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