Multiple And Generalized Nonparametric Regression
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Nonparametric Regression And Generalized Linear Models
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Author : P.J. Green
language : en
Publisher: CRC Press
Release Date : 1993-05-01
Nonparametric Regression And Generalized Linear Models written by P.J. Green and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993-05-01 with Mathematics categories.
Nonparametric Regression and Generalized Linear Models focuses on the roughness penalty method of nonparametric smoothing and shows how this technique provides a unifying approach to a wide range of smoothing problems. The emphasis is methodological rather than theoretical, and the authors concentrate on statistical and computation issues. Real data examples are used to illustrate the various methods and to compare them with standard parametric approaches. The mathematical treatment is self-contained and depends mainly on simple linear algebra and calculus. This monograph will be useful both as a reference work for research and applied statisticians and as a text for graduate students.
Multiple And Generalized Nonparametric Regression
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Author : John Fox
language : en
Publisher: SAGE Publications
Release Date : 2000-05-01
Multiple And Generalized Nonparametric Regression written by John Fox and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-05-01 with Social Science categories.
This book builds on John Fox′s previous volume in the QASS Series, Non Parametric Simple Regression. In this monograph readers learn to estimate and plot smooth functions when there are multiple independent variables. While regression analysis traces the dependence of the distribution of a response variable to see if it bears a particular (linear) relationship to one or more of the predictors, nonparametric regression analysis makes minimal assumptions about the form of relationship between the average response and the predictors. This makes nonparametric regression a more useful technique for analyzing data in which there are several predictors that may combine additively to influence the response. (An example could be something like birth order/gender/and temperament on achievement motivation). Unfortunately, researchers have not had accessible information on nonparametric regression analysis, until now. Beginning with presentation of nonparametric regression based on dividing the data into bins and averaging the response values in each bin, Fox introduces readers to the techniques of kernel estimation, additive nonparametric regression, and the ways nonparametric regression can be employed to select transformations of the data preceding a linear least-squares fit. The book concludes with ways nonparametric regression can be generalized to logit, probit, and Poisson regression.
Nonparametric And Semiparametric Models
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Author : Wolfgang Karl Härdle
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-08-27
Nonparametric And Semiparametric Models written by Wolfgang Karl Härdle 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 2012-08-27 with Mathematics categories.
The statistical and mathematical principles of smoothing with a focus on applicable techniques are presented in this book. It naturally splits into two parts: The first part is intended for undergraduate students majoring in mathematics, statistics, econometrics or biometrics whereas the second part is intended to be used by master and PhD students or researchers. The material is easy to accomplish since the e-book character of the text gives a maximum of flexibility in learning (and teaching) intensity.
Lisrel Approaches To Interaction Effects In Multiple Regression
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Author : James Jaccard
language : en
Publisher: SAGE
Release Date : 1996-03-21
Lisrel Approaches To Interaction Effects In Multiple Regression written by James Jaccard and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996-03-21 with Mathematics categories.
With detailed examples, this book demonstrates the use of the computer program LISREL and how it can be applied to the analysis of interactions in regression frameworks. The authors consider a wide range of applications including: qualitative moderator variables; longitudinal designs; and product term analysis. They describe different types of measurement error and then present a discussion of latent variable representations of measurement error which serves as the foundation for the analyses described in later chapters. Finally they offer a brief introduction to LISREL and show how it can be used to execute the analyses. Readers can use this book without any prior training in LISREL and will find it an excellent introduction to analytic methods that deal with the problem of measurement error in the analysis of interactions.
Linear Models With R Second Edition
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Author : Julian J. Faraway
language : en
Publisher: CRC Press
Release Date : 2014-07-01
Linear Models With R Second Edition written by Julian J. Faraway and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-01 with Mathematics categories.
A Hands-On Way to Learning Data Analysis Part of the core of statistics, linear models are used to make predictions and explain the relationship between the response and the predictors. Understanding linear models is crucial to a broader competence in the practice of statistics. Linear Models with R, Second Edition explains how to use linear models in physical science, engineering, social science, and business applications. The book incorporates several improvements that reflect how the world of R has greatly expanded since the publication of the first edition. New to the Second Edition Reorganized material on interpreting linear models, which distinguishes the main applications of prediction and explanation and introduces elementary notions of causality Additional topics, including QR decomposition, splines, additive models, Lasso, multiple imputation, and false discovery rates Extensive use of the ggplot2 graphics package in addition to base graphics Like its widely praised, best-selling predecessor, this edition combines statistics and R to seamlessly give a coherent exposition of the practice of linear modeling. The text offers up-to-date insight on essential data analysis topics, from estimation, inference, and prediction to missing data, factorial models, and block designs. Numerous examples illustrate how to apply the different methods using R.
Modern Statistics For The Social And Behavioral Sciences
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Author : Rand Wilcox
language : en
Publisher: CRC Press
Release Date : 2011-08-05
Modern Statistics For The Social And Behavioral Sciences written by Rand Wilcox and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-08-05 with Mathematics categories.
In addition to learning how to apply classic statistical methods, students need to understand when these methods perform well, and when and why they can be highly unsatisfactory. Modern Statistics for the Social and Behavioral Sciences illustrates how to use R to apply both standard and modern methods to correct known problems with classic techniques. Numerous illustrations provide a conceptual basis for understanding why practical problems with classic methods were missed for so many years, and why modern techniques have practical value. Designed for a two-semester, introductory course for graduate students in the social sciences, this text introduces three major advances in the field: Early studies seemed to suggest that normality can be assumed with relatively small sample sizes due to the central limit theorem. However, crucial issues were missed. Vastly improved methods are now available for dealing with non-normality. The impact of outliers and heavy-tailed distributions on power and our ability to obtain an accurate assessment of how groups differ and variables are related is a practical concern when using standard techniques, regardless of how large the sample size might be. Methods for dealing with this insight are described. The deleterious effects of heteroscedasticity on conventional ANOVA and regression methods are much more serious than once thought. Effective techniques for dealing heteroscedasticity are described and illustrated. Requiring no prior training in statistics, Modern Statistics for the Social and Behavioral Sciences provides a graduate-level introduction to basic, routinely used statistical techniques relevant to the social and behavioral sciences. It describes and illustrates methods developed during the last half century that deal with known problems associated with classic techniques. Espousing the view that no single method is always best, it imparts a general understanding of the relative merits of various techniques so that the choice of method can be made in an informed manner.
The Reviewer S Guide To Quantitative Methods In The Social Sciences
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Author : Gregory R. Hancock
language : en
Publisher: Routledge
Release Date : 2018-11-15
The Reviewer S Guide To Quantitative Methods In The Social Sciences written by Gregory R. Hancock and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-15 with Education categories.
The Reviewer’s Guide to Quantitative Methods in the Social Sciences provides evaluators of research manuscripts and proposals in the social and behavioral sciences with the resources they need to read, understand, and assess quantitative work. 35 uniquely structured chapters cover both traditional and emerging methods of quantitative data analysis, which neither junior nor veteran reviewers can be expected to know in detail. The second edition of this valuable resource updates readers on each technique’s key principles, appropriate usage, underlying assumptions and limitations, providing reviewers with the information they need to offer constructive commentary on works they evaluate. Written by methodological and applied scholars, this volume is also an indispensable author’s reference for preparing sound research manuscripts and proposals.
Polytomous Item Response Theory Models
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Author : Remo Ostini
language : en
Publisher: SAGE
Release Date : 2006
Polytomous Item Response Theory Models written by Remo Ostini and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Psychology categories.
This volume provides an introduction to the range of polytomous models available within item response theory. It begins by outlining the distinction between the two major types of polytomous IRT models, then goes on to describe them in detail.
Randomized Response And Related Methods
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Author : James Alan Fox
language : en
Publisher: SAGE Publications
Release Date : 2015-07-29
Randomized Response And Related Methods written by James Alan Fox and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07-29 with Social Science categories.
Randomized response is a data collection strategy specifically designed for surveys of a sensitive nature. By establishing a probabilistic connection between question and answer, randomized response and related methods protect respondents who are asked to disclose personal information. Covering a half century of theoretical and applied research, the Second Edition significantly updates and expands what was, at the time, the first comprehensive and practical guide to randomized response.
Analyzing Complex Survey Data
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Author : Eun Sul Lee
language : en
Publisher: SAGE
Release Date : 2006
Analyzing Complex Survey Data written by Eun Sul Lee and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Mathematics categories.
In this introduction to the different ways of analysing complex survey data, the authors consider new analytical approaches, review new software and introduce a model-based analysis that can be used for well-designed and relatively small-scale social surveys.