quantitative models were chosen, the Moving Average, Exponential Smoothing and Regression, to determine their applicability to the task at hand. One base within Air Combat Command, …

Groundwater Model Parameter Estimation Using Response Surface Methodology, Richard M. Cotman

Theses and Dissertations

This thesis examined the use of response surface methodology (RSM) to estimate the parameters of a finite-element groundwater model. An existing two-dimensional, steady-state flow model of a fractured carbonate groundwater system in southwestern Ohio served as the calibration target data set. A Plackett-Burman screening design showed that only four of the ten hydraulic conductivity zones significantly contributed to the output of the finite-element model. Also, the effective porosity parameter did not significantly affect the model's output. Using only the four significant hydraulic conductivity parameters; four two-level, four-factor designed experiments were conducted to exploit the first-order response surface defined by a …

Comparing Traditional Statistical Models With Neural Network Models: The Case Of The Relation Of Human Performance Factors To The Outcomes Of Military Combat, William Oliver Hedgepeth

Engineering Management & Systems Engineering Theses & Dissertations

Statistics and neural networks are analytical methods used to learn about observed experience. Both the statistician and neural network researcher develop and analyze data sets, draw relevant conclusions, and validate the conclusions. They also share in the challenge of creating accurate predictions of future events with noisy data.

Both analytical methods are investigated. This is accomplished by examining the veridicality of both with real system data. The real system used in this project is a database of 400 years of historical military combat. The relationships among the variables represented in this database are recognized as being hypercomplex and nonlinear.

The …

Estimating Groundwater Flow Parameters Using Response Surface Methodology, Leo C. Adams

Theses and Dissertations

This thesis examined the use of response surface methodology RSM as a parameter estimation technique in the field of groundwater flow modeling. Using RSM, an attempt was made to calibrate three hydraulic parameters porosity, transverse permeability, and rate of recharge of an existing two- dimensional, steady-state flow model. The model simulated groundwater flow for a portion of landfill 10 located on Wright-Patterson Air Force Base, Ohio. The model had previously been calibrated by graphical matching observed water-levels to predicted water-levels. Using the parameter values from the earlier calibration effort as a starting point, a central composite design was developed and …

Developing Prediction Regions For A Time Series Model For Hurricane Forecasting, William Cheman

Theses and Dissertations

In this thesis, a class of time series models for forecasting a hurricanes future position based on its previous positions and a generalized model of hurricane motion are examined and extended. Results of a literature review suggest that meteorological models continue to increase in complexity while few statistical approaches, such as linear regression, have been successfully applied. An exception is provided by a certain class of time series models that appear to forecast storms almost as well as current meteorological models without their tremendous complexity. A suggestion for enhancing the performance of these time series models is pursued through an …

An In Vitro Study Comparing The Conventional Step-Back Instrumentation Technique To A Combination Step-Back/Ultrasonic Technique, James A. Eberhardt

Loma Linda University Electronic Theses, Dissertations & Projects

Cleaning and shaping the root canal system is an important phase of endodontic therapy, and must be performed thoroughly and completely if successful root canal therapy is to be expected. A number of investigators have compared different methods of cleaning and shaping of the root canal system. The purpose of this study was to compare the effectiveness of the conventional step-back technique with that of a combination step-back/ultrasonic technique. This combination technique is a modification of the conventional step-back technique using an ultrasonic instrument alternately with hand instrumentation. Utilizing 40 canals from extracted human mandibular molar teeth with a curvature …

Radar Cross Section Models For Limited Aspect Angle Windows, Mark C. Robinson

Theses and Dissertations

This thesis presents a method for building Radar Cross Section (RCS) models of aircraft based on static data taken from limited aspect angle windows. These models statistically characterize static RCS. This is done to show that a limited number of samples can be used to effectively characterize static aircraft RCS. The optimum models are determined by performing both a Kolmogorov and a Chi-Square goodness-of-fit test comparing the static RCS data with a variety of probability density functions (pdf) that are known to be effective at approximating the static RCS of aircraft. The optimum parameter estimator is also determined by the …

The Development Of A Performance Measurement Concept For The Royal Australian Air Force, David R. Mcdonald

Theses and Dissertations

he Royal Australian Air Force (RAAF) needed to develop performance measurements (PMs) to support its Program Management and Budgeting (PMB) System. This research assessed the use of the concepts of the Theory of Constraints (TOC) to develop those PMs. The literature indicated that: traditional accounting PMs were not always suitable in an environment of continuous improvement; Activity Based Costing did not provide the required measures; and non-financial PMs were supplanting the older measures. Further, governments faced unique problems in developing PMs, particularly in defining the outcomes to be measured. Using the Critical Theory and Action Research methodologies, and a case …