Two-Method Measurement Planned Missing Data With Purposefully Selected Samples

Area of Science:

• Educational research methodology
• Statistical modeling
• Psychometrics

Background:

• Planned missing data designs are increasingly used in education research.
• Traditional methods rely on missing completely at random (MCAR) data.
• Existing designs may not fully leverage targeted assessment strategies.

Purpose of the Study:

• To evaluate the feasibility of planned missingness designs based on student performance.
• To introduce and test a purposeful missingness method.
• To compare its performance against the MCAR mechanism.

Main Methods:

• A Monte Carlo simulation study was conducted.
• The purposeful missingness method was implemented within a two-method measurement design.
• Parameter recovery was assessed across various conditions.

Main Results:

• The purposeful missingness method demonstrated comparable accuracy to the MCAR method in recovering parameter estimates.
• Performance was consistent across multiple simulated conditions.
• This approach allows for focused assessment efforts on a target sample.

Conclusions:

• Purposeful missingness is a viable alternative to MCAR in planned missing data designs.
• This method can maintain statistical power while optimizing assessment resources.
• It offers a flexible approach for applied education research.