Item Sum: A New Technique for Asking Quantitative Sensitive Questions

Abstract

This article contributes to an ongoing debate about how to measure sensitive topics in population surveys. We propose a novel technique that can be applied to the measurement of quantitative sensitive variables: the item sum technique (IST). This method is closely related to the item count technique (ICT), which was developed for the measurement of dichotomous sensitive items. First, we provide a description of our new technique and discuss how data collected by the IST can be analyzed. Second, we present the results of a CATI survey on undeclared work in Germany, in which the IST has been applied. Using an experimental design, we compare the IST to direct questioning. Our empirical results indicate that the IST is a promising data collection technique for sensitive questions. We conclude the article by discussing the limitations of the new technique and outlining possible improvements for future studies.

How to ask sensitive questions in conservation: A review of specialized questioning techniques

“…how many hours they spend per month herding, 334 farming and hunting). However, because respondents in the baseline group only report the sum from 335 non-sensitive activities, the extent of the sensitive behaviour can be calculated from the mean 336 difference of answers between the two subsamples (Trappmann et al, 2014). required to report the total number of items that apply to them without identifying any individual item.…”

Item sum techniques for quantitative sensitive estimation on successive occasions

“…The decisive point in the IST is how to split the total sample in to the LL sample and SL sample. Trappmann et al (2014) allocated the same number of units to each sample irrespective of the vari-…”

“…However, Chaudhuri and Christofides (2013) proposed a generalization to ICT for estimating a quantitative sensitive variable. Trappmann et al (2014) named this technique as item sum technique (IST). Perri et al (2018) discussed the optimal sample size allocation in the IST.…”

“…Therefore, the IST difference, the IST regression and also the IST general class of estimators have been proposed in the present work to estimate a sensitive population mean in two occasion successive sampling. All these proposed estimators have been discussed under Trappmann et al (2014) allocation and Perri et al (2018) optimal allocation designs. Detail properties including optimum replacement strategies are elaborated.…”

Multiple sensitive estimation and optimal sample size allocation in the item sum technique

“…To address this situation, Chaudhuri and Christofides (2013) proposed a generalization of the ICT that can be used to estimate the mean (or the total) of a quantitative variable. Trappmann, Krumpal, Kirchner, and Jann (2014) called this variant the item sum technique (IST) and used it in a survey to estimate the amount of undeclared work in Germany. The IST works in a similar way to the ICT and offers a promising tool for dealing with sensitive issues.…”