A novel item-allocation procedure for the three-form planned missing data design

We propose a new method of constructing questionnaire forms in the three-form planned missing data design (PMDD). The random item allocation (RIA) procedure that we propose promises to dramatically simplify the process of implementing three-form PMDDs without compromising statistical performance. Ou...

Full description

Bibliographic Details
Main Authors: Kyle M. Lang, E. Whitney G. Moore, Elizabeth M. Grandfield
Format: Article
Language:English
Published: Elsevier 2020-01-01
Series:MethodsX
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2215016120301618
Description
Summary:We propose a new method of constructing questionnaire forms in the three-form planned missing data design (PMDD). The random item allocation (RIA) procedure that we propose promises to dramatically simplify the process of implementing three-form PMDDs without compromising statistical performance. Our method is a stochastic approximation to the currently recommended approach of deterministically spreading a scale's items across the X-, A-, B-, and C-blocks when allocating the items in a three-form design. Direct empirical support for the performance of our method is only available for scales containing at least 12 items, so we also propose a modified approach for use with scales containing fewer than 12 items. We also discuss the limitations of our procedure and several nuances for researchers to consider when implementing three-form PMDDs using our method.● The RIA procedure allows researchers to implement statistically sound three-form planned missing data designs without the need for expert knowledge or results from prior statistical modeling.● The RIA procedure can be used to construct both “paper-and-pencil” questionnaires and questionnaires administered through online survey software.● The RIA procedure is a simple framework to aid in designing three-form PMDDs; implementing the RIA method does not require any specialized software or technical expertise.
ISSN:2215-0161