||Using Linear and Polynomial Models to Examine the Environmental Stability of Viruses (Chapter 7).
Hurst, C. J. ;
||Environmental Protection Agency, Cincinnati, OH. Risk Reduction Engineering Lab. ;American Society for Microbiology, Washington, DC.
Statistical models ;
Regression analysis ;
Water microbiology ;
Soil microbiology ;
Waste water ;
Soil water ;
Soil chemistry ;
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The article presents the development of model equations for describing the fate of viral infectivity in environmental samples. Most of the models were based upon the use of a two-step linear regression approach. The first step employs regression of log base 10 transformed viral titer ratios from various sampling dates as the dependent variable versus the length of time that the viruses were incubated in the test material as the independent variable. The slope values derived from this first step of the regression technique are then used as the dependent variable in the second step of the analysis, when they are linearly regressed against either a single independent variable such as soil moisture level or incubation temperature, or against a set of independent variables in a multiple regression. A variety of examples based upon experimental data were used to demonstrate the application and benefits of this two-step regression technique.