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Maximum Likelihood Estimation With Stata Fourth Edition


Maximum Likelihood Estimation With Stata Fourth Edition
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Maximum Likelihood Estimation With Stata


Maximum Likelihood Estimation With Stata
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Author : William Gould
language : en
Publisher:
Release Date : 2003

Maximum Likelihood Estimation With Stata written by William Gould and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Mathematics categories.




Maximum Likelihood Estimation With Stata


Maximum Likelihood Estimation With Stata
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Author : William Gould
language : en
Publisher:
Release Date : 2010

Maximum Likelihood Estimation With Stata written by William Gould and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Social sciences categories.


Maximum Likelihood Estimation with Stata, Fourth Edition is written for researchers in all disciplines who need to compute maximum likelihood estimators that are not available as prepackaged routines. Readers are presumed to be familiar with Stata, but no special programming skills are assumed except in the last few chapters, which detail how to add a new estimation command to Stata. The book begins with an introduction to the theory of maximum likelihood estimation with particular attention on the practical implications for applied work. Individual chapters then describe in detail each of the four types of likelihood evaluator programs and provide numerous examples, such as logit and probit regression, Weibull regression, random-effects linear regression, and the Cox proportional hazards model. Later chapters and appendixes provide additional details about the ml command, provide checklists to follow when writing evaluators, and show how to write your own estimation commands.



Maximum Likelihood Estimation With Stata Third Edition


Maximum Likelihood Estimation With Stata Third Edition
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Author : William Gould
language : en
Publisher: Stata Press
Release Date : 2006

Maximum Likelihood Estimation With Stata Third Edition written by William Gould and has been published by Stata Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Computers categories.


Written by the creators of Stata's likelihood maximization features, Maximum Likelihood Estimation with Stata, Third Edition continues the pioneering work of the previous editions. Emphasizing practical implications for applied work, the first chapter provides an overview of maximum likelihood estimation theory and numerical optimization methods. With step-by-step instructions, the next several chapters detail the use of Stata to maximize user-written likelihood functions. Various examples include logit, probit, linear, Weibull, and random-effects linear regression as well as the Cox proportional hazards model. The final chapters describe how to add a new estimation command to Stata. Assuming a familiarity with Stata, this reference is ideal for researchers who need to maximize their own likelihood functions. New ml commands and their functions: constraint: fits a model with linear constraints on the coefficient by defining your constraints; accepts a constraint matrix ml model: picks up survey characteristics; accepts the subpop option for analyzing survey data optimization algorithms: Berndt-Hall-Hall-Hausman (BHHH), Davidon-Fletcher-Powell (DFP), Broyden-Fletcher-Goldfarb-Shanno (BFGS) ml: switches between optimization algorithms; computes variance estimates using the outer product of gradients (OPG)



Maximum Likelihood Estimation With Stata Fourth Edition


Maximum Likelihood Estimation With Stata Fourth Edition
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Author : William Gould
language : en
Publisher: Stata Press
Release Date : 2010-10-27

Maximum Likelihood Estimation With Stata Fourth Edition written by William Gould and has been published by Stata Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-10-27 with Mathematics categories.


Maximum Likelihood Estimation with Stata, Fourth Edition is written for researchers in all disciplines who need to compute maximum likelihood estimators that are not available as prepackaged routines. Readers are presumed to be familiar with Stata, but no special programming skills are assumed except in the last few chapters, which detail how to add a new estimation command to Stata. The book begins with an introduction to the theory of maximum likelihood estimation with particular attention on the practical implications for applied work. Individual chapters then describe in detail each of the four types of likelihood evaluator programs and provide numerous examples, such as logit and probit regression, Weibull regression, random-effects linear regression, and the Cox proportional hazards model. Later chapters and appendixes provide additional details about the ml command, provide checklists to follow when writing evaluators, and show how to write your own estimation commands.



Handbook Of Statistical Analyses Using Stata


Handbook Of Statistical Analyses Using Stata
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Author : Brian S. Everitt
language : en
Publisher: CRC Press
Release Date : 2006-11-15

Handbook Of Statistical Analyses Using Stata written by Brian S. Everitt and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-11-15 with Mathematics categories.


With each new release of Stata, a comprehensive resource is needed to highlight the improvements as well as discuss the fundamentals of the software. Fulfilling this need, AHandbook of Statistical Analyses Using Stata, Fourth Edition has been fully updated to provide an introduction to Stata version 9. This edition covers many



An Introduction To Medical Statistics


An Introduction To Medical Statistics
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Author : Martin Bland
language : en
Publisher: Oxford University Press
Release Date : 2015-07-23

An Introduction To Medical Statistics written by Martin Bland and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07-23 with Medical categories.


Now in its Fourth Edition, An Introduction to Medical Statistics continues to be a 'must-have' textbook for anyone who needs a clear logical guide to the subject. Written in an easy-to-understand style and packed with real life examples, the text clearly explains the statistical principles used in the medical literature. Taking readers through the common statistical methods seen in published research and guidelines, the text focuses on how to interpret and analyse statistics for clinical practice. Using extracts from real studies, the author illustrates how data can be employed correctly and incorrectly in medical research helping readers to evaluate the statistics they encounter and appropriately implement findings in clinical practice. End of chapter exercises, case studies and multiple choice questions help readers to apply their learning and develop their own interpretative skills. This thoroughly revised edition includes new chapters on meta-analysis, missing data, and survival analysis.



Generalized Linear Models And Extensions Second Edition


Generalized Linear Models And Extensions Second Edition
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Author : James W. Hardin
language : en
Publisher: Stata Press
Release Date : 2007

Generalized Linear Models And Extensions Second Edition written by James W. Hardin and has been published by Stata Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Computers categories.


Deftly balancing theory and application, this book stands out in its coverage of the derivation of the GLM families and their foremost links. This edition has new sections on discrete response models, including zero-truncated, zero-inflated, censored, and hurdle count models, as well as heterogeneous negative binomial, and more.



Handbook Of Statistical Analyses Using Stata Fourth Edition


Handbook Of Statistical Analyses Using Stata Fourth Edition
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Author : Brian S. Everitt
language : en
Publisher: CRC Press
Release Date : 2006-11-15

Handbook Of Statistical Analyses Using Stata Fourth Edition written by Brian S. Everitt and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-11-15 with Mathematics categories.


With each new release of Stata, a comprehensive resource is needed to highlight the improvements as well as discuss the fundamentals of the software. Fulfilling this need, A Handbook of Statistical Analyses Using Stata, Fourth Edition has been fully updated to provide an introduction to Stata version 9. This edition covers many new features of Stata, including a new command for mixed models and a new matrix language. Each chapter describes the analysis appropriate for a particular application, focusing on the medical, social, and behavioral fields. The authors begin each chapter with descriptions of the data and the statistical techniques to be used. The methods covered include descriptives, simple tests, variance analysis, multiple linear regression, logistic regression, generalized linear models, survival analysis, random effects models, and cluster analysis. The core of the book centers on how to use Stata to perform analyses and how to interpret the results. The chapters conclude with several exercises based on data sets from different disciplines. A concise guide to the latest version of Stata, A Handbook of Statistical Analyses Using Stata, Fourth Edition illustrates the benefits of using Stata to perform various statistical analyses for both data analysis courses and self-study.



Modeling Ordered Choices


Modeling Ordered Choices
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Author : William H. Greene
language : en
Publisher: Cambridge University Press
Release Date : 2010-04-08

Modeling Ordered Choices written by William H. Greene and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-04-08 with Business & Economics categories.


It is increasingly common for analysts to seek out the opinions of individuals and organizations using attitudinal scales such as degree of satisfaction or importance attached to an issue. Examples include levels of obesity, seriousness of a health condition, attitudes towards service levels, opinions on products, voting intentions, and the degree of clarity of contracts. Ordered choice models provide a relevant methodology for capturing the sources of influence that explain the choice made amongst a set of ordered alternatives. The methods have evolved to a level of sophistication that can allow for heterogeneity in the threshold parameters, in the explanatory variables (through random parameters), and in the decomposition of the residual variance. This book brings together contributions in ordered choice modeling from a number of disciplines, synthesizing developments over the last fifty years, and suggests useful extensions to account for the wide range of sources of influence on choice.



An Introduction To Modern Econometrics Using Stata


An Introduction To Modern Econometrics Using Stata
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Author : Christopher F. Baum
language : en
Publisher: Stata Press
Release Date : 2006-08-17

An Introduction To Modern Econometrics Using Stata written by Christopher F. Baum and has been published by Stata Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-08-17 with Business & Economics categories.


Integrating a contemporary approach to econometrics with the powerful computational tools offered by Stata, this introduction illustrates how to apply econometric theories used in modern empirical research using Stata. The author emphasizes the role of method-of-moments estimators, hypothesis testing, and specification analysis and provides practical examples that show how to apply the theories to real data sets. The book first builds familiarity with the basic skills needed to work with econometric data in Stata before delving into the core topics, which range from the multiple linear regression model to instrumental-variables estimation.