Power Analysis of Trials with Multilevel Data

Power Analysis of Trials with Multilevel Data
Author: Mirjam Moerbeek
Publisher: CRC Press
Total Pages: 275
Release: 2015-07-01
Genre: Mathematics
ISBN: 1498729908

Power Analysis of Trials with Multilevel Data is a valuable reference for anyone who wants to perform power calculations on trials with hierarchical data. It provides a thorough overview of power analysis, familiarizing you with terminology and notation, outlining the key concepts of statistical power and power analysis, and covering all common hierarchical designs.

Doing Meta-Analysis with R

Doing Meta-Analysis with R
Author: Mathias Harrer
Publisher: CRC Press
Total Pages: 500
Release: 2021-09-15
Genre: Mathematics
ISBN: 1000435636

Doing Meta-Analysis with R: A Hands-On Guide serves as an accessible introduction on how meta-analyses can be conducted in R. Essential steps for meta-analysis are covered, including calculation and pooling of outcome measures, forest plots, heterogeneity diagnostics, subgroup analyses, meta-regression, methods to control for publication bias, risk of bias assessments and plotting tools. Advanced but highly relevant topics such as network meta-analysis, multi-three-level meta-analyses, Bayesian meta-analysis approaches and SEM meta-analysis are also covered. A companion R package, dmetar, is introduced at the beginning of the guide. It contains data sets and several helper functions for the meta and metafor package used in the guide. The programming and statistical background covered in the book are kept at a non-expert level, making the book widely accessible. Features • Contains two introductory chapters on how to set up an R environment and do basic imports/manipulations of meta-analysis data, including exercises • Describes statistical concepts clearly and concisely before applying them in R • Includes step-by-step guidance through the coding required to perform meta-analyses, and a companion R package for the book

Practical Statistical Power Analysis

Practical Statistical Power Analysis
Author: Zhiyong Zhang
Publisher: Isdsa Press
Total Pages: 358
Release: 2018-05
Genre:
ISBN: 9781946728029

The importance of conducting a statistical power analysis at the beginning of a study is universally accepted. Without careful planning, a study can easily fail to detect an existing effect by chance. This book teaches how to conduct power analysis for a range of models from correlation and t-test to structural equation models and multilevel models. Both a graphical Web software WebPower and an R package are introduced to practically conduct the analysis.

Introduction to Power Analysis

Introduction to Power Analysis
Author: E. C. Hedberg
Publisher: SAGE Publications
Total Pages: 157
Release: 2017-12-05
Genre: Mathematics
ISBN: 1506343112

Introduction to Power Analysis: Two-Group Studies provides readers with the background, examples, and explanation they need to read technical papers and materials that include complex power analyses. This clear and accessible guide explains the components of test statistics and their sampling distributions, and author Eric Hedberg walks the reader through the simple and complex considerations of this research question. Filled with graphics and examples, the reader is taken on a tour of power analyses from covariates to clusters, seeing how the complicated task of comparing two groups, and the power analysis, can be made easy.

Multilevel Analysis

Multilevel Analysis
Author: Tom A. B. Snijders
Publisher: SAGE
Total Pages: 282
Release: 1999
Genre: Mathematics
ISBN: 9780761958901

Multilevel analysis covers all the main methods, techniques and issues for carrying out multilevel modeling and analysis. The approach is applied, and less mathematical than many other textbooks.

Handbook of Regression Modeling in People Analytics

Handbook of Regression Modeling in People Analytics
Author: Keith McNulty
Publisher: CRC Press
Total Pages: 272
Release: 2021-07-29
Genre: Business & Economics
ISBN: 1000427897

Despite the recent rapid growth in machine learning and predictive analytics, many of the statistical questions that are faced by researchers and practitioners still involve explaining why something is happening. Regression analysis is the best ‘swiss army knife’ we have for answering these kinds of questions. This book is a learning resource on inferential statistics and regression analysis. It teaches how to do a wide range of statistical analyses in both R and in Python, ranging from simple hypothesis testing to advanced multivariate modelling. Although it is primarily focused on examples related to the analysis of people and talent, the methods easily transfer to any discipline. The book hits a ‘sweet spot’ where there is just enough mathematical theory to support a strong understanding of the methods, but with a step-by-step guide and easily reproducible examples and code, so that the methods can be put into practice immediately. This makes the book accessible to a wide readership, from public and private sector analysts and practitioners to students and researchers. Key Features: 16 accompanying datasets across a wide range of contexts (e.g. academic, corporate, sports, marketing) Clear step-by-step instructions on executing the analyses Clear guidance on how to interpret results Primary instruction in R but added sections for Python coders Discussion exercises and data exercises for each of the main chapters Final chapter of practice material and datasets ideal for class homework or project work.

Design and Analysis of Group-randomized Trials

Design and Analysis of Group-randomized Trials
Author: David M. Murray
Publisher: Monographs in Epidemiology and
Total Pages: 481
Release: 1998
Genre: Medical
ISBN: 0195120361

Community or group-randomized trials, which are usually done to evaluate the effect of health promotion effors. It reviews the underlying issues, describes the most widely used research design, and presents the many approaches to analysis that are now available.

Handbook of Multilevel Analysis

Handbook of Multilevel Analysis
Author: Jan Deleeuw
Publisher: Springer Science & Business Media
Total Pages: 498
Release: 2007-12-26
Genre: Mathematics
ISBN: 0387731865

This book presents the state of the art in multilevel analysis, with an emphasis on more advanced topics. These topics are discussed conceptually, analyzed mathematically, and illustrated by empirical examples. Multilevel analysis is the statistical analysis of hierarchically and non-hierarchically nested data. The simplest example is clustered data, such as a sample of students clustered within schools. Multilevel data are especially prevalent in the social and behavioral sciences and in the biomedical sciences. The chapter authors are all leading experts in the field. Given the omnipresence of multilevel data in the social, behavioral, and biomedical sciences, this book is essential for empirical researchers in these fields.

Statistical Power Analysis

Statistical Power Analysis
Author: Kevin R. Murphy
Publisher: Routledge
Total Pages: 247
Release: 2003-08-01
Genre: Psychology
ISBN: 1135625328

This book presents a simple and general method for conducting statistical power analysis based on the widely used F statistic. The book illustrates how these analyses work and how they can be applied to problems of studying design, to evaluate others' research, and to choose the appropriate criterion for defining "statistically significant" outcomes. Statistical Power Analysis examines the four major applications of power analysis, concentrating on how to determine: *the sample size needed to achieve desired levels of power; *the level of power that is needed in a study; *the size of effect that can be reliably detected by a study; and *sensible criteria for statistical significance. Highlights of the second edition include: a CD with an easy-to-use statistical power analysis program; a new chapter on power analysis in multi-factor ANOVA, including repeated-measures designs; and a new One-Stop PV Table to serve as a quick reference guide. The book discusses the application of power analysis to both traditional null hypothesis tests and to minimum-effect testing. It demonstrates how the same basic model applies to both types of testing and explains how some relatively simple procedures allow researchers to ask a series of important questions about their research. Drawing from the behavioral and social sciences, the authors present the material in a nontechnical way so that readers with little expertise in statistical analysis can quickly obtain the values needed to carry out the power analysis. Ideal for students and researchers of statistical and research methodology in the social, behavioral, and health sciences who want to know how to apply methods of power analysis to their research.

Intensive Longitudinal Methods

Intensive Longitudinal Methods
Author: Niall Bolger
Publisher: Guilford Press
Total Pages: 274
Release: 2013-01-22
Genre: Psychology
ISBN: 1462506925

This book offers a complete, practical guide to doing an intensive longitudinal study with individuals, dyads, or groups. It provides the tools for studying social, psychological, and physiological processes in everyday contexts, using methods such as diary and experience sampling. A range of engaging, worked-through research examples with datasets are featured. Coverage includes how to: select the best intensive longitudinal design for a particular research question, apply multilevel models to within-subject designs, model within-subject change processes for continuous and categorical outcomes, assess the reliability of within-subject changes, assure sufficient statistical power, and more. Several end-of-chapter write-ups illustrate effective ways to present study findings for publication. Datasets and output in SPSS, SAS, Mplus, HLM, MLwiN, and R for the examples are available on the companion website (www.intensivelongitudinal.com).