Measuring Creativity with Planned Missing Data

2020 ◽  
Vol 54 (1) ◽  
pp. 150-164 ◽  
Author(s):  
Guillaume Fürst
Keyword(s):  
Missing Data ◽  
Planned Missing Data ◽  
Planned Missing

Planned missing data designs in psychological research.

2006 ◽  
Vol 11 (4) ◽  
pp. 323-343 ◽  
Author(s):  
John W. Graham ◽  
Bonnie J. Taylor ◽  
Allison E. Olchowski ◽  
Patricio E. Cumsille
Keyword(s):  
Missing Data ◽  
Psychological Research ◽  
Planned Missing Data ◽  
Planned Missing

scholarly journals Reflection on modern methods: planned missing data designs for epidemiological research

2020 ◽  
Vol 49 (5) ◽  
pp. 1702-1711 ◽  
Author(s):  
Charlie Rioux ◽  
Antoine Lewin ◽  
Omolola A Odejimi ◽  
Todd D Little
Keyword(s):  
Missing Data ◽  
Gold Standard ◽  
Epidemiological Research ◽  
Missing Data Treatments ◽  
Planned Missing Data ◽  
Missing Completely At Random ◽  
Modern Methods ◽  
Missing Items ◽  
Data Design ◽  
Planned Missing

Abstract Taking advantage of the ability of modern missing data treatments in epidemiological research (e.g. multiple imputation) to recover power while avoiding bias in the presence of data that is missing completely at random, planned missing data designs allow researchers to deliberately incorporate missing data into a research design. A planned missing data design may be done by randomly assigning participants to have missing items in a questionnaire (multiform design) or missing occasions of measurement in a longitudinal study (wave-missing design), or by administering an expensive gold-standard measure to a random subset of participants while the whole sample is administered a cheaper measure (two-method design). Although not common in epidemiology, these designs have been recommended for decades by methodologists for their benefits—notably that data collection costs are minimized and participant burden is reduced, which can increase validity. This paper describes the multiform, wave-missing and two-method designs, including their benefits, their impact on bias and power, and other factors that must be taken into consideration when implementing them in an epidemiological study design.

Planned Missing Data Designs for Developmental Researchers

2013 ◽  
Vol 7 (4) ◽  
pp. 199-204 ◽  
Author(s):  
Todd D. Little ◽  
Mijke Rhemtulla
Keyword(s):  
Missing Data ◽  
Planned Missing Data ◽  
Planned Missing
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