Cheng Hua – författare

Rasch Measurement Theory Analysis in R provides researchers and practitioners with a step-by-step guide for conducting Rasch measurement theory analyses using R. It includes theoretical introductions to major Rasch measurement principles and techniques, demonstrations of analyses using several R packages that contain Rasch measurement functions, and sample interpretations of results. Features:Accessible to users with relatively little experience with R programmingReproducible data analysis examples that can be modified to accommodate users’ own dataAccompanying e-book website with links to additional resources and R code updates as neededFeatures dichotomous and polytomous (rating scale) Rasch models that can be applied to data from a wide range of disciplinesThis book is designed for graduate students, researchers, and practitioners across the social, health, and behavioral sciences who have a basic familiarity with Rasch measurement theory and with R. Readers will learn how to use existing R packages to conduct a variety of analyses related to Rasch measurement theory, including evaluating data for adherence to measurement requirements, applying the dichotomous, Rating Scale, Partial Credit, and Many-Facet Rasch models, examining data for evidence of differential item functioning, and considering potential interpretations of results from such analyses.

Rasch Measurement Theory Analysis in R provides researchers and practitioners with a step-by-step guide for conducting Rasch measurement theory analyses using R. It includes theoretical introductions to major Rasch measurement principles and techniques, demonstrations of analyses using several R packages that contain Rasch measurement functions, and sample interpretations of results. Features:Accessible to users with relatively little experience with R programmingReproducible data analysis examples that can be modified to accommodate users’ own dataAccompanying e-book website with links to additional resources and R code updates as neededFeatures dichotomous and polytomous (rating scale) Rasch models that can be applied to data from a wide range of disciplinesThis book is designed for graduate students, researchers, and practitioners across the social, health, and behavioral sciences who have a basic familiarity with Rasch measurement theory and with R. Readers will learn how to use existing R packages to conduct a variety of analyses related to Rasch measurement theory, including evaluating data for adherence to measurement requirements, applying the dichotomous, Rating Scale, Partial Credit, and Many-Facet Rasch models, examining data for evidence of differential item functioning, and considering potential interpretations of results from such analyses.

This book comprises select proceedings of the workshop “Practical inverse problems and their prospects” held online by zoom, from Mar 2nd to Mar. 4th, 2022, supported by Institute of Mathematics for Industry, Kyushu University focusing on cutting-edge research carried out in the areas of practical inverse problems based on industry-academia and interdisciplinary collaborations.Various themes on practical inverse problems covered in this book are medical imaging, non-destructive and non-invasive inspections, viscoelastic waves, remote sensing, infrared light tomography, maintenance of infrastructure, and so on, and mathematical theories in inverse problems are also handled in these proceedings.All papers in this book are written by qualified authors in the practical inverse problems area and also the papers are newly announced. Readers can get leading-edge information on practical inverse problems.