具体描述
Review
From reviews of the previous edition:
`... explains apparently complex issues to an uninformed audience. At the same time the authors avoid oversimplifying the basics.' The Lancet
`It fills a notable gap in the literature... it provides a very comprehensive and readable introduction.' British Journal of Psychiatry
Book Description
This is the new edition of the highly successful practical guide for clinicians developing tools to measure subjective states, attitudes or non-tangible outcomes in their patients. It is widely used by people from many disciplines, who have only a limited knowledge of statistics. This thoroughly updated edition of Health Measurement Scales, Third Edition gives more details on cognitive requirements in answering questions, and how this influences scale development. There is now an expanded discussion of generalizability theory, a completely revised chapter on Item Response Theory and many revisions are included, based on the latest research findings. These features combine to provide the most up-to-date guide to measuring scale development available. It synthesizes the theory of scale construction with practical advice, culled from the literature and the authors' experience, about how to develop and validate measurement scales to be used in the health sciences. The theory goes into issues of reliability, generalizability theory, validity, the measurement of change, the cognitive requirements of answering questions, and item response theory. Practical issues cover devising the items, biases that may affect the responses, pre-testing and weeding out poorly performing items, combining items into scales, setting cut points, and the practical issues of using scales in various ways, such as face-to-face interviews; mailed or telephone-administered surveys; and over the internet. One chapter also discusses some of the ethical issues that scale developers and users should be aware of. Appendices lead the reader to other readings; sources of already developed scales and items; and a very brief introduction to exploratory and confirmatory factor analysis.
Most Helpful Customer Reviews
2 of 2 people found the following review helpful:
Simple .......but yet comprehensive, June 25, 2001
By A Customer
This review is from: Health Measurement Scales: A Practical Guide to Their Development and Use (Oxford Medical Publications) (Paperback)
This is undoubtedly, one of the best books I have read in this area. The authors follow an appropriate sequence in terms of addressing scale development, testing and analyses issues. The best thing about the book is that it is really easy to comprehend and covers all the important areas. I feel it is a "must buy" for professionals in the area of health-related quality of life and outcomes research. Comment | Permalink | Was this review helpful to you? (Report this)
very nice book, excellent practical advice, February 14, 2008
By J. Verkuilen (New York, NY United States) - See all my reviews
I really like this book and wish that I'd found out about it before my psychometrics class in the spring started, because I would have assigned it in a heartbeat. It's got a lot of the kind of practical advice that anyone thinking of creating a scale REALLY needs to hear first, including the #1 bit of advice: Should you make one yourself? For instance, excellent summaries of the work on scale usage biases by Jon Krosnick, Norbert Schwartz, etc., give useful cautionary information for scale constructors. I have a few disagreements---some of the advice about procedures such as some of the scaling methods they mention is out of date, for instance---but this is the sort of thing an expert in the field might disagree with. It certainly doesn't detract from the value of the book overall and I've learned a bunch I didn't know reading it. It'll be on the syllabus next time! Comment | Permalink | Was this review helpful to you? (Report this)
Best option, March 9, 2007
By Leonardo O. Costa "Leo Costa" (Sydney, NSW Australia) - See all my reviews
This book is definally the best one in the field, it is clear and provides all information about psychometry. Comment | Permalink | Was this review helpful to you? (Report this)
作者简介
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这本书的辅助资源配置堪称典范，是其价值的有力延伸。光盘（或在线资源包）中附带的那些经过严格清洗和预处理的模拟数据集，简直是为动手实践派读者量身定做的宝藏。我尝试着用书中介绍的结构方程模型（SEM）对其中一个数据集进行了重现分析，发现作者提供的示例代码——无论是使用哪种主流统计软件的语法——都详尽无遗，并且包含了详细的注释，解释了每一步参数设定的内在逻辑。更棒的是，这些数据集并非只是为了演示某个公式而存在，它们都带着清晰的背景故事和研究假设，使得练习不再枯燥，而是成为了一种情境化的学习。这种将理论与实践无缝对接的配套设计，极大地加速了我将所学知识转化为实际操作能力的过程，对于那些需要快速将学术知识应用于项目交付的研究人员来说，这套辅助材料的价值几乎是不可估量的。
评分这本书的装帧设计确实让人眼前一亮，封面那种哑光处理的质感，加上字体排版的疏密有致，立刻就给人一种专业、沉稳的感觉。我拿到手的时候，首先就被它厚实的纸张吸引住了，内页的纸张选择也十分考究，即便是在长时间阅读和标记重点后，也不会出现明显的透墨现象，这对于经常需要做笔记和查阅的读者来说，简直是福音。装订方面，我特别喜欢它能够完全平摊开来，这在阅读那些包含大量图表和公式的章节时，极大地提升了阅读体验，不用费力地去按压书脊，可以更专注于内容本身。而且，书中索引和目录的编制也做得非常人性化，结构清晰，查找特定主题非常方便，这体现了编者对读者需求的深刻理解。总的来说，从物理层面上看，这是一本被精心对待的作品，让人愿意长期珍藏和反复翻阅，而不是仅仅当作一本快消的参考书。书脊的设计也很有意思，虽然内容看起来学术性很强，但外表却散发着一种低调的优雅，这种反差感让人在办公室或图书馆里拿出它时，都倍感自信。
评分阅读这本书的过程，对我而言更像是一次与一位经验丰富导师的对话。作者的语言风格在保持高度学术性的同时，又充满了对读者的鼓励和引导。我特别注意到，在涉及“量表开发伦理”的部分，作者使用了大量现实案例进行反思，这些案例的选择非常贴近临床和教育研究的真实困境，例如，如何平衡研究的效度和受试者的隐私权，如何在跨文化应用中保持测量公平性等。他没有直接给出标准答案，而是引导读者去思考“为什么”以及“如何负责任地应用”这些工具。这种着重于批判性思维培养的叙述方式，远比单纯的知识灌输要有效得多。读完相关章节后，我感觉自己在处理自己的研究方案时，对“后果评估”的重视程度明显提升了一个档次，这是一种潜移默化的、难以量化的收获。
评分这本书在章节之间的逻辑衔接上，展现出了一种近乎建筑学般的精妙结构。它并不是简单地罗列各种量表类型，而是构建了一个从基础理论到高级应用的完整知识体系。开篇奠定了坚实的理论基石后，后续的内容就像是不断向上搭建楼层，每提升一个层次，都会以前面知识为支撑，引入更复杂、更具实际操作性的评估工具和伦理考量。我发现，作者在谈论到“测量误差来源”时，并没有停留在经典的随机误差和系统误差的划分，而是引入了情境依赖性误差（Context-Dependent Error）的概念，这一点非常具有前瞻性，让我对日常数据收集中的细微偏差有了全新的认识。这种层层递进、相互印证的编排方式，极大地降低了自学过程中的挫败感。你总能感觉到，当前面章节的疑惑，在后续章节中得到了意想不到的补充和解答，形成了一个完美的闭环学习体验。
评分我花了将近一个月的时间来系统地研读其中关于“测量一致性与信度评估”的章节，其深度和广度远远超出了我原先的预期。作者在阐述Cronbach’s Alpha时，并没有止步于最基础的公式讲解，而是深入剖析了不同数据分布下该系数的局限性，并通过一系列精心构造的模拟案例，展示了如何识别和处理潜在的维度异质性问题。尤其值得称赞的是，他对因子分析（Factor Analysis）的论述，从探索性到验证性，每一步的逻辑推导都极其严谨，清晰地勾勒出了从理论构建到实际数据拟合的完整路径。我尤其欣赏作者在解释复杂统计概念时所使用的类比方式，那种深入浅出的表达，使得原本可能令人生畏的数学模型变得触手可及。例如，他将主成分分析比喻为“提炼信息的黄金比例”，瞬间就抓住了核心要义。对于任何想要在量化研究领域深耕的人来说，这些章节提供的不仅仅是方法论，更是一种严谨的思维训练框架。
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