This paper echoes the familiar warning that additive measurement error and multicollinearity in the explanatory variables can mislead investigators in multiple Poisson regression analysis. Often, a causal variable measured with error may be overlooked and its signiยฎcance transferred to another covar
Robust, locally stable, measurement error regression methods
โ Scribed by Tapon Roy
- Publisher
- John Wiley and Sons
- Year
- 1997
- Tongue
- English
- Weight
- 280 KB
- Volume
- 11
- Category
- Article
- ISSN
- 0886-9383
No coin nor oath required. For personal study only.
โฆ Synopsis
Robust, equivariant, locally stable, measurement error (ME) techniques for estimating parameters in regression models are developed and compared with other robust methods which do not combine high resistance with local stability. Examples from physical chemistry and astronomy are used to illustrate the techniques.
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In medical research, a situation commonly arises where new variables are calculated from a common set of directly measured variables. When the directly measured variables each contain an error component, the relationship between the observed calculated variables can often be distorted. A source of t