ロード中...
COVARIATE DECOMPOSITION METHODS FOR LONGITUDINAL MISSING-AT-RANDOM DATA AND PREDICTORS ASSOCIATED WITH SUBJECT-SPECIFIC EFFECTS
Investigators often gather longitudinal data to assess changes in responses over time within subjects and to relate these changes to within-subject changes in predictors. Missing data are common in such studies and predictors can be correlated with subject-specific effects. Maximum likelihood method...
保存先:
| 出版年: | Aust N Z J Stat |
|---|---|
| 主要な著者: | , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
2014
|
| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4456042/ https://ncbi.nlm.nih.gov/pubmed/26052246 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1111/anzs.12093 |
| タグ: |
タグ追加
タグなし, このレコードへの初めてのタグを付けませんか!
|