Regardless of how perfectly a screener or questionnaire is designed, or how perfectly the recruiting was done, almost every research study will have one respondent, or maybe even a few, who don't belong in the sample. These people may have lied when they answered the screener questions or maybe even guessed correctly even though they knew their answers were bogus. That's a fact of research and it happens in almost every study. That's cool. Some people like to sneak into things so they can get paid, but there is a way to weed these people out of the sample.
If a respondent varies too much from the rest of the sample, the person is eliminated. You can compute the score yourself on a spreadsheet.
Here are the steps to do it:
Here are the steps:
1) Calculate the standard deviation for each respondent's answers.
2) Calculate z-scores for all the respondents' standard deviation scores.
3) Eliminate any respondent whose standard deviation z-score is greater than ±1.5. A person with a z-score that high does not belong in the sample.
Is there a way to automate such process with LimeSurvey and somehow highlight such respondents?
