Factors that influence reading and comprehension of branching instructions in self–administered questionnaires

Summary: In this paper we examine the tendency for branching instructions to be ignored, misread, or otherwise not appropriately followed so that item nonresponse occurs for follow–up questions. The potential influence on branching errors of seven features of question complexity are examined, including high number of question words, high number of answer categories, last categories branch, all categories branch, write–in responses, location at the bottom of a page, and high distance between the answer box and branching instruction. A logistic regression analysis revealed that question complexity had a tendency to increase certain errors, but not others.* A more detailed version of this paper with additional analysis and discussion is available at http://www.sesrc.wsu.edu/dillman/. The opinions expressed here are those of the authors, not necessarily of the institutions where they presently work or the U.S. Census Bureau, which provided financial support for the collection of these data. We would like to thank Aref Dajani and Yves Thibaudeau for their advice on the analysis used in this paper.     

The Distribution of Sums of Rounded Percentages

When percentages are computed for counts in several categories or for several positive measurements0 each taken as a fraction of their sum, the rounded percentages often fail to add to 100 percent. We investigate how frequently this failure occurs and what the distributions of sums of rounded percentages are for (1) an empirical set of data, (2) the multinomial distribution in small samples, (3) spacings between points dropped on an interval-the broken-stick model-; and (4) for simulation for several categories. The several methods produce similar distributions.We find that the probability that the sum of rounded percentages adds to exactly 100 percent is certain for two categories, about three-fourths for three categories, about two-thirds for four categories, and about [Formula: see text] for larger numbers of categories, c, on the average when categories are not improbable.