Comparison of Linear Regression Methods When Both Variables Contain Error: Relation to Clinical Studies
Explore this paper's citation graph
Summary
It is suggested that linear regression by the traditional method of y upon x is appropriate in the majority of clinical situations, but when n is large and errors in x are much larger than those in y, orthogonal regression or the averaging method may be preferable.
- Type
- article
- Published
- 1989-11-01
- Cited by
- 5
- References
- 16
- OpenAlex
- https://openalex.org/W2287795324
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:11303485
Keywords
Homoscedasticity, Linear regression, Mathematics, Heteroscedasticity, Statistics
References
- In Reply: Positive Interference with Immunoassay of Theophylline in Serum of Uremics
- Analyzing research data: The basics of biomedical research methodology
- Amikacin serum concentrations: prediction of levels and dosage guidelines.
- Applied Regression Analysis and Other Multivariate Methods
- Effect of erythromycin on theophylline kinetics.
- A Study of the Powers of Several Methods of Multiple Comparisons
- Plasma protein binding of phenytoin in the aged: in vivo studies.
- Fitting straight lines when both variables are subject to error.
- Orthogonal least squares.
- Significance tests for multiple comparison of proportions, variances, and other statistics.
- Stepwise Multiple Comparison Procedures
- Positive interference with immunoassay of theophylline in serum of uremics.
- Applied regression analysis and other multivariable methods