Reduction of Survey Length through Split Questionnaire Design: Consequences for Nonresponse and Measurement Error

社会科学的许多研究和政府政策的制定都依赖于调查数据，对调查数据的需求也在不断增长。对更多数据的需求导致调查时间更长，增加了调查对象在时间和精力方面的负担。实证表明，调查时长与调查不响应之间存在正相关关系，这对调查估计的代表性构成了威胁。也有证据表明，随着受访者在调查中被要求回答更多问题，测量（报告）误差也会增加。然而，收集较少的变量可能无法满足给定研究的目标。这个研究项目通过实验评估收集所有所需数据的能力，通过一个分裂的问卷设计，其中受访者被要求只有一个子集的问题。该项目将使用多重输入方法来完成未要求特定受访者填写的部分的数据。研究人员将扩展目前的imputation方法，包括半参数和参数模型。主要假设是，与部署完整问卷相比，分裂问卷设计方法将产生更少偏差的估计，甚至更少的总误差。这个项目评估了一种方法，基本上转移了部分时间和精力来完成调查，从个人到研究人员。它还评估了由于减少应答者负担而收集更高质量数据的能力。最后，本研究旨在扩展所采用的统计方法，以更好地保留数据的属性。其结果将有助于为广泛的调查提供一种替代方法，改进分裂问题单设计方法本身，并提供关于在何种情况下实施这种设计可能有益的信息。

Much research in the social sciences and development of government policy relies on survey data, and the demand for survey data continues to grow. The need for more data has led to longer surveys, increasing the burden for survey respondents in terms of time and effort. Empirical evidence shows a positive correlation between survey length and survey nonresponse, which threatens the representativeness of the survey estimates. There also is evidence that measurement (reporting) error increases as respondents are asked to answer more questions in the survey. Collecting fewer variables may not satisfy a given study's objectives, however. This research project experimentally evaluates the ability to collect all desired data through a split questionnaire design in which respondents are asked only a subset of the questions. The project will use a multiple imputation method to complete the data in the sections that are not asked of particular respondents. The investigators' will extend current imputation methods to include semi-parametric and parametric models. The main hypothesis is that the split questionnaire design approach will yield estimates with less bias and even less total error compared to deploying the full questionnaire.This project evaluates a method that essentially transfers part of the time and effort to complete the survey from the individual to the researcher. It also evaluates the ability to collect higher quality data as a result of this reduction in respondent burden. Finally, the study aims to extend the employed statistical methods to better preserve the properties of the data. The results will help to provide an alternative methodology for a wide array of surveys, improve split questionnaire design methodology itself, and provide information regarding the circumstances under which implementing such designs can be beneficial.