Issue № 1 |
Analytical review |
pdf-version |
Varaksin Anatoly | Dr.Sc., Institute of Industrial Ecology, S.Kovalevskaya St, 20-A, Ekaterinburg, varaksin@ecko.uran.ru |
Shalaumova Julia | Ph. D., Institute of Industrial Ecology, S.Kovalevskaya St, 20-A, Ekaterinburg, yulyash@gmail.com |
Panov Vladimir | Ph.D., Institute of Industrial Ecology, S.Kovalevskaya St, 20-A, Ekaterinburg, vpanov@ecko.uran.ru |
Keywords: confounding variables accounting confounders standardization risk factor analysis of observational data regression models |
Summary: The methods of the analysis of research data including the concomitant variables (confounders) associated with both the response and the current factor are considered. There are two usual ways to take into account such variables: the first, at the stage of planning the experiment and the second, in analyzing the received data. Despite the equal effectiveness of these approaches, there exists strong reason to restrict the usage of regression method to accounting for confounders by ANCOVA. Authors consider the standardization by stratification as a reliable method to account for the effect of confounding factors as opposed to the widely-implemented application of logistic regression and the covariance analysis. The program for the automation of standardization procedure is proposed, it is available at the site of the Institute of Industrial Ecology. © Petrozavodsk State University |
Received on: 21 April 2014 Published on: 17 December 2014 |