Abstract
The consequences of the misspecification of a regression model are considered. For small effects of covariates a proportional consistency theorem is derived. The consistent estimation of the covariance matrix of the estimates is discussed.
| Original language | English |
|---|---|
| Pages (from-to) | 141-145 |
| Number of pages | 5 |
| Journal | Biometrical Journal |
| Volume | 29 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 1987 |
| Externally published | Yes |
Keywords
- Consistency
- Covariance matrix
- Linear combination of covariates
- Maximum likelihood
- Misspecification of model
ASJC Scopus subject areas
- Statistics and Probability
- Statistics, Probability and Uncertainty