Estimation of Odds Ratio in 2 X 2 Contingency Tables with Small Cell Counts PDF Download
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Author: Guohao Zhu
Publisher:
ISBN:
Category : Contingency tables
Languages : en
Pages : 0
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Book Description
This study is focusing on properties of estimators of odds ratio or its logarithm in case of 2x2 tables with small counts. The odds ratio represents the odds that an outcome of interest will occur given a particular exposure, compared to the odds of the outcome occurring in the absence of that exposure. Both parameters are often used to quantify the strength of association of two binary variables and are common measurements reported in case-control, cohort, and cross-sectional studies. Because of their wide applicability, both parameters, odds ratio, and its logarithm, have been intensively studied in the literature. However, most of their desirable properties are based on the asymptotic normality of the estimators which are not necessarily true in case of small sample sizes. In addition, contingency tables with small counts often contain cells with counts that equal zero which makes maximum likelihood estimators of odds ratio and its logarithm undefined. While in many research areas it is possible to collect data of the size needed, there are areas, such as health related multi-center research, where sample size cannot be increased. We are studying performance of estimators of odds ratio, and its logarithm, for independent 2x2 tables with small counts. Among other applications, our conclusions could also serve as recommendations for comparison of odds ratios in multiple 2x2 tables--a step necessary before performing meta-analysis.
Author: Guohao Zhu
Publisher:
ISBN:
Category : Contingency tables
Languages : en
Pages : 0
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Book Description
This study is focusing on properties of estimators of odds ratio or its logarithm in case of 2x2 tables with small counts. The odds ratio represents the odds that an outcome of interest will occur given a particular exposure, compared to the odds of the outcome occurring in the absence of that exposure. Both parameters are often used to quantify the strength of association of two binary variables and are common measurements reported in case-control, cohort, and cross-sectional studies. Because of their wide applicability, both parameters, odds ratio, and its logarithm, have been intensively studied in the literature. However, most of their desirable properties are based on the asymptotic normality of the estimators which are not necessarily true in case of small sample sizes. In addition, contingency tables with small counts often contain cells with counts that equal zero which makes maximum likelihood estimators of odds ratio and its logarithm undefined. While in many research areas it is possible to collect data of the size needed, there are areas, such as health related multi-center research, where sample size cannot be increased. We are studying performance of estimators of odds ratio, and its logarithm, for independent 2x2 tables with small counts. Among other applications, our conclusions could also serve as recommendations for comparison of odds ratios in multiple 2x2 tables--a step necessary before performing meta-analysis.
Author: Tamás Rudas
Publisher: SAGE
ISBN: 9780761903628
Category : Mathematics
Languages : en
Pages : 92
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Book Description
In this volume the author shows how odds ratios can be used as a framework for understanding log-linear models. The book moves from paradigmatic 2x2 case to more complicated cases. The author also carefully defines the odds ratio.
Author: Marit L. Bovbjerg
Publisher:
ISBN: 9781955101035
Category : Health & Fitness
Languages : en
Pages : 176
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Book Description
Foundations of Epidemiology is an open access, introductory epidemiology text intended for students and practitioners in public or allied health fields. It covers epidemiologic thinking, causality, incidence and prevalence, public health surveillance, epidemiologic study designs and why we care about which one is used, measures of association, random error and bias, confounding and effect modification, and screening. Concepts are illustrated with numerous examples drawn from contemporary and historical public health issues.
Author: Alan Agresti
Publisher: John Wiley & Sons
ISBN: 1119405270
Category : Mathematics
Languages : en
Pages : 400
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Book Description
A valuable new edition of a standard reference The use of statistical methods for categorical data has increased dramatically, particularly for applications in the biomedical and social sciences. An Introduction to Categorical Data Analysis, Third Edition summarizes these methods and shows readers how to use them using software. Readers will find a unified generalized linear models approach that connects logistic regression and loglinear models for discrete data with normal regression for continuous data. Adding to the value in the new edition is: • Illustrations of the use of R software to perform all the analyses in the book • A new chapter on alternative methods for categorical data, including smoothing and regularization methods (such as the lasso), classification methods such as linear discriminant analysis and classification trees, and cluster analysis • New sections in many chapters introducing the Bayesian approach for the methods of that chapter • More than 70 analyses of data sets to illustrate application of the methods, and about 200 exercises, many containing other data sets • An appendix showing how to use SAS, Stata, and SPSS, and an appendix with short solutions to most odd-numbered exercises Written in an applied, nontechnical style, this book illustrates the methods using a wide variety of real data, including medical clinical trials, environmental questions, drug use by teenagers, horseshoe crab mating, basketball shooting, correlates of happiness, and much more. An Introduction to Categorical Data Analysis, Third Edition is an invaluable tool for statisticians and biostatisticians as well as methodologists in the social and behavioral sciences, medicine and public health, marketing, education, and the biological and agricultural sciences.
Author: Morten Fagerland
Publisher: CRC Press
ISBN: 1466588187
Category : Mathematics
Languages : en
Pages : 657
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Book Description
Statistical Analysis of Contingency Tables is an invaluable tool for statistical inference in contingency tables. It covers effect size estimation, confidence intervals, and hypothesis tests for the binomial and the multinomial distributions, unpaired and paired 2x2 tables, rxc tables, ordered rx2 and 2xc tables, paired cxc tables, and stratified tables. For each type of table, key concepts are introduced, and a wide range of intervals and tests, including recent and unpublished methods and developments, are presented and evaluated. Topics such as diagnostic accuracy, inter-rater reliability, and missing data are also covered. The presentation is concise and easily accessible for readers with diverse professional backgrounds, with the mathematical details kept to a minimum. For more information, including a sample chapter and software, please visit the authors' website.
Author: Adelin Albert
Publisher: CRC Press
ISBN: 9780824777357
Category : Mathematics
Languages : en
Pages : 332
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Book Description
This first of its kind guide describes statistical methods for the effective and efficient analysis of multivariate laboratory data, providing coverage which goes well beyond the standard single-sample diagnostic tools that regularly appear in medical literature.
Author: Nicholas P. Jewell
Publisher: CRC Press
ISBN: 0203496868
Category : Medical
Languages : en
Pages : 376
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Book Description
Statistical ideas have been integral to the development of epidemiology and continue to provide the tools needed to interpret epidemiological studies. Although epidemiologists do not need a highly mathematical background in statistical theory to conduct and interpret such studies, they do need more than an encyclopedia of "recipes." Statistics for Epidemiology achieves just the right balance between the two approaches, building an intuitive understanding of the methods most important to practitioners and the skills to use them effectively. It develops the techniques for analyzing simple risk factors and disease data, with step-by-step extensions that include the use of binary regression. It covers the logistic regression model in detail and contrasts it with the Cox model for time-to-incidence data. The author uses a few simple case studies to guide readers from elementary analyses to more complex regression modeling. Following these examples through several chapters makes it easy to compare the interpretations that emerge from varying approaches. Written by one of the top biostatisticians in the field, Statistics for Epidemiology stands apart in its focus on interpretation and in the depth of understanding it provides. It lays the groundwork that all public health professionals, epidemiologists, and biostatisticians need to successfully design, conduct, and analyze epidemiological studies.
Author: Jeff Sauro
Publisher: Morgan Kaufmann
ISBN: 0128025484
Category : Computers
Languages : en
Pages : 374
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Book Description
Quantifying the User Experience: Practical Statistics for User Research, Second Edition, provides practitioners and researchers with the information they need to confidently quantify, qualify, and justify their data. The book presents a practical guide on how to use statistics to solve common quantitative problems that arise in user research. It addresses questions users face every day, including, Is the current product more usable than our competition? Can we be sure at least 70% of users can complete the task on their first attempt? How long will it take users to purchase products on the website? This book provides a foundation for statistical theories and the best practices needed to apply them. The authors draw on decades of statistical literature from human factors, industrial engineering, and psychology, as well as their own published research, providing both concrete solutions (Excel formulas and links to their own web-calculators), along with an engaging discussion on the statistical reasons why tests work and how to effectively communicate results. Throughout this new edition, users will find updates on standardized usability questionnaires, a new chapter on general linear modeling (correlation, regression, and analysis of variance), with updated examples and case studies throughout. Completely updated to provide practical guidance on solving usability testing problems with statistics for any project, including those using Six Sigma practices Includes new and revised information on standardized usability questionnaires Includes a completely new chapter introducing correlation, regression, and analysis of variance Shows practitioners which test to use, why they work, and best practices for application, along with easy-to-use Excel formulas and web-calculators for analyzing data Recommends ways for researchers and practitioners to communicate results to stakeholders in plain English
Author: A J. Lee
Publisher: Routledge
ISBN: 1351405853
Category : Mathematics
Languages : en
Pages : 324
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Book Description
In 1946 Paul Halmos studied unbiased estimators of minimum variance, and planted the seed from which the subject matter of the present monograph sprang. The author has undertaken to provide experts and advanced students with a review of the present status of the evolved theory of U-statistics, including applications to indicate the range and scope of U-statistic methods. Complete with over 200 end-of-chapter references, this is an invaluable addition to the libraries of applied and theoretical statisticians and mathematicians.
Author: Maria Kateri
Publisher: Springer
ISBN: 0817648119
Category : Mathematics
Languages : en
Pages : 315
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Book Description
Contingency tables arise in diverse fields, including life sciences, education, social and political sciences, notably market research and opinion surveys. Their analysis plays an essential role in gaining insight into structures of the quantities under consideration and in supporting decision making. Combining both theory and applications, this book presents models and methods for the analysis of two- and multidimensional-contingency tables. An excellent reference for advanced undergraduates, graduate students, and practitioners in statistics as well as biosciences, social sciences, education, and economics, the work may also be used as a textbook for a course on categorical data analysis. Prerequisites include basic background on statistical inference and knowledge of statistical software packages.
