Logistic regression models for binary response problems are present in a wide variety of industrial, biological, social and medical experiments; therefore, optimum designs are a valuable tool for experimenters, leading to estimators of parameters with minimum variance. Our interest in this contribution is to provide explicit formulae for the D-optimal designs as a function of the unknown parameters for the logistic model where q is an indicator variable. We have considered an experiment based on the dose-response to a fly insecticide in which males and females respond in different ways, proposed in Atkinson et al. (1995) . To find the D-optimal designs, this problem has been reduced to a canonical form.
 Silvey, S.D. (1980) Optimal Design. Chapman and Hall, London.
 Ford, I., Tosney, B. and Wu, C.F.J. (1992) The Use of a Canonical form in the Construction of Locally Optimal Designs for Non-Linear Problems. Journal of the Royal Statistical Society: Series B, 54, 569-583.
 Ardanuy, R., Lopez-Fidalgo, J., Laycock, P.J. and Wong, W.K. (1999) When Is an Equally-Weihted Design D-Optimal? Annals of the Institute of Statistical Mathematics, 51, 531-540.
 Chernoff, H. (1953) Locally Optimal Designs for Estimating Parameters. The Annals of Mathematical Statistics, 24, 586-602. http://dx.doi.org/10.1214/aoms/1177728915
 Chaloner, K. and Larntz, K. (1989) Optimal Bayesian Design Applied to Logistic Regression Experiments. Journal of Statistical Planning and Inference, 21, 191-208.
 Silvey, S.D. and Titterington, D.M. (1973) A Geometrical Approach to Optimal Design Theory. Biometrika, 60, 21-32.
 Torsney, B. and Musrati, A.K. (1993) On the Construction of Optimal Designs with Applications to Binary Response and to Weighted Regression Models. Model Oriented Data Analysis, Physica-Verlag, Heidelberg.