Abstract
In medical research, while carrying out regression analysis, it is usually assumed that the independent (covariates) and dependent (response) variables follow a multivariate normal distribution. In some situations, the covariates may not have normal distribution and instead may have some symmetric distribution. In such a situation, the estimation of the regression parameters using Tiku's Modified Maximum Likelihood (MML) method may be more appropriate. The method of estimating the parameters is discussed and the applications of the method are illustrated using real sets of data from the field of public health.
Original language | English |
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Pages (from-to) | 446-462 |
Number of pages | 17 |
Journal | Journal of Modern Applied Statistical Methods |
Volume | 13 |
Issue number | 1 |
DOIs | |
Publication status | Published - 2014 |
Keywords
- Delta method
- Maximum likelihood
- Modified maximum likelihood
- Order statistics
- Student's tdistribution
ASJC Scopus subject areas
- Statistics and Probability
- Statistics, Probability and Uncertainty