4.3 Article

A primer for biomedical scientists on how to execute Model II linear regression analysis

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出版社

WILEY
DOI: 10.1111/j.1440-1681.2011.05643.x

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ancova; Model I regression; Model IIA regression; Model IIB regression; R; sas; smatr; spss; pasw; Statistica; systat

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1. There are two very different ways of executing linear regression analysis. One is Model I, when the x-values are fixed by the experimenter. The other is Model II, in which the x-values are free to vary and are subject to error. 2. I have received numerous complaints from biomedical scientists that they have great difficulty in executing Model II linear regression analysis. This may explain the results of a Google Scholar search, which showed that the authors of articles in journals of physiology, pharmacology and biochemistry rarely use Model II regression analysis. 3. I repeat my previous arguments in favour of using least products linear regression analysis for Model II regressions. I review three methods for executing ordinary least products (OLP) and weighted least products (WLP) regression analysis: (i) scientific calculator and / or computer spreadsheet; (ii) specific purpose computer programs; and (iii) general purpose computer programs. 4. Using a scientific calculator and/ or computer spreadsheet, it is easy to obtain correct values for OLP slope and intercept, but the corresponding 95% confidence intervals (CI) are inaccurate. 5. Using specific purpose computer programs, the freeware computer program SMATR gives the correct OLP regression coefficients and obtains 95% CI by bootstrapping. In addition, SMATR can be used to compare the slopes of OLP lines. 6. When using general purpose computer programs, I recommend the commercial programs SYSTAT and Statistica for those who regularly undertake linear regression analysis and I give step-by-step instructions in the Supplementary Information as to how to use loss functions.

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