ABSTRACT

Questionnaire data present challenges, as a missing item of a multi-item scale would lead to a total missing scale. A researcher applying multiple imputation to an incomplete multi-item questionnaire can impute the incomplete items prior to computing scale scores or impute the scale score entirely. Methodologist have favored item-level imputation because it greatly enhances precision in comparison to scale-level imputation; however, this benefit in precision might not translate into longitudinal data studies where entire questionnaire batteries are missing. We investigated the performance of item- and scale-level imputation model and found that item-level imputation did not produce a precision advantage in estimating any of the growth model parameters and scale-level showed better precision in estimating the slope variance parameter than item-level imputation.

摘要

问卷数据存在挑战，因为多项目量表的缺失项目将导致总缺失量表。对不完整的多项目问卷应用多重插补的研究人员可以在计算量表分数之前对不完整的项目进行插补，或者完全插补量表分数。方法论者偏爱项目级别的插补，因为与尺度级别的插补相比，它大大提高了精度；然而，这种精度的好处可能不会转化为纵向数据研究，因为缺少整个问卷组。