Two-Method planned missing designs for longitudinal research

Mauricio Garnier-Villarreal*, Mijke Rhemtulla, Todd D. Little

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review


We examine longitudinal extensions of the two-Method measurement design, which uses planned missingness to optimize cost-efficiency and validity of hard-to-Measure constructs. These designs use a combination of two measures: a "gold standard" that is highly valid but expensive to administer, and an inexpensive (e.g., survey-based) measure that contains systematic measurement bias (e.g., response bias). Using simulated data on four measurement occasions, we compared the cost-efficiency and validity of longitudinal designs where the gold standard is measured at one or more measurement occasions. We manipulated the nature of the response bias over time (constant, increasing, fluctuating), the factorial structure of the response bias over time, and the constraints placed on the latent variable model. Our results showed that parameter bias is lowest when the gold standard is measured on at least two occasions. When a multifactorial structure was used to model response bias over time, it is necessary to have the "gold standard" measures included at every time point, in which case most of the parameters showed low bias. Almost all parameters in all conditions displayed high relative efficiency, suggesting that the 2-Method design is an effective way to reduce costs and improve both power and accuracy in longitudinal research.

Original languageEnglish
Pages (from-to)411-422
Number of pages12
JournalInternational Journal of Behavioral Development
Issue number5
Publication statusPublished - Sept 2014
Externally publishedYes


  • Intentionally missing data
  • Missing data
  • Planned missingness
  • Simsem
  • Structural equation modeling
  • Two-Method measurement


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