Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
This paper describes a low variance simulator of the normal distribution function. The probability integral is evaluated exactly at an initial point specified with a factor analytic covariance structure, so that the integral can be derived using dimension reduction techniques. The line integral between the initial point and the desired point is evaluated using Plackett's identity. A Monte Carlo simulation of this line integral simulator (LIS) with the Geweke-Hajivassiliou-Keane (GHK) simulator demonstrates that for dimensions of ten or less, the LIS outperformed the GHK simulator, typically by an order of magnitude and in some cases by two orders of magnitude. Copyright 1994 by MIT Press.