Reducing Undecided Voters and Other Sources of Error in Election Surveys

Abstract

The present study found the number of undecided voters on forcedchoice questions about candidate preferences was roughly three times higher than that on subjective probability questions, and that election predictions based on traditional forcedchoice scales had a higher degree of error than predictions based on subjective probability scales. The findings show that subjective probability scales can introduce error when there are more than two candidates or parties in an election, but this can be easily corrected by the procedure for adjusting subjective probability scores that was used by Hoek & Gendall (1993). While the use of adjusted probability scores improved the accuracy of predictions in multicandidate races, no difference was found in the accuracy of predictions based on adjusted and unadjusted probabilities in elections with only two candidates.