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Summary Furr & Bacharach (2014) - Psychometrics An Introduction - Chapter 10 $3.21   Add to cart

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Summary Furr & Bacharach (2014) - Psychometrics An Introduction - Chapter 10

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Summary study book Psychometrics of R. Michael Furr, Dr. Verne R. Bacharach (H10) - ISBN: 9781452256801, Edition: 1, Year of publication: 2013 (Summary chapter 10)

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By: linaklee • 6 year ago

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By: sophiaamllr • 6 year ago

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Furr, & Bacharach (2014) – Psychometrics An introduction




Chapter 10 – Response biases
Important because can harm the psychometric quality of many types of tests, scales +
inventories  can diminish reliability + validity, which in turns affects interpretation of
research.

Types of response biases
- Acquiescence bias (“yea-saying + nay-saying”): occurs when an individual agrees with
statements without regard for meaning of those statements. Usually in one direction.
o Often found on personality trait inventories, attitude questionnaires, interest
inventories, clinical inventories + marketing surveys.
o Usually with Likert-scale; sum is total score  having highest score on
questionnaire = having highest level of construct?
o Phrasing items important: must be all in same direction (positive/agreement or
negative/disagreement).
o Implications for test users:
 If some have bias, others not: test users might not be able to detect
which respondents have high level of construct + which respondents
are simply responding with bias  misinformed + misguided decisions.
 Imply that there’s a correlation between 2 constructs, while there’s
actually none  only look at correlations among only those
participants who responded validly (because otherwise high artificially
correlation possible).
 If multiple tests are ‘contaminated’ by the bias, then the tests will be more
strongly correlated with each other than are the underlying constructs
(because acquiescent = scoring relatively high on both tests).
o Also ‘nay-saying’ bias: disagreeing with statement. Similar effects as ‘yeah-
saying’  disagree on both tests = artificially more positive correlations.
o Bias seems to occur most often when respondents don’t easily understand test
items.
- Extreme + moderate responding: responses reflecting different degrees of intensity/
endorsement/occurrence (e.g., ‘often’, or ‘almost always’. Problem is the differences
in tendency to use/avoid extreme response options (even when having same true
level of construct).
o Implications:
 Extremity bias  ambiguity in respondents’ scores  decision makers
might make inappropriate decisions.
 Inaccurate conclusions about correlations  can generate artificial
differences among respondents’ test scores.
 Can obscure true differences among respondents’ construct levels: e.g.,
identical test scores, but different true trait levels because one of
participants is reluctant to use more extreme response option  test
score isn’t as high as trait level.
 Can lead to inaccurate research conclusions.
o Use of extreme/moderate response options is itself not bias/problem, if it
reflects an individual’s true trait level (i.e., person is truly extreme).
o Problems arise when:

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