| Literature DB >> 23712802 |
Ofer Harel1, Hwan Chung, Diana Miglioretti.
Abstract
Latent class regression (LCR) is a popular method for analyzing multiple categorical outcomes. While nonresponse to the manifest items is a common complication, inferences of LCR can be evaluated using maximum likelihood, multiple imputation, and two-stage multiple imputation. Under similar missing data assumptions, the estimates and variances from all three procedures are quite close. However, multiple imputation and two-stage multiple imputation can provide additional information: estimates for the rates of missing information. The methodology is illustrated using an example from a study on racial and ethnic disparities in breast cancer severity.Entities:
Keywords: Latent class regression; Missing data; Missing information; Multiple imputation
Mesh:
Year: 2013 PMID: 23712802 PMCID: PMC3791520 DOI: 10.1002/bimj.201200020
Source DB: PubMed Journal: Biom J ISSN: 0323-3847 Impact factor: 2.207