Planned missingness to reduce survey length: A sheep in wolf's clothing

Psychologists often have the need to reduce the length of a survey study to ensure data quality, meet practical constraints, or conserve participant resources. The present study explores a survey technique called planned missingness (PM) as an approach to reducing study length. We conducted a Monte Carlo simulation that directly compared using a PM design to the standard practice of using short forms of measures on their ability to reproduce true population intercorrelations. We manipulated a number of population and study characteristics, including the number of constructs, missingness level, sample size, true intercorrelations, as well as the manner in which short forms are developed, and their impact on the short form-planned missingness comparison. Results show that the two approaches perform comparably across a large number of conditions. Under simulated, idealized data conditions and using correctly specified models, short forms produce slightly more accurate estimates when empirically developed short forms are readily available for use. PM produces slightly more accurate estimates when short forms are developed not entirely empirically. However, discrepancies are small in general. Additional advantages and limitations of PM are discussed. (PsycInfo Database Record (c) 2026 APA, all rights reserved).