Measurement Theory and Applications for the Social Sciences

The text covers scale development, item writing, reliability and validity, advanced topics, and end-of-chapter exercises. It also provides annotated examples, syntax, and datasets on the companion website.

\n Format: Hardback
\n Length: 661 pages
\n Publication date: 22 March 2018
\n Publisher: Guilford Publications
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When determining whether a scale is appropriate for a given measurement situation, it is crucial to consider various types of validity evidence. Validity refers to the extent to which a scale measures what it intends to measure. Here are some key types of validity evidence to consider:
Construct validity: Construct validity assesses the extent to which the scale's items and scales reflect the underlying construct or concept being measured. It involves evaluating the theoretical basis of the scale, the relationship between the scale's items and the construct, and the reliability and validity of the scale's measurements.
Content validity: Content validity measures the extent to which the scale's items cover the relevant aspects of the construct or concept being measured. It involves evaluating the relevance, clarity, and comprehensiveness of the scale's items and ensuring that they represent the different dimensions or aspects of the construct.
Concurrent validity: Concurrent validity assesses the extent to which a scale measures the same construct as a different scale or measure. It involves comparing the scores on the two scales or measures to determine if they are statistically related or if they measure the same thing.
Predictive validity: Predictive validity assesses the extent to which a scale predicts or correlates with a relevant outcome or criterion. It involves comparing the scores on the scale with the scores on a different measure or outcome to determine if the scale is able to predict or correlate with the outcome.
Internal consistency reliability: Internal consistency reliability measures the extent to which the scale's items are consistent with each other. It involves calculating the coefficient alpha, which indicates the degree of agreement between the items within a scale.
Test-retest reliability: Test-retest reliability measures the extent to which a scale's scores are consistent over time. It involves administering the scale to the same individuals at two different times and comparing the scores to determine if there is a reliable difference between the scores.

Reliability evidence is also an important consideration when evaluating the appropriateness of a scale. Reliability refers to the extent to which a scale produces consistent and reliable measurements over time and across different situations. Here are some key types of reliability evidence to consider:
Cronbach's alpha coefficient: Cronbach's alpha coefficient is a measure of internal consistency reliability. It calculates the degree of agreement between the items within a scale and provides an estimate of the scale's reliability. A high Cronbach's alpha coefficient indicates that the scale's items are consistent with each other and that the scale is reliable.
Split-half reliability: Split-half reliability measures the extent to which the scores on a scale are consistent when the scale is divided into two halves. It involves administering the scale to half of the individuals and then comparing the scores on the two halves to determine if there is a reliable difference between them.
Test-retest reliability: Test-retest reliability measures the extent to which a scale's scores are consistent over time. It involves administering the scale to the same individuals at two different times and comparing the scores to determine if there is a reliable difference between the scores.

In conclusion, when selecting and using a scale for measurement, it is essential to consider both validity and reliability evidence. Validity evidence helps ensure that the scale measures what it intends to measure, while reliability evidence ensures that the scale produces consistent and reliable measurements. By evaluating these types of evidence, researchers and practitioners can make informed decisions about the selection and use of measurement instruments in social and behavioral sciences.

\n Weight: 1376g\n
Dimension: 188 x 261 x 37 (mm)\n
ISBN-13: 9781462532131\n \n