Hi Shelley,
I think you have entered the "realm" of determining best ways to handle missing data.
If you are treating the data as though it were a simple random sample, you could
1) create a category consisting of the "non-responders" and include them in your analysis
2) assume that data are missing completely at random and ignore the non-response.
If the you did have variability in your (non-missing) responses you could
3) attempt an imputation method to estimate the missing data
OR
if you were dealing with a complex survey sample, you could get proportions using sampling weights that have been adjusted for non-response.
Happy to discuss further via Skype if you wish.
Best regards,
Novie
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------Original Message------
I would appreciate getting feedback on what would be the most appropriate way to report survey results with non-responders.
For example if one question in a multi-question survey asked:
Would you be willing to replace your current product with the evaluation product?
"Yes" and "No" were the only options.
72 forms were received back: 4 had no response to that question and the other 68 responded "Yes"
Would statistician recommend to report results as:
100% of those responding said "Yes"
or
94% of evaluators said "Yes"
or
something else?
Thanks!
(looking for a good solution to an ongoing debate with marketing...I cannot generate new data as a solution)
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Shelley-Ann Walters
3M
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