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Physical Sciences and Mathematics Commons™
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- Matrix sampling questionnaires (1)
- Missing data analysis; missingness mechanisms; planned missing design; multiple imputation; full information maximum likelihood (1)
- Planned missing data (1)
- Planned missing designs; simulation; full information maximum likelihood (FIML); multiple imputation (MI); 3-form survey (1)
- Survey design (1)
Articles 1 - 4 of 4
Full-Text Articles in Physical Sciences and Mathematics
A Novel Item-Allocation Procedure For The Three-Form Planned Missing Data Design, Kyle M. Lang, E. Whitney G. Moore, Elizabeth M. Grandfield
A Novel Item-Allocation Procedure For The Three-Form Planned Missing Data Design, Kyle M. Lang, E. Whitney G. Moore, Elizabeth M. Grandfield
Kinesiology, Health and Sport Studies
We propose a new method of constructing questionnaire forms in the three-form planned missing data design (PMDD). The random item allocation (RIA) procedure that we propose promises to dramatically simplify the process of implementing three-form PMDDs without compromising statistical performance. Our method is a stochastic approximation to the currently recommended approach of deterministically spreading a scale's items across the X-, A-, B-, and C-blocks when allocating the items in a three-form design. Direct empirical support for the performance of our method is only available for scales containing at least 12 items, so we also propose a modified approach for use …
On The Joys Of Missing Data, Todd D. Little, Terrence D. Jorgensen, Kyle M. Lang, E. Whitney G. Moore
On The Joys Of Missing Data, Todd D. Little, Terrence D. Jorgensen, Kyle M. Lang, E. Whitney G. Moore
Kinesiology, Health and Sport Studies
We provide conceptual introductions to missingness mechanisms—missing completely at random (MCAR), missing at random (MAR), and missing not at random (MNAR)—and state-of-the-art methods of handling missing data—full-information maximum likelihood (FIML) and multiple imputation (MI)—followed by a discussion of planned missing designs: multiform questionnaire protocols, two-method measurement models, and wave-missing longitudinal designs. We reviewed 80 articles of empirical studies published in the 2012 issues of the Journal of Pediatric Psychology to present a picture of how adequately missing data are currently handled in this field. To illustrate the benefits of utilizing MI or FIML and incorporating planned missingness into study designs, …
Planned Missing Data Designs & Small Sample Size: How Small Is Too Small?, Fan Jia, E. Whitney G. Moore, Richard Kinai, Kelly S. Crowe, Alexander M. Schoemann, Todd D. Little
Planned Missing Data Designs & Small Sample Size: How Small Is Too Small?, Fan Jia, E. Whitney G. Moore, Richard Kinai, Kelly S. Crowe, Alexander M. Schoemann, Todd D. Little
Kinesiology, Health and Sport Studies
Utilizing planned missing data (PMD) designs (ex. 3-form surveys) enables researchers to ask participants fewer questions during the data collection process. An important question, however, is just how few participants are needed to effectively employ planned missing data designs in research studies. This paper explores this question by using simulated three-form planned missing data to assess analytic model convergence, parameter estimate bias, standard error bias, mean squared error (MSE), and relative efficiency (RE).Three models were examined: a one-time point, cross-sectional model with 3 constructs; a two-time point model with 3 constructs at each time point; and a three-time point, mediation …
Planned Missingness Study Design: Two Methods To Developing The Study Survey Versions, E. Whitney G. Moore
Planned Missingness Study Design: Two Methods To Developing The Study Survey Versions, E. Whitney G. Moore
Kinesiology, Health and Sport Studies
A planned missingness data study design takes advantage of modern techniques for handling data missingness that is MCAR (Missing Completely at Random) and MAR (Missing at Random) (Brown, 2006; Enders, 2010). As modern data imputation techniques have improved, this study design option has become a powerful, cost-effective option for collecting the most data across the largest sample possible, while keeping the fatigue effect and expense of the study minimized (Little, 2010a, 2010b, 2012). The purpose of this guide is to provide an applied example for designing the surveys necessary when conducting a planned missingness research study design.