Tools of the Trade: Planned Missing Data Designs for Research in Cognitive Development

Area of Science:

• Developmental Psychology
• Research Methodology

Background:

• Data collection is a significant bottleneck in developmental research, often demanding substantial time and financial resources.
• Traditional research designs may not optimally balance data quality with research efficiency.

Purpose of the Study:

• To introduce and explain planned missing data designs for maximizing data quality (reliability and validity) while minimizing research costs.
• To illustrate the application of these designs in cognitive development research.

Main Methods:

• Description of planned missing data designs, including multi-form designs and two-method measurement designs.
• Strategic use of missing data to increase the number of assessed measures without increasing participant burden.
• Leveraging cost-effective measures alongside gold-standard measures to expand sample sizes.

Main Results:

• Planned missing data designs offer an efficient approach to manage research costs.
• These designs have the potential to improve data quality, reduce participant fatigue, and mitigate practice effects.
• Strategic data collection can enhance the validity of developmental research findings.

Conclusions:

• Planned missing data designs are underutilized but effective strategies for efficient and high-quality developmental research.
• Implementation with appropriate analysis methods yields unbiased results and optimizes resource allocation.
• These designs represent a valuable tool for researchers aiming to improve data collection efficiency and participant experience.