Planned missing data designs in psychological research.

Abstract

The authors describe 2 efficiency (planned missing data) designs for measurement: the 3-form design and the 2-method measurement design. The 3-form design, a kind of matrix sampling, allows researchers to leverage limited resources to collect data for 33% more survey questions than can be answered by any 1 respondent. Power tables for estimating correlation effects illustrate the benefit of this design. The 2-method measurement design involves a relatively cheap, less valid measure of a construct and an expensive, more valid measure of the same construct. The cost effectiveness of this design stems from the fact that few cases have both measures, and many cases have just the cheap measure. With 3 brief simulations involving structural equation models, the authors show that compared with the same-cost complete cases design, a 2-method measurement design yields lower standard errors and a higher effective sample size for testing important study parameters. With a large cost differential between cheap and expensive measures and small effect sizes, the benefits of the design can be enormous. Strategies for using these 2 designs are suggested.

Sex-Related Online Behaviors and Adolescents’ Body and Sexual Self-Perceptions

“…Remaining items in the scale were imputed. 33,34 After each completed questionnaire adolescents received a book voucher This study was approved by the ethics board of the Faculty of Social and Behavioral Sciences of Utrecht University, Netherlands.…”

No le tema a los datos perdidos: enfoques modernos para el manejo de datos perdidos

“…Existen diferentes diseños de datos perdidos (ver Graham, 2006) que pueden ser utilizados en la medición en psicología y educación, no obstante el objetivo del presente artículo es describir las principales características de los protocolos multi formulario y el diseño de datos perdidos para dos medidas.…”

“…La principal ventaja de este diseño es la posibilidad de obtener un modelo con mayor poder estadístico, que si implementáramos solamente la medida costosa, así mismo garantiza mayor validez de constructo en comparación a un estudio que solo incluyera la medida menos costosa. Esto es así, debido a que la medida más costosa y confiable puede ser usada para modelar el sesgo asociado con la medida menos costosa, afirmación que encuentra respaldo en estudios de simulación previos donde se ha hallado que este diseño produce errores estándar reducidos y cantidades de muestra altamente efectivos para someter a prueba los parámetros del estudio (Graham, 2006).…”

“…Asimismo, los datos perdidos no son más un problema que debe ser prevenido, ya que es posible utilizar diseños que contemplen perder datos de manera deliberada en aras de economizar tiempo y dinero sin arriesgar en gran medida el poder estadístico (Graham, 2006;Rhemtulla & Little, 2012). Así, es factible abarcar muestras numerosas con instrumentos extensos sin agotar las energías y recursos cognitivos de los y las participantes .…”

Methods for testing theory and evaluating impact in randomized field trials: Intent-to-treat analyses for integrating the perspectives of person, place, and time

“…Multiple imputation forms a set of complete datasets based on an imputation model, then uses an analytic model to assess intervention effects on each of the completed datasets. The imputation model used to replace the missing data should always be at least as complex as the analytic model used to examine intervention impact (Collins et al, 2001;Graham et al, 2006Graham et al, , 2007Schafer, 1997Schafer, , 1999Schafer and Graham, 2002).…”