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Latent class regression: Inference and estimation with two-stage multiple imputation
- Harel, Ofer;
- Chung, Hwan;
- Miglioretti, Diana
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10초록
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.
키워드
Latent class regression; Missing data; Missing information; Multiple imputation; CLASS MODELS
- 제목
- Latent class regression: Inference and estimation with two-stage multiple imputation
- 저자
- Harel, Ofer; Chung, Hwan; Miglioretti, Diana
- 발행일
- 2013-07
- 유형
- Article
- 권
- 55
- 호
- 4
- 페이지
- 541 ~ 553