Michael Goldstein

Sam Goldstein

Susan M. Sheridan

Clare B. Jones

Lauren Braswell

From the Reviews of the First Edition "A well written, extremely readable addition to the literature on ADHD." —Journal of Clinical Psychology "Goldstein and Goldstein’s volume should be on every practitioner’s bookcase as a solid and comprehensive guide…" —Archives of Clinical Neuropsychology A proven approach to the diagnosis and management of one of the most challenging childhood disorders ADHD is the most commonly diagnosed behavioral disorder among children and adolescents. It is also one of the most difficult to manage. In this updated and expanded Second Edition of their critically acclaimed practitioner’s guide, Drs. Sam Goldstein and Michael Goldstein describe a proven multidisciplinary approach to the diagnosis and treatment of childhood ADHD, developed at the prestigious Neurology, Learning and Behavior Center in Salt Lake City. A valuable working resource for practitioners who manage children with ADHD, Managing Attention Deficit Hyperactivity in Children, Second Edition features: In-depth reviews of the latest research into the etiology and development of ADHD Step-by-step guidelines on evaluating ADHD—medically, at home, and in school A multidisciplinary approach to treating ADHD that combines medical, family, cognitive, behavioral, and school interventions Critical discussions of controversial new treatments, including diets, dietary supplements, and EEG/biofeedback

A Guide for Practitioners

Managing Attention Deficit Hyperactivity Disorder in Children

MEET PIKACHU'S ANCESTORS! Welcome to the first of its kind introduction to the mystical and mischievous ancient Japanese monsters, the YOKAI! Through poetry and art, you'll discover a new world where Pikachu's predecessors reigned. Each monster is introduced through a tonka (Japanese poem), and you'll also enjoy learning the sounds of the Japanese alphabet.

Yokai Character Collection

David Wooff

Bayesian methods combine information available from data with any prior information available from expert knowledge. The Bayes linear approach follows this path, offering a quantitative structure for expressing beliefs, and systematic methods for adjusting these beliefs, given observational data. The methodology differs from the full Bayesian methodology in that it establishes simpler approaches to belief specification and analysis based around expectation judgements. Bayes Linear Statistics presents an authoritative account of this approach, explaining the foundations, theory, methodology, and practicalities of this important field. The text provides a thorough coverage of Bayes linear analysis, from the development of the basic language to the collection of algebraic results needed for efficient implementation, with detailed practical examples. The book covers: The importance of partial prior specifications for complex problems where it is difficult to supply a meaningful full prior probability specification. Simple ways to use partial prior specifications to adjust beliefs, given observations. Interpretative and diagnostic tools to display the implications of collections of belief statements, and to make stringent comparisons between expected and actual observations. General approaches to statistical modelling based upon partial exchangeability judgements. Bayes linear graphical models to represent and display partial belief specifications, organize computations, and display the results of analyses. Bayes Linear Statistics is essential reading for all statisticians concerned with the theory and practice of Bayesian methods. There is an accompanying website hosting free software and guides to the calculations within the book.

Michael Goldstein

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