Response Variable


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Monte Carlo Simulation Power Analysis Using Mplus and R


Monte Carlo Simulation Power Analysis Using Mplus and R

Author: James Peugh

language: en

Publisher: Guilford Publications

Release Date: 2026-03-26


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Planning effective research investigations requires sophisticated power analysis techniques. This book provides readers with clearly explained tools for using Monte Carlo simulations to estimate the needed sample sizes for adequate statistical power for a variety of modern research designs. Featuring step-by-step instructions, chapters move from simpler cross-sectional designs and path tracing rules to advanced longitudinal designs, while incorporating mediation, moderation, and missing data considerations. Worked-through applied examples with annotated Mplus and R syntax scripts, sample power analysis write-ups, and end-of-chapter suggested readings are also included. The companion website offers Mplus and R code for four additional power analysis models--latent variable moderation, discrete- and continuous-time survival analyses, cross-sectional and longitudinal two-level models, and moderated mediation--as well as supplemental computational materials.

Fundamentals of Clinical Trials


Fundamentals of Clinical Trials

Author: Lawrence M. Friedman

language: en

Publisher: Springer Science & Business Media

Release Date: 1998


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This classic reference, now updated with the newest applications and results, addresses the fundamentals of such trials based on sound scientific methodology, statistical principles, and years of accumulated experience by the three authors.

International Handbook of Research Methods And Statistics (Volume 4)


International Handbook of Research Methods And Statistics (Volume 4)

Author: Urfat Anjem MIr, Sonam Joldan, Vinay Kumar, Sonia Saini

language: en

Publisher: The Readers Paradise

Release Date:


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The International Handbook of Research in Statistics Education provides a comprehensive, global overview of the latest research, trends, and practices in the teaching and learning of statistics. Edited by Dani Ben-Zvi, Katie Makar, and Joan Garfield, this handbook brings together leading scholars to explore foundational theories, innovative methodologies, and emerging challenges in statistics education. Covering topics such as statistical reasoning, learning trajectories, teacher development, curriculum design, and the role of technology, the book serves as a critical resource for researchers, educators, curriculum developers, and policymakers. Rich with evidence-based insights and international perspectives, it offers both theoretical depth and practical applications, making it an essential guide for advancing the field of statistics education.