Health Measurement Scales A Practical Guide to Their Development and Use

ISBN-10: 0199231885

ISBN-13: 9780199231881

Edition: 4th 2008

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Description: Clinicians and those in health sciences are frequently called upon to measure subjective states such as attitudes, feelings, quality of life, educational achievement and aptitude, and learning style in their patients. This fourth edition of Health Measurement Scales enables these groups, whooften have limited knowledge of statistics, to both develop scales to measure non-tangible health outcomes, and better evaluate and differentiate between existing tools. It covers how the individual items are developed; various biases that can affect responses (eg social desirability, yea-saying, framing); various response options; how to select the best items in the set; how to combine them into a scale; and then how to determine the reliability and validity of thescale. It concludes with a discussion of ethical issues that may be encountered, and guidelines for reporting the results of the scale development process. Appendices include a comprehensive guide to finding existing scales, and a brief introduction to exploratory and confirmatory factor analysis. It synthesizes the theory of scale construction with practical advice, making it the ultimate guide to how to develop and validate measurement scales that are to be used in the health sciences.

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Book details

Edition: 4th
Copyright year: 2008
Publisher: Oxford University Press, Incorporated
Publication date: 12/15/2008
Binding: Paperback
Pages: 428
Size: 6.00" wide x 8.75" long x 1.00" tall
Weight: 1.430
Language: English

Introduction
Basic concepts
Searching the literature
Critical review
Empirical forms of validity
The two traditions of assessment
The reduction of measurement error
Summary
Devising the items
The source of items
Content validity
Generic versus specific scales and the 'fidelity versus bandwidth' issue
Translation
Scaling responses
Introduction
Some basic concepts
Categorical judgments
Continuous judgments
To rate or to rank
Multidimensional scaling
Selecting the items
Interpretability
Face validity
Frequency of endorsement and discrimination
Homogeneity of the items
Multifactor inventories
When homegeneity does not matter
Putting it all together
Biases in responding
The differing perspectives
Answering questions: the cognitive requirements
Optimizing and satisficing
Social desirability and faking good
Deviation and faking bad
Yea-saying or acquiescencne
End-aversion, positive skew, and halo
Framing
Biases related to the measurement of change
Estimates of the prior state-implicit theory of change
Reconciling the two positions
Proxy reporting
Testing the items
From items to scales
Weighting the items
Missing items
Multiplicative composite scores
Transforming the final score
Percentiles
Standard and standardized scores
Normalized scores
Age and sex norms
Establishing cut points
Methods based on characteristics of the distribution
Methods based on judgment
Absolute methods
Receiver operating characteristics curves
Summary
Reliability
Basic concepts
Philosophical implications
Terminology
Defining reliability
Other considerations in calculating the reliability of a test
The observer nested within subject
Multiple observations
Other types of reliability
Different forms of the reliability coefficient
Kappa coefficient versus the ICC
The method of Bland and Altman
Issues of interpretation
Improving reliability
Standard error of the reliability coefficient and sample size
Reliability generalization
The average value of r and �
The variance of the reliability estimates
Combining estimates
Factors affecting the reliability
Summary
Generalizability theory
Generalizability theory fundamentals
An Example
The First Step-the ANOVA
From ANOVA to G coefficients
Relative vs. Absolute Error
Equivalent for the nested design
Generalizability of an average
from G study to D study
ANOVA for statisticians and ANOVA for psychometricians
Confidence intervals for G coefficients
The general rules to compute G coefficients
Getting the computer to do it for you
Some Common Examples
Uses and abuses of G theory
Summary
Validity
Why assess validity?
Reliability and validity
A history of the 'types' of validity
Content validation
Criterion validation
Construct validation
Construct validational studies
Extreme groups
Convergent and discriminant validation
Consequential validation
The multitrait-multimethod matrix
Summary
Responsiveness and sensitivity to change
Validity and 'types of indices'
Biases in validity assessment
Unreliability of the criterion
Changes in the sample
Validity generalization
Summary
Measuring change
Introduction
The goal of measurement of change
Why not measure change directly?
Measures of association-reliability and sensitivity to change
Difficulties with changes scores in experimental designs
Change scores and quasi-experimental designs
Measuring change using multiple observations: growth curves
How much change is enough?
Summary
Item response theory
Problems with classical test theory
The introduction of item response theory
Item characteristic curves
The one-parameter model
The two-and three-parameter models
Polytomous models
Item information
Item fit
Person fit
Differential item functioning
Unidimensionality and local independence
The standard error of measurement
Equating tests
Sample size
Mokken scaling
Advantages
Disadvantages
Computer programs
Methods of administration
Face-to-face interviews
Advantages
Disadvantages
Telephone questionnaires
Random digit dialling
Advantages
Disadvantages
Mailed questionnaires
The necessity of persistence
Computer-assisted administration
Using e-mail and the Web
Personal data assistants
Reporting response rates
Ethical considerations
Reporting test results
Standards for Educational and Psychological Testing
The STARD initiative
Summary
Appendices
Further reading
Where to find tests
A (very) brief introduction to factor analysis
Author Index
Subject Index
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