Error-in-variables model, EVM

The next step in the protocol answers the question about what is the best method to estimate the reactivity ratios. Historically, because of its simplicity, linearization techniques such as the Fineman-Ross, Kelen-Tudos, and extended Kelen-Tudos methods have been used. Easily performed on a simple calculator, these techniques suffer from inaccuracies due to the linearization of the inherently nonlinear Mayo-Lewis model. Such techniques violate basic assumptions of linear regression and have been repeatedly shown to be invalid [117, 119, 126]. Nonlinear least squares (NLLS) techniques and other more advanced nonlinear techniques such as the error-in-variables-model (EVM) method have been readily available for several decades [119, 120, 126, 127]. 

Brar and Sunita [184] have reported the reactivity ratios (r) for the acrylonitrile]A)-methyl acrylate (M) monomer pair using the errors in variables model (EVM) [185, 186] with the use of a computer program written by O Driscoll and co-workers [187]. The primary structure factors monomer composition, diad/triad sequence distribution, conditional probabilities, and number-average sequence lengths of acrylonitrile-methyl acrylate copolymers were determined on the basis of C H -NMR analyses and compared with those calculated from reactivity ratios as determined from EVM program. The diad sequence calculated from C H)-NMR (proton decoupled C-NMR) spectra was correlated with the Tg of A/M copolymers. 

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