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

Kyle M Lang1, E Whitney G Moore2, Elizabeth M Grandfield3

  • 1Tilburg University Department of Methodology and Statistics, the Netherlands.

Methodsx
|July 9, 2020
PubMed
Summary
This summary is machine-generated.

We introduce the random item allocation (RIA) procedure for simplified construction of three-form planned missing data designs (PMDDs). This method ensures statistical validity without requiring expert statistical knowledge or complex software for implementation.

Keywords:
Matrix samplingPlanned missing dataQuestionnairesSurvey design

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Area of Science:

  • Statistics
  • Survey Methodology
  • Psychometrics

Background:

  • Planned missing data designs (PMDDs) are valuable for efficient data collection in surveys.
  • Implementing three-form PMDDs traditionally requires complex item allocation strategies.

Purpose of the Study:

  • To propose a simplified method for constructing three-form PMDDs.
  • To introduce the random item allocation (RIA) procedure for easier implementation.

Main Methods:

  • The proposed random item allocation (RIA) procedure offers a stochastic approximation to deterministic item spreading.
  • A modified approach is suggested for scales with fewer than 12 items.

Main Results:

  • The RIA procedure simplifies the implementation of three-form PMDDs.
  • It does not compromise statistical performance compared to existing methods.
  • Empirical support is available for scales with 12 or more items.

Conclusions:

  • The RIA procedure enables statistically sound three-form PMDDs without expert statistical knowledge.
  • It is adaptable for both paper-and-pencil and online survey formats.
  • The method is a user-friendly framework for designing three-form PMDDs.