How Errors Cumulate: Two Examples

Abstract

Abstract This article examines the relationship among different types of nonobservation errors (all of which affect estimates from nonprobability internet samples) and between nonresponse and measurement errors. Both are examples of how different error sources can interact. Estimates from nonprobability samples seem to have more total error than estimates from probability samples, even ones with very low response rates. This finding suggests that the combination of coverage, selection, and nonresponse errors has greater cumulative effects than nonresponse error alone. The probabilities of having internet access, joining an internet panel, and responding to a particular survey request are probably correlated and, as a result, may lead to greater covariances with survey variables than response propensities alone; the biases accentuate one another. With nonresponse and measurement error, the two sources seem more or less uncorrelated, with one exception—those most prone to social desirability bias (those in the undesirable categories) are also less likely to respond. In addition, the propensity for unit nonresponse seems to be related to item nonresponse.