Monte Carlo simulations using extant data to mimic populations: Applications to the modified linear probability model and logistic regression.

Monte Carlo simulations are widely used in the social sciences to explore the viability of analytic methods in the face of assumption violations. Simulation results, however, may not be applicable to substantive research applications because they often are conducted under idealized rather than realistic conditions. Shortcomings of simulation design are discussed using linear equations as a case study, focusing on (a) variable distributions, (b)...