Open Access. Powered by Scholars. Published by Universities.®

Statistics and Probability Commons

Open Access. Powered by Scholars. Published by Universities.®

5,651 Full-Text Articles 7,919 Authors 1,229,421 Downloads 146 Institutions

All Articles in Statistics and Probability

Faceted Search

5,651 full-text articles. Page 1 of 124.

Beta-Binomial Kriging: A New Approach To Modeling Spatially Correlated Proportions, Aimee Schwab 2015 University of Nebraska-Lincoln

Beta-Binomial Kriging: A New Approach To Modeling Spatially Correlated Proportions, Aimee Schwab

Dissertations and Theses in Statistics

Spatially correlated count data sets appear often in applied data analysis problems, but there is little consensus in the literature about how best to analyze the data. The two prevailing approaches provide accurate parameter estimates and predictions, at the cost of model interpretability and simplicity. This dissertation will present a new approach to modeling spatially correlated binomial observations: beta-binomial kriging. The model proposed here is a modified form of spatial kriging which assumes the data are generated from a correlated beta-binomial distribution. Given this assumption, the spatial parameters and predicted values can be estimated using simple matrix algebra. Beta-binomial kriging ...


Comparison Of Two Parameter Estimation Techniques For Stochastic Models, Thomas C. Robacker 2015 East Tennessee State University

Comparison Of Two Parameter Estimation Techniques For Stochastic Models, Thomas C. Robacker

Electronic Theses and Dissertations

Parameter estimation techniques have been successfully and extensively applied to deterministic models based on ordinary differential equations but are in early development for stochastic models. In this thesis, we first investigate using parameter estimation techniques for a deterministic model to approximate parameters in a corresponding stochastic model. The basis behind this approach lies in the Kurtz limit theorem which implies that for large populations, the realizations of the stochastic model converge to the deterministic model. We show for two example models that this approach often fails to estimate parameters well when the population size is small. We then develop a ...


Extended Followup Of A Cohort Of Chromium Production Workers, Herman Jones Gibb, Peter St. John Lees, Jing Wang, Keri O'Leary 2015 George Washington University

Extended Followup Of A Cohort Of Chromium Production Workers, Herman Jones Gibb, Peter St. John Lees, Jing Wang, Keri O'Leary

Epidemiology and Biostatistics Faculty Publications

No abstract provided.


Robin Chapman On (Her) Mathematics Education, Robin Chapman 2015 University of Wisconsin-Madison

Robin Chapman On (Her) Mathematics Education, Robin Chapman

Journal of Humanistic Mathematics

No abstract provided.


Computerizing Efficient Estimation Of A Pathwise Differentiable Target Parameter, Mark J. van der Laan, Marco Carone, Alexander R. Luedtke 2015 Division of Biostatistics, University of California, Berkeley

Computerizing Efficient Estimation Of A Pathwise Differentiable Target Parameter, Mark J. Van Der Laan, Marco Carone, Alexander R. Luedtke

U.C. Berkeley Division of Biostatistics Working Paper Series

Frangakis et al. (2015) proposed a numerical method for computing the efficient influence function of a parameter in a nonparametric model at a specified distribution and observation (provided such an influence function exists). Their approach is based on the assumption that the efficient influence function is given by the directional derivative of the target parameter mapping in the direction of a perturbation of the data distribution defined as the convex line from the data distribution to a pointmass at the observation. In our discussion paper Luedtke et al. (2015) we propose a regularization of this procedure and establish the validity ...


Hilbe-Pglr-Errata-And-Comments, Joseph M. Hilbe 2015 Arizona State University

Hilbe-Pglr-Errata-And-Comments, Joseph M. Hilbe

Joseph M Hilbe

Errata and Comments for Practical Guide to Logistic Regression


R Code For Practical Guide To Logistic Regression, Joseph M. Hilbe 2015 Arizona State University

R Code For Practical Guide To Logistic Regression, Joseph M. Hilbe

Joseph M Hilbe

R code for Practical Guide to Logistic Regression


Pglr-Stata Data Files, Joseph M. Hilbe 2015 Arizona State University

Pglr-Stata Data Files, Joseph M. Hilbe

Joseph M Hilbe

Stata data files for Practical Guide to Logistic Regression


Pglr-Sas Data, Joseph M. Hilbe 2015 Arizona State University

Pglr-Sas Data, Joseph M. Hilbe

Joseph M Hilbe

SAS data files for Practical Guide to Logistic Regression


Sas Code & Output For Practical Guide To Logistic Regression, Joseph M. Hilbe 2015 Arizona State University

Sas Code & Output For Practical Guide To Logistic Regression, Joseph M. Hilbe

Joseph M Hilbe

SAS code for Practical Guide to Logistic Regression


Sas Code Only For Practical Guide To Logistic Regression, Joseph M. Hilbe 2015 Arizona State University

Sas Code Only For Practical Guide To Logistic Regression, Joseph M. Hilbe

Joseph M Hilbe

SAS code-only for Practical Guide to Logistic Regression


Drawing Valid Targeted Inference When Covariate-Adjusted Response-Adaptive Rct Meets Data-Adaptive Loss-Based Estimation, With An Application To The Lasso, Wenjing Zheng, Antoine Chambaz, Mark J. van der Laan 2015 Division of Biostatistics, University of California, Berkeley, and Center for AIDS Prevention Studies, University of California, San Francisco

Drawing Valid Targeted Inference When Covariate-Adjusted Response-Adaptive Rct Meets Data-Adaptive Loss-Based Estimation, With An Application To The Lasso, Wenjing Zheng, Antoine Chambaz, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

Adaptive clinical trial design methods have garnered growing attention in the recent years, in large part due to their greater flexibility over their traditional counterparts. One such design is the so-called covariate-adjusted, response-adaptive (CARA) randomized controlled trial (RCT). In a CARA RCT, the treatment randomization schemes are allowed to depend on the patient’s pre-treatment covariates, and the investigators have the opportunity to adjust these schemes during the course of the trial based on accruing information (including previous responses), in order to meet a pre-specified optimality criterion, while preserving the validity of the trial in learning its primary study parameter ...


Negative Outcome Control For Unobserved Confounding Under A Cox Proportional Hazards Model, Eric J. Tchetgen Tchetgen, Tamar Sofer, David Richardson 2015 Harvard T.H. Chan School of Public Health

Negative Outcome Control For Unobserved Confounding Under A Cox Proportional Hazards Model, Eric J. Tchetgen Tchetgen, Tamar Sofer, David Richardson

Harvard University Biostatistics Working Paper Series

No abstract provided.


Review Of Developing Quantitative Literacy Skills In History And The Social Sciences: A Web-Based Common Core Approach By Kathleen W. Craver, Victor J. Ricchezza, H L. Vacher 2015 University of South Florida

Review Of Developing Quantitative Literacy Skills In History And The Social Sciences: A Web-Based Common Core Approach By Kathleen W. Craver, Victor J. Ricchezza, H L. Vacher

Numeracy

Kathleen W. Craver. Developing Quantitative Literacy Skills in History and Social Sciences: A Web-Based Common Core Standards Approach (Lantham MD: Rowman & Littlefield Publishing Group, Inc., 2014). 191 pp.
ISBN 978-1-4758-1050-9 (cloth); ISBN …-1051-6 (pbk); ISBN…-1052-3 (electronic).

This book could be a breakthrough for teachers in the trenches who are interested in or need to know about quantitative literacy (QL). It is a resource providing 85 topical pieces, averaging 1.5 pages, in which a featured Web site is presented, described, and accompanied by 2-4 critical-thinking questions purposefully drawing on data from the Web site. The featured Web sites range from primary documents (e.g., All about California and the ...


The Levels Of Conceptual Understanding In Statistics (Locus) Project: Results Of The Pilot Study, Douglas Whitaker, Steven Foti, Tim Jacobbe 2015 University of Florida

The Levels Of Conceptual Understanding In Statistics (Locus) Project: Results Of The Pilot Study, Douglas Whitaker, Steven Foti, Tim Jacobbe

Numeracy

The Levels of Conceptual Understanding in Statistics (LOCUS) project (NSF DRL-111868) has created assessments that measure conceptual (rather than procedural) understanding of statistics as outlined in GAISE Framework (Franklin et al., 2007, Guidelines for Assessment and Instruction in Statistics Education, American Statistical Association). Here we provide a brief overview of the LOCUS project and present results from multiple-choice items on the pilot administration of the assessments with data collected from over 3400 students in grades 6-12 across six states. These results help illustrate students’ understanding of statistical topics prior to the implementation of the Common Core State Standards. Using the ...


Accounting For Interactions And Complex Inter-Subject Dependency For Estimating Treatment Effect In Cluster Randomized Trials With Missing At Random Outcomes, Melanie Prague, Rui Wang, Alisa Stephens, Eric Tchetgen Tchetgen, Victor DeGruttola 2015 Harvard T.H. Chan School of Public Health

Accounting For Interactions And Complex Inter-Subject Dependency For Estimating Treatment Effect In Cluster Randomized Trials With Missing At Random Outcomes, Melanie Prague, Rui Wang, Alisa Stephens, Eric Tchetgen Tchetgen, Victor Degruttola

Harvard University Biostatistics Working Paper Series

No abstract provided.


Doubly Robust Estimation Of A Marginal Average Effect Of Treatment On The Treated With An Instrumental Variable, Lan Liu, Wang Miao, Baoluo Sun, James M. Robins, Eric J. Tchetgen Tchetgen 2015 Harvard University

Doubly Robust Estimation Of A Marginal Average Effect Of Treatment On The Treated With An Instrumental Variable, Lan Liu, Wang Miao, Baoluo Sun, James M. Robins, Eric J. Tchetgen Tchetgen

Harvard University Biostatistics Working Paper Series

No abstract provided.


Estimating Standard Errors For Importance Sampling Estimators With Multiple Markov Chains, Vivekananda Roy, Aixin Tan, James M. Flegal 2015 Iowa State University

Estimating Standard Errors For Importance Sampling Estimators With Multiple Markov Chains, Vivekananda Roy, Aixin Tan, James M. Flegal

Statistics Preprints

The naive importance sampling estimator based on the samples from a single importance density can be extremely numerically unstable. We consider multiple distributions importance sampling estimators where samples from more than one probability distributions are combined to consistently estimate means with respect to given target distributions. These generalized importance sampling estimators provide more stable estimators than the naive importance sampling estimators. Importance sampling estimators can also be used in the Markov chain Monte Carlo (MCMC) context, that is, where iid samples are replaced with positive Harris Markov chains with invariant importance distributions. If these Markov chains converge to their respective ...


One-Step Targeted Minimum Loss-Based Estimation Based On Universal Least Favorable One-Dimensional Submodels, Mark J. van der Laan 2015 University of California, Berkeley, Division of Biostatistics

One-Step Targeted Minimum Loss-Based Estimation Based On Universal Least Favorable One-Dimensional Submodels, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

Consider a study in which one observes n independent and identically distributed random variables whose probability distribution is known to be an element of a particular statistical model, and one is concerned with estimation of a particular real valued pathwise differentiable target parameter of this data probability distribution. The canonical gradient of the pathwise derivative of the target parameter, also called the efficient influence curve, defines an asymptotically efficient estimator as an estimator that is asymptotically linear with influence curve equal to the efficient influence curve.The targeted maximum likelihood estimator is a two stage estimator obtained by constructing a ...


Identification And Doubly Robust Estimation Of Data Missing Not At Random With An Ancillary Variable, Wang Miao, Eric Tchetgen Tchetgen, Zhi Geng 2015 Beijing University

Identification And Doubly Robust Estimation Of Data Missing Not At Random With An Ancillary Variable, Wang Miao, Eric Tchetgen Tchetgen, Zhi Geng

Harvard University Biostatistics Working Paper Series

No abstract provided.


Digital Commons powered by bepress