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Summary Furr & Bacharach (2014) - Psychometrics An Introduction - Chapter 5 $3.74
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Summary Furr & Bacharach (2014) - Psychometrics An Introduction - Chapter 5

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Summary study book Psychometrics of R. Michael Furr, Dr. Verne R. Bacharach (H5) - ISBN: 9781452256801, Edition: 1, Year of publication: 2013 (Summary chapter 5)

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  • February 18, 2017
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Furr, & Bacharach (2014) – Psychometrics An introduction




Chapter 5 – Reliability: Conceptual Basis
Overview of reliability and classical test theory
- Reliable: ability to reflect real psychological differences accurately. Continuum of
reliability.
- Classical test theory (CTT): measurement theory that defines conceptual basis of
reliability + outlines procedures for estimating reliability of psychological measures.
o Observed scores: values obtained from measurement of characteristic.
o True scores (signal): real amount of characteristic. Observed scores interpreted
as good estimates of true scores, because most research are intended to
reflect true psychological characteristics.
o Reliability (signal/signal+noise): reflects extent to which differences in
respondents’ test scores are function of their true psychological differences, as
opposed to measurement error. Is an unobserved feature of test scores 
estimate (compare intelligence).
o Measurement error (signal + noise): extent to which ‘other’ characteristics
contribute to differences in observed scores  create inconsistency between
observed + true scores. Score is never perfectly reliable, always some error;
BUT: hard to find all sources of measurement error (e.g., measuring babies’
length affected by amount of squirming, or different nurses measuring babies).

Observed scores, true scores, and measurement error
- Reliability depends on:
o Extent to which differences in test scores can be attributed to real inter- or
intra-individual differences.
o Extent to which differences in test scores are function of measurement error.
- CTT: observed score is true score + error 
o Assumption about measurement error: error occurs as if it’s random = just as
likely to inflate any score as to decrease score. Simply chance to score
higher/lower due to error  independent from true scores, because error can
influence every true score, whether it is high or low.
 Error tends to cancel itself out across respondents = inflates scores of
some respondents + deflates of other  average effect of error = 0.
 Error scores are uncorrelated with true scores: still affecting observed
scores, independent of level of true score.




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