Should I test more babies? Solutions for transparent data peeking

Area of Science:

• Developmental Psychology
• Infant Research Methodology

Background:

• Infant research is time-intensive, creating pressure for efficient participant use.
• Data peeking, or optional stopping, is a strategy used to optimize study efficiency.
• However, data peeking can increase false positive rates, potentially compromising research integrity.

Purpose of the Study:

• To explore methods for harnessing the benefits of data peeking in infant research.
• To address the negative consequences of data peeking, such as increased false positives.
• To propose simple, implementable corrections for efficient and reliable infant study designs.

Main Methods:

• Review of existing data peeking strategies in developmental research.
• Introduction of two transparently reportable corrections for data peeking.
• Discussion of the applicability of these corrections within current infant research frameworks.

Main Results:

• Data peeking can be effectively utilized in infant research with appropriate corrections.
• Two corrections are presented: one for pre-study planning and one for ongoing data collection.
• These corrections are easily integrated into existing research practices.

Conclusions:

• Implementing simple corrections with data peeking enhances participant efficiency in infant studies.
• Transparent reporting of these corrections improves the replicability of infant research findings.
• This approach balances efficiency gains with the need for statistical rigor and reliable results.