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  • IGB Berlin  (2)
  • Müncheberg ZALF  (2)
  • Kath. HS Sozialwesen
  • Mathematics  (4)
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  • 1
    Book
    Book
    Mixed models : theory and applications with R (2013)
    Hoboken, NJ : Wiley
    Details
    UID:
    gbv_750766506
    Format: XXVII, 717 S. , Ill., graph. Darst. , 25 cm
    Edition: 2. ed.
    ISBN: 1118091574 , 9781118091579
    Series Statement: Wiley series in probability and statistics
    Content: "Mixed modeling is one of the most promising and exciting areas of statistical analysis, enabling the analysis of nontraditional, clustered data that may come in the form of shapes or images. This book provides in-depth mathematical coverage of mixed models' statistical properties and numerical algorithms, as well as applications such as the analysis of tumor regrowth, shape, and image. The new edition includes significant updating, over 300 exercises, stimulating chapter projects and model simulations, inclusion of R subroutines, and a revised text format. The target audience continues to be graduate students and researchers. An author-maintained web site is available with solutions to exercises and a compendium of relevant data sets"--
    Note: Includes bibliographical references and index , In der mitgedruckten CiP-Aufnahme irrtümlich gezählt als Bd. 893 der Schriftenreihe , Machine generated contents note: Preface xviiPreface to the Second Edition xixR software and functions xxData Sets xxiiOpen Problems in Mixed Models xxiii1 Introduction: Why Mixed Models? 11.1 Mixed effects for clustered data 21.2 ANOVA, variance components, and the mixed model 41.3 Other special cases of the mixed effects model 61.4 A compromise between Bayesian and frequentist approaches 71.5 Penalized likelihood and mixed effects 91.6 Healthy Akaike information criterion 111.7 Penalized smoothing 131.8 Penalized polynomial fitting 161.9 Restraining parameters, or what to eat 181.10 Ill-posed problems, Tikhonov regularization, and mixed effects 201.11 Computerized tomography and linear image reconstruction 231.12 GLMM for PET 261.13 Maple shape leaf analysis 291.14 DNA Western blot analysis 311.15 Where does the wind blow? 331.16 Software and books361.17 Summary points 372 MLE for LME Model 412.1 Example: Weight versus height 422.2 The model and log-likelihood functions 452.3 Balanced random-coefficient model 602.4 LME model with random intercepts 642.5 Criterion for the MLE existence 722.6 Criterion for positive definiteness of matrix D742.7 Preestimation bounds for variance parameters 772.8 Maximization algorithms792.9 Derivatives of the log-likelihood function 812.10 Newton--Raphson algorithm 832.11 Fisher scoring algorithm852.12 EM algorithm 882.13 Starting point 932.14 Algorithms for restricted MLE 962.15 Optimization on nonnegative definite matrices 972.16 lmeFS and lme in R 1082.17 Appendix: Proof of the MLE existence 1122.18 Summary points 1153 Statistical Properties of the LME Model 1193.1 Introduction 1193.2 Identifiability of the LMEmodel 1193.3 Information matrix for variance parameters 1223.4 Profile-likelihood confidence intervals 1333.5 Statistical testing of the presence of random effects 1353.6 Statistical properties of MLE 1393.7 Estimation of random effects 1483.8 Hypothesis and membership testing 1533.9 Ignoring random effects 1573.10 MINQUE for variance parameters 1603.11 Method of moments 1693.12 Variance least squares estimator 1733.13 Projection on D+ space 1783.14 Comparison of the variance parameter estimation 1783.15 Asymptotically efficient estimation for [beta] 1823.16 Summary points 1834 Growth Curve Model and Generalizations 1874.1 Linear growth curve model 1874.2 General linear growth curve model 2034.3 Linear model with linear covariance structure 2214.4 Robust linear mixed effects model 2354.5 Appendix: Derivation of the MM estimator 2434.6 Summary points 2445 Meta-analysis Model 2475.1 Simple meta-analysis model 2485.2 Meta-analysis model with covariates 2755.3 Multivariate meta-analysis model 2805.4 Summary points 2916 Nonlinear Marginal Model 2936.1 Fixed matrix of random effects 2946.2 Varied matrix of random effects 3076.3 Three types of nonlinear marginal models 3186.4 Total generalized estimating equations approach 3236.5 Summary points 3307 Generalized Linear Mixed Models 3337.1 Regression models for binary data 3347.2 Binary model with subject-specific intercept 3577.3 Logistic regression with random intercept 3647.4 Probit model with random intercept 3847.5 Poisson model with random intercept 3887.6 Random intercept model: overview 4037.7 Mixed models with multiple random effects 4047.8 GLMM and simulation methods 4137.9 GEE for clustered marginal GLM 4187.10 Criteria for MLE existence for binary model 4267.11 Summary points 4318 Nonlinear Mixed Effects Model 4358.1 Introduction 4358.2 The model 4368.3 Example: Height of girls and boys 4398.4 Maximum likelihood estimation 4418.5 Two-stage estimator 4448.6 First-order approximation 4508.7 Lindstrom--Bates estimator 4528.8 Likelihood approximations 4578.9 One-parameter exponential model 4608.10 Asymptotic equivalence of the TS and LB estimators 4678.11 Bias-corrected two-stage estimator 4698.12 Distribution misspecification 4718.13 Partially nonlinear marginal mixed model 4748.14 Fixed sample likelihood approach4758.15 Estimation of random effects and hypothesis testing 4788.16 Example (continued) 4798.17 Practical recommendations 4818.18 Appendix: Proof of theorem on equivalence 4828.19 Summary points 4859 Diagnostics and Influence Analysis 4899.1 Introduction 4899.2 Influence analysis for linear regression 4909.3 The idea of infinitesimal influence 4939.4 Linear regression model 4959.5 Nonlinear regression model 5129.6 Logistic regression for binary outcome 5179.7 Influence of correlation structure 5269.8 Influence of measurement error 5279.9 Influence analysis for the LME model 5309.10 Appendix: MLE derivative with respect to σ2 5369.11 Summary points 53710 Tumor Regrowth Curves 54110.1 Survival curves 54310.2 Double--exponential regrowth curve 54510.3 Exponential growth with fixed regrowth time 55910.4 General regrowth curve 56510.5 Double--exponential transient regrowth curve 56610.6 Gompertz transient regrowth curve 57310.7 Summary points 57611 Statistical Analysis of Shape 57911.1 Introduction 57911.2 Statistical analysis of random triangles 58111.3 Face recognition 58411.4 Scale-irrelevant shape model 58511.5 Gorilla vertebrae analysis 58911.6 Procrustes estimation of the mean shape 59111.7 Fourier descriptor analysis 59811.8 Summary points 60712 Statistical Image Analysis 60912.1 Introduction 60912.2 Testing for uniform lighting 61212.3 Kolmogorov--Smirnov image comparison 61612.4 Multinomial statistical model for images 62012.5 Image entropy 62312.6 Ensemble of unstructured images 62712.7 Image alignment and registration 64012.8 Ensemble of structured images 65212.9 Modeling spatial correlation 65412.10 Summary points 66013 Appendix: Useful Facts and Formulas 66313.1 Basic facts of asymptotic theory 66313.2 Some formulas of matrix algebra 67013.3 Basic facts of optimization theory 674References 683Index 713.
    Additional Edition: ISBN 9781118593066
    Additional Edition: Online-Ausg. Demidenko, Eugene, 1948 - Mixed models Hoboken : Wiley, 2013 ISBN 9781118593066
    Additional Edition: Erscheint auch als Online-Ausgabe Mixed models Hoboken, New Jersey : John Wiley & Sons, Inc, 2013 ISBN 9781118651537
    Additional Edition: ISBN 1118651537
    Additional Edition: ISBN 9781118593066
    Additional Edition: ISBN 1118593065
    Language: English
    Subjects: Mathematics
    RVK:
    SK 840
    Keywords: Gemischtes Modell ; R
    URL: Cover
    URL: Inhaltstext
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  • 2
    Book
    Book
    The essential guide to effect sizes : statistical power, meta-analysis, and the interpretation of research results (2010)
    Cambridge : Cambridge University Press
    Details
    UID:
    gbv_1602700192
    Format: xvii, 173 Seiten , Diagramme , 25 cm
    ISBN: 0521142466 , 0521194237 , 9780521142465 , 9780521194235
    Content: "This succinct and jargon-free introduction to effect sizes gives students and researchers the tools they need to interpret the practical significance of their results. Using a class-tested approach that includes numerous examples and step-by-step exercises, it introduces and explains three of the most important issues relating to the practical significance of research results: the reporting and interpretation of effect sizes (Part I), the analysis of statistical power (Part II), and the meta-analytic pooling of effect size estimates drawn from different studies (Part III). The book concludes with a handy list of recommendations for those actively engaged in or currently preparing research projects"--
    Content: Introduction to effect sizes -- Interpreting effects -- Power analysis and the detection of effects -- The painful lessons of power research -- Drawing conclusions using meta-analysis -- Minimizing bias in meta-analysis
    Note: Literaturverzeichnis: Seiten 153-169 , Hier auch später erschienene, unveränderte Nachdrucke
    Additional Edition: Erscheint auch als Online-Ausgabe Ellis, Paul D., 1969 - The essential guide to effect sizes Cambridge : Cambridge University Press, 2010 ISBN 9780511761676
    Language: English
    Subjects: Economics , General works , Mathematics , Psychology , Sociology
    RVK:
    QH 235
    RVK:
    MR 2100
    RVK:
    AK 30300
    RVK:
    SK 850
    RVK:
    CM 3000
    RVK:
    CM 4000
    RVK:
    SK 830
    Keywords: Testtheorie ; Metaanalyse ; Forschung ; Datenerhebung ; Statistik
    URL: Inhaltsverzeichnis
    URL: Cover
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  • 3
    Book
    Book
    Mathematical ecology of populations and ecosystems (2008)
    Chichester [u.a.] : Wiley-Blackwell
    Details
    UID:
    b3kat_BV035354425
    Format: XIV, 329 S. , Ill., graph. Darst.
    Edition: 1. publ.
    ISBN: 9781405177955 , 1405177950 , 9781405188111 , 1405188111
    Content: "Population ecologists study how births and deaths affect the dynamics of populations and communities while ecosystem ecologists study how species control the flux of energy and materials through food webs and ecosystems. Although all these processes occur simultaneously in nature, the mathematical frameworks bridging the two disciplines have developed independently. Consequently, this independent development of theory has impeded the cross-fertilization of population and ecosystem ecology. Using recent developments from dynamical systems theory, this advanced undergraduate/graduate level textbook shows how to bridge the two disciplines seamlessly. This book shows how bifurcations between the solutions of models can help understand regime shifts in natural populations and ecosystems once thresholds in rates of births, deaths, consumption, competition, nutrient inputs, and decay are crossed. "Mathematical Ecology" is essential reading for students of ecology who have had a first course in calculus and linear algebra or students in mathematics wishing to learn how dynamical systems theory can be applied to ecological problems." --NHBS Bookstore.
    Note: Includes bibliographical references (p. 305-317) and index
    Language: English
    Subjects: Biology , Mathematics
    RVK:
    SK 950
    RVK:
    WI 1500
    RVK:
    WI 2050
    Keywords: Ökologie ; Mathematisches Modell ; Ökosystem ; Mathematisches Modell ; Populationsbiologie ; Mathematisches Modell
    URL: Inhaltsverzeichnis
    URL: Klappentext
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  • 4
    Book
    Book
    The R book (2013)
    Chichester : Wiley
    Details
    UID:
    gbv_1616281987
    Format: xxiv, 1051 Seiten , Diagramme , 25 cm
    Edition: Second edition
    ISBN: 9780470973929 , 0470973927
    Content: Hugely successful and popular text presenting an extensive and comprehensive guide for all R users The R language is recognized as one of the most powerful and flexible statistical software packages, enabling users to apply many statistical techniques that would be impossible without such software to help implement such large data sets. R has become an essential tool for understanding and carrying out research.This edition: Features full colour text and extensive graphics throughout. Introduces a clear structure with numbered section headings to help readers locate information more efficiently. Looks at the evolution of R over the past five years. Features a new chapter on Bayesian Analysis and Meta-Analysis. Presents a fully revised and updated bibliography and reference section. Is supported by an accompanying website allowing examples from the text to be run by the user. Praise for the first edition:'...if you are an R user or wannabe R user, this text is the one that should be on your shelf. The breadth of topics covered is unsurpassed when it comes to texts on data analysis in R.' (The American Statistician, August 2008)'The High-level software language of R is setting standards in quantitative analysis. And now anybody can get to grips with it thanks to The R Book ... (Professional Pensions, July 2007)
    Note: Literaturverz. S. [971] - 975 , Hier auch später erschienene, unveränderte Nachdrucke
    Additional Edition: ISBN 9781118448908
    Additional Edition: Erscheint auch als Online-Ausgabe Crawley, Michael J., 1949 - The R book Chichester : Wiley, 2013 ISBN 0470973927
    Additional Edition: ISBN 1118448928
    Additional Edition: ISBN 9781118448922
    Additional Edition: Erscheint auch als Online-Ausgabe Crawley, Michael J., 1949 - The R book Hoboken, N.J : Wiley, 2013 ISBN 9781118448946
    Additional Edition: ISBN 9781118448960
    Additional Edition: Erscheint auch als Online-Ausgabe Crawley, Michael J., 1949 - The R book Chichester, West Sussex, United Kingdom : Wiley, 2013 ISBN 9781118448908
    Additional Edition: ISBN 9781118448960
    Additional Edition: ISBN 1118448960
    Additional Edition: ISBN 9781118448946
    Additional Edition: ISBN 1118448944
    Additional Edition: ISBN 9781118448922
    Additional Edition: ISBN 1118448928
    Additional Edition: ISBN 1118448901
    Additional Edition: Erscheint auch als Online-Ausgabe Crawley, Michael J., 1949 - The R book Chichester : Wiley, 2013 ISBN 9780470973929
    Language: English
    Subjects: Computer Science , Economics , Biology , Mathematics
    RVK:
    ST 601
    RVK:
    SK 850
    RVK:
    QH 237
    RVK:
    WC 7000
    RVK:
    ST 250
    Keywords: Statistik ; R ; Zeitreihenanalyse ; Statistik ; R
    URL: Cover
    URL: Inhaltstext
    URL: Inhaltsverzeichnis
    URL: Inhaltstext
    URL: Cover
    Author information: Crawley, Michael J. 1949-
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