Multiple imputation is a popular method for addressing data that are presumed to be missing at random. To obtain accurate results, one's imputation model must be congenial to (appropriate for) one's ...
The National Assessment of Educational Progress (NAEP) uses latent trait item response models to summarize performance of students on assessments of educational proficiency in different subject areas ...
© CBS Missing values are a common problem in statistical analyses. Estimating such values—a problem known as imputation—can be very difficult, especially if the ...
In finance, data is often incomplete because the data is unavailable, inapplicable or unreported. Unfortunately, many classical data analysis techniques — for instance, linear regression — cannot ...
The Centre for Multilevel Modelling has a long-standing interest in developing methods and software to aid researchers in handling missing data. As discussed below, we have developed functionality in ...
Missing data are a frequently encountered problem in epidemiologic and clinical research.1, 2 One approach is to include in the analysis only those participants without missing observations (complete ...
Previous work (Carpenter and Goldstein 2004: Multilevel Modelling Newsletter 16 (2) (PDF, 298kB)) implements procedures that are based on methodological extensions that allow multivariate mixtures of ...
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