Covariate-dependent Confidence Intervals for Percentiles PDF Download

Author: Arja Virtanen
Publisher:
ISBN:
Category :
Languages : en
Pages : 126

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Author: Douglas Altman
Publisher: John Wiley & Sons
ISBN: 1118702506
Category : Medical
Languages : en
Pages : 322

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This highly popular introduction to confidence intervals has been thoroughly updated and expanded. It includes methods for using confidence intervals, with illustrative worked examples and extensive guidelines and checklists to help the novice.

Author: Wolfgang Wiedermann
Publisher: John Wiley & Sons
ISBN: 1119523141
Category : Mathematics
Languages : en
Pages : 432

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Covers the latest developments in direction dependence research Direction Dependence in Statistical Modeling: Methods of Analysis incorporates the latest research for the statistical analysis of hypotheses that are compatible with the causal direction of dependence of variable relations. Having particular application in the fields of neuroscience, clinical psychology, developmental psychology, educational psychology, and epidemiology, direction dependence methods have attracted growing attention due to their potential to help decide which of two competing statistical models is more likely to reflect the correct causal flow. The book covers several topics in-depth, including: A demonstration of the importance of methods for the analysis of direction dependence hypotheses A presentation of the development of methods for direction dependence analysis together with recent novel, unpublished software implementations A review of methods of direction dependence following the copula-based tradition of Sungur and Kim A presentation of extensions of direction dependence methods to the domain of categorical data An overview of algorithms for causal structure learning The book's fourteen chapters include a discussion of the use of custom dialogs and macros in SPSS to make direction dependence analysis accessible to empirical researchers.

Author: DodsoN/NolaN
Publisher: CRC Press
ISBN: 9780824703646
Category : Technology & Engineering
Languages : en
Pages : 612

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Providing a comprehensive approach to both the art and science of reliability engineering, this volume covers all aspects of the field, from basic concepts to accelerated testing, including SPC, designed experiments, human factors, and reliability management. It also presents the theory of reliability systems and its application as prescribed by industrial and government standards.

Author: Colin O. Wu
Publisher: CRC Press
ISBN: 0429939078
Category : Mathematics
Languages : en
Pages : 512

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Nonparametric Models for Longitudinal Data with Implementations in R presents a comprehensive summary of major advances in nonparametric models and smoothing methods with longitudinal data. It covers methods, theories, and applications that are particularly useful for biomedical studies in the era of big data and precision medicine. It also provides flexible tools to describe the temporal trends, covariate effects and correlation structures of repeated measurements in longitudinal data. This book is intended for graduate students in statistics, data scientists and statisticians in biomedical sciences and public health. As experts in this area, the authors present extensive materials that are balanced between theoretical and practical topics. The statistical applications in real-life examples lead into meaningful interpretations and inferences. Features: • Provides an overview of parametric and semiparametric methods • Shows smoothing methods for unstructured nonparametric models • Covers structured nonparametric models with time-varying coefficients • Discusses nonparametric shared-parameter and mixed-effects models • Presents nonparametric models for conditional distributions and functionals • Illustrates implementations using R software packages • Includes datasets and code in the authors’ website • Contains asymptotic results and theoretical derivations

Author: Tiina Ojanen
Publisher:
ISBN:
Category : Interpersonal relations in adolescence
Languages : en
Pages : 112

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Author: Gerald J. Hahn
Publisher: John Wiley & Sons
ISBN: 0470317442
Category : Mathematics
Languages : en
Pages : 423

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Presents a detailed exposition of statistical intervals and emphasizes applications in industry. The discussion differentiates at an elementary level among different kinds of statistical intervals and gives instruction with numerous examples and simple math on how to construct such intervals from sample data. This includes confidence intervals to contain a population percentile, confidence intervals on probability of meeting specified threshold value, and prediction intervals to include observation in a future sample. Also has an appendix containing computer subroutines for nonparametric statistical intervals.

Author: Neil J. Salkind
Publisher: SAGE
ISBN: 1412961270
Category : Philosophy
Languages : en
Pages : 1779

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"Comprising more than 500 entries, the Encyclopedia of Research Design explains how to make decisions about research design, undertake research projects in an ethical manner, interpret and draw valid inferences from data, and evaluate experiment design strategies and results. Two additional features carry this encyclopedia far above other works in the field: bibliographic entries devoted to significant articles in the history of research design and reviews of contemporary tools, such as software and statistical procedures, used to analyze results. It covers the spectrum of research design strategies, from material presented in introductory classes to topics necessary in graduate research; it addresses cross- and multidisciplinary research needs, with many examples drawn from the social and behavioral sciences, neurosciences, and biomedical and life sciences; it provides summaries of advantages and disadvantages of often-used strategies; and it uses hundreds of sample tables, figures, and equations based on real-life cases."--Publisher's description.

Author: Penny S. Reynolds
Publisher: John Wiley & Sons
ISBN: 1119799988
Category : Medical
Languages : en
Pages : 294

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A Guide to Sample Size for Animal-based Studies Understand a foundational area of experimental design with this innovative reference Animal-based research is an essential part of basic and preclinical research, but poses a unique set of experimental design challenges. The most important of these are the 3Rs − Replacement, Reduction and Refinement − the principles comprising the ethical framework for humane animal-based studies. However, many researchers have difficulty navigating the design trade-offs necessary to simultaneously minimize animal use, and produce scientific information that is both rigorous and reliable. A Guide to Sample Size for Animal-based Studies meets this need with a thorough, accessible reference work to the subject. This book provides a straightforward systematic approach to “rightsizing” animal-based experiments, with sample size estimates based on the fundamentals of statistical thinking: structured research questions, variation control and appropriate design of experiments. The result is a much-needed guide to planning animal-based experiments to ensure scientifically valid and reliable results. This book offers: Step-by-step guidance in diverse methods for approximating and refining sample size Detailed treatment of research topics specific to animal-based research, including pilot, feasibility and proof-of-concept studies Sample size approximation methods for different types of data − binary, continuous, ordinal, time to event − and different study types − description, comparison, nested designs, reference interval construction and dose-response studies Numerous worked examples, using real data from published papers, together with SAS and R code A Guide to Sample Size for Animal-based Studies is a must-have reference for preclinical and veterinary researchers, as well as ethical oversight committees and policymakers.

Author: Robert J. Grissom
Publisher: Routledge
ISBN: 1136632344
Category : Psychology
Languages : en
Pages : 532

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Book Description
Noted for its comprehensive coverage, this greatly expanded new edition now covers the use of univariate and multivariate effect sizes. Many measures and estimators are reviewed along with their application, interpretation, and limitations. Noted for its practical approach, the book features numerous examples using real data for a variety of variables and designs, to help readers apply the material to their own data. Tips on the use of SPSS, SAS, R, and S-Plus are provided. The book's broad disciplinary appeal results from its inclusion of a variety of examples from psychology, medicine, education, and other social sciences. Special attention is paid to confidence intervals, the statistical assumptions of the methods, and robust estimators of effect sizes. The extensive reference section is appreciated by all. With more than 40% new material, highlights of the new editon include: three new multivariate chapters covering effect sizes for analysis of covariance, multiple regression/correlation, and multivariate analysis of variance more learning tools in each chapter including introductions, summaries, "Tips and Pitfalls" and more conceptual and computational questions more coverage of univariate effect sizes, confidence intervals, and effect sizes for repeated measures to reflect their increased use in research more software references for calculating effect sizes and their confidence intervals including SPSS, SAS, R, and S-Plus the data used in the book are now provided on the web along with new data and suggested calculations with IBM SPSS syntax for computational practice. Effect Sizes for Research covers standardized and unstandardized differences between means, correlational measures, strength of association, and parametric and nonparametric measures for between- and within-groups data. Intended as a resource for professionals, researchers, and advanced students in a variety of fields, this book is also an excellent supplement for advanced statistics courses in psychology, education, the social sciences, business, and medicine. A prerequisite of introductory statistics through factorial analysis of variance and chi-square is recommended.