This paper gives an overview of the error-in-variables-model (EVM) procedure for parameter estimation with nonlinear models. It is shown that the nested-iterative EVM algorithm, used in this work, is efficient and powerful, since it provides both true values of the variables and the best estimates of the parameters. The step by step illustration along with evaluation techniques for results, are followed by further discussion about the importance and advantages of combining EVM with design of experiments strategies. With the focus on the performance of the EVM algorithm, an illustrative example of reactivity ratio estimation in copolymerization is included, with single-response (composition data) and multi-response (triad fraction data) scenarios. (c) 2012 Elsevier Ltd. All rights reserved.