ERIC Number: EJ1039724
Record Type: Journal
Publication Date: 2014-Sep
Abstractor: As Provided
Reference Count: 32
Planned Missing Data Designs with Small Sample Sizes: How Small Is Too Small?
Jia, Fan; Moore, E. Whitney G.; Kinai, Richard; Crowe, Kelly S.; Schoemann, Alexander M.; Little, Todd D.
International Journal of Behavioral Development, v38 n5 p435-452 Sep 2014
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 article 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 model with 3 constructs over three time points. Both full-information maximum likelihood (FIML) and multiple imputation (MI) were used to handle the missing data. Models were found to meet convergence rate and acceptable bias criteria with FIML at smaller sample sizes than with MI.
Descriptors: Data Analysis, Statistical Inference, Error of Measurement, Computation, Multivariate Analysis, Research Problems, Maximum Likelihood Statistics, Simulation, Statistical Bias, Models, Sample Size, Factor Analysis
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Sponsor: National Science Foundation
Authoring Institution: N/A
Grant or Contract Numbers: NSF 1053160