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Started by Daniel Read
Wed, 02 Sep 1992 12:15
unweighted mean of means
Author: Daniel Read
Date: Wed, 02 Sep 1992 12:15
Date: Wed, 02 Sep 1992 12:15
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I have some questionnaire data from which I wish to derive a "knowledge index" by taking the mean response to several of the questions. However, these are true-false questions and more of the questions are true than false. Moreover, many people are clearly disposed to choose True as a response rather than False. Of course, to the degree that they have this bias their knowledge index is inflated. I have solved this problem by taking the (unweighted) mean of the mean answer to false questions plus the mean answer to true questions. My question: can you think of anything wrong with doing this? BTW, I realize that taking the "mean" of ordinal responses is problematic, but I'm willing to weather this storm on my own -- which doesn't mean that I am uninterested in comments on that issue. Thanks in advance, daniel
Re: unweighted mean of means
Author: Hume Winzar
Date: Thu, 03 Sep 1992 09:06
Date: Thu, 03 Sep 1992 09:06
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>I have some questionnaire data from which I wish to derive a "knowledge
>index" by taking the mean response to several of the questions.
>However, these are true-false questions and more of the questions are
>true than false. Moreover, many people are clearly disposed to choose
>True as a response rather than False. Of course, to the degree that
>they have this bias their knowledge index is inflated.
>I have solved this problem by taking the (unweighted) mean of the mean
>answer to false questions plus the mean answer to true questions.
An alternative is an approach often used for rescaling multiple choice
exams:
In this case there is a 50% probability of guessing a correct answer.
So all of the wrong answers must be about half of the guesses - the other
half of the guesses were correct by pure chance. After calculating the
probable number of guesses you can subtract this number from the total
number of questions. In this case it reduces to, for each person:
SCORE = N(correct) - N(wrong)
Of course this does not get you arround the systematic bias created by the
propensity to answer TRUE more often.
- - - - - - - - -
| _--_|\ | Hume Winzar
| / \ | Commerce School,
| *_.--._/ | Murdoch University,
| v | Perth, Western Australia
- - - - - - - - -
E_Mail winzar@csuvax1.csu.murdoch.edu.au
Phone: (09) 310 7389
Fax: (09) 310 5004
Re: unweighted mean of means
Author: Duncan Murdoch
Date: Thu, 03 Sep 1992 14:08
Date: Thu, 03 Sep 1992 14:08
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In article <winzar.73.0@newsman> winzar@newsman (Hume Winzar) writes: >Of course this does not get you arround the systematic bias created by the >propensity to answer TRUE more often. That bias results from a mis-designed questionaire. If the correct choice is randomly chosen (with equal probabilities) and the question worded to fit, then any system of picking answers that doesn't depend on knowledge about the statement will have equal chances of picking the right and wrong answers. You should also try to make knowledge of the subject matter important, e.g. don't do this: As everyone knows, 2+2 = 5. True False 2+2=4. True False As everyone knows, unbiased estimates of the variance are essential. True False Most sponsored surveys are just about this blatant in wording their questions to elicit the "correct" answer. Duncan Murdoch dmurdoch@mast.queensu.ca
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