Maximum Likelihood For Social Science
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Maximum Likelihood For Social Science
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Author : Michael D. Ward
language : en
Publisher: Cambridge University Press
Release Date : 2018-11-22
Maximum Likelihood For Social Science written by Michael D. Ward 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 2018-11-22 with Political Science categories.
Practical, example-driven introduction to maximum likelihood for the social sciences. Emphasizes computation in R, model selection and interpretation.
Large Sample Properties Of Maximum Likelihood Estimators
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Author : Nicholas Herbert Stern
language : en
Publisher:
Release Date : 1980
Large Sample Properties Of Maximum Likelihood Estimators written by Nicholas Herbert Stern and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1980 with Mathematical statistics categories.
Statistics In The Social Sciences
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Author : Stanislav Kolenikov
language : en
Publisher: John Wiley & Sons
Release Date : 2010-02-22
Statistics In The Social Sciences written by Stanislav Kolenikov and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-02-22 with Mathematics categories.
A one-of-a-kind compilation of modern statistical methods designed to support and advance research across the social sciences Statistics in the Social Sciences: Current Methodological Developments presents new and exciting statistical methodologies to help advance research and data analysis across the many disciplines in the social sciences. Quantitative methods in various subfields, from psychology to economics, are under demand for constant development and refinement. This volume features invited overview papers, as well as original research presented at the Sixth Annual Winemiller Conference: Methodological Developments of Statistics in the Social Sciences, an international meeting that focused on fostering collaboration among mathematical statisticians and social science researchers. The book provides an accessible and insightful look at modern approaches to identifying and describing current, effective methodologies that ultimately add value to various fields of social science research. With contributions from leading international experts on the topic, the book features in-depth coverage of modern quantitative social sciences topics, including: Correlation Structures Structural Equation Models and Recent Extensions Order-Constrained Proximity Matrix Representations Multi-objective and Multi-dimensional Scaling Differences in Bayesian and Non-Bayesian Inference Bootstrap Test of Shape Invariance across Distributions Statistical Software for the Social Sciences Statistics in the Social Sciences: Current Methodological Developments is an excellent supplement for graduate courses on social science statistics in both statistics departments and quantitative social sciences programs. It is also a valuable reference for researchers and practitioners in the fields of psychology, sociology, economics, and market research.
Maximum Likelihood Estimates Of Alternative Relations
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Author : A. R. G. Heesterman
language : en
Publisher:
Release Date : 1973
Maximum Likelihood Estimates Of Alternative Relations written by A. R. G. Heesterman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1973 with categories.
The Evaluation Of Exact Maximum Likelihood Estimates For Varma Models
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Author : A. D. Hall
language : en
Publisher:
Release Date : 1979
The Evaluation Of Exact Maximum Likelihood Estimates For Varma Models written by A. D. Hall and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1979 with categories.
Handbook Of Statistical Modeling For The Social And Behavioral Sciences
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Author : G. Arminger
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-06-29
Handbook Of Statistical Modeling For The Social And Behavioral Sciences written by G. Arminger and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-29 with Psychology categories.
Contributors thoroughly survey the most important statistical models used in empirical reserch in the social and behavioral sciences. Following a common format, each chapter introduces a model, illustrates the types of problems and data for which the model is best used, provides numerous examples that draw upon familiar models or procedures, and includes material on software that can be used to estimate the models studied. This handbook will aid researchers, methodologists, graduate students, and statisticians to understand and resolve common modeling problems.
The Sage Encyclopedia Of Social Science Research Methods
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Author : Michael Lewis-Beck
language : en
Publisher: SAGE
Release Date : 2004
The Sage Encyclopedia Of Social Science Research Methods written by Michael Lewis-Beck and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Reference categories.
Featuring over 900 entries, this resource covers all disciplines within the social sciences with both concise definitions & in-depth essays.
Maximum Likelihood Estimation For Sample Surveys
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Author : Raymond L. Chambers
language : en
Publisher: CRC Press
Release Date : 2012-05-02
Maximum Likelihood Estimation For Sample Surveys written by Raymond L. Chambers and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-05-02 with Mathematics categories.
Sample surveys provide data used by researchers in a large range of disciplines to analyze important relationships using well-established and widely used likelihood methods. The methods used to select samples often result in the sample differing in important ways from the target population and standard application of likelihood methods can lead to biased and inefficient estimates. Maximum Likelihood Estimation for Sample Surveys presents an overview of likelihood methods for the analysis of sample survey data that account for the selection methods used, and includes all necessary background material on likelihood inference. It covers a range of data types, including multilevel data, and is illustrated by many worked examples using tractable and widely used models. It also discusses more advanced topics, such as combining data, non-response, and informative sampling. The book presents and develops a likelihood approach for fitting models to sample survey data. It explores and explains how the approach works in tractable though widely used models for which we can make considerable analytic progress. For less tractable models numerical methods are ultimately needed to compute the score and information functions and to compute the maximum likelihood estimates of the model parameters. For these models, the book shows what has to be done conceptually to develop analyses to the point that numerical methods can be applied. Designed for statisticians who are interested in the general theory of statistics, Maximum Likelihood Estimation for Sample Surveys is also aimed at statisticians focused on fitting models to sample survey data, as well as researchers who study relationships among variables and whose sources of data include surveys.
Numerical Issues In Statistical Computing For The Social Scientist
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Author : Micah Altman
language : en
Publisher: John Wiley & Sons
Release Date : 2004-02-15
Numerical Issues In Statistical Computing For The Social Scientist written by Micah Altman and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-02-15 with Mathematics categories.
At last—a social scientist's guide through the pitfalls ofmodern statistical computing Addressing the current deficiency in the literature onstatistical methods as they apply to the social and behavioralsciences, Numerical Issues in Statistical Computing for the SocialScientist seeks to provide readers with a unique practicalguidebook to the numerical methods underlying computerizedstatistical calculations specific to these fields. The authorsdemonstrate that knowledge of these numerical methods and how theyare used in statistical packages is essential for making accurateinferences. With the aid of key contributors from both the socialand behavioral sciences, the authors have assembled a rich set ofinterrelated chapters designed to guide empirical social scientiststhrough the potential minefield of modern statisticalcomputing. Uniquely accessible and abounding in modern-day tools, tricks,and advice, the text successfully bridges the gap between thecurrent level of social science methodology and the moresophisticated technical coverage usually associated with thestatistical field. Highlights include: A focus on problems occurring in maximum likelihoodestimation Integrated examples of statistical computing (using softwarepackages such as the SAS, Gauss, Splus, R, Stata, LIMDEP, SPSS,WinBUGS, and MATLAB®) A guide to choosing accurate statistical packages Discussions of a multitude of computationally intensivestatistical approaches such as ecological inference, Markov chainMonte Carlo, and spatial regression analysis Emphasis on specific numerical problems, statisticalprocedures, and their applications in the field Replications and re-analysis of published social scienceresearch, using innovative numerical methods Key numerical estimation issues along with the means ofavoiding common pitfalls A related Web site includes test data for use in demonstratingnumerical problems, code for applying the original methodsdescribed in the book, and an online bibliography of Web resourcesfor the statistical computation Designed as an independent research tool, a professionalreference, or a classroom supplement, the book presents awell-thought-out treatment of a complex and multifaceted field.
The Sage Handbook Of Quantitative Methodology For The Social Sciences
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Author : David Kaplan
language : en
Publisher: SAGE Publications
Release Date : 2004-06-21
The Sage Handbook Of Quantitative Methodology For The Social Sciences written by David Kaplan and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-06-21 with Social Science categories.
The SAGE Handbook of Quantitative Methodology for the Social Sciences is the definitive reference for teachers, students, and researchers of quantitative methods in the social sciences, as it provides a comprehensive overview of the major techniques used in the field. The contributors, top methodologists and researchers, have written about their areas of expertise in ways that convey the utility of their respective techniques, but, where appropriate, they also offer a fair critique of these techniques. Relevance to real-world problems in the social sciences is an essential ingredient of each chapter and makes this an invaluable resource.