The similarity of item and ability parameter estimations was investigated using two numerical analysis techniques via marginal maximum likelihood estimation (MMLE) with a large simulated data set (n=1,000 examinees) and changing the number of quadrature points. MMLE estimation uses a numerical analysis technique to integrate examinees' abilities over the ability distribution for item and ability parameter estimations because of the difficulty of direct integration with a digital computer. For integrating ability, the values of quadrature points and the weights corresponding to each quadrature point are specified. The Gauss-Hermite quadrature formula and R. J. Mislevy's histogram solution (1984) have been used for numerical integration over the normal density function. It was determined that the Gauss-Hermite quadrature formula and Mislevy's graphical solution via MMLE estimated item and ability parameters equally when a large number of quadrature points was specified. When a small number of quadrature points was specified, Mislevy's histogram solution via the MMLE approach estimated item and ability parameters more accurately than did the Gauss-Hermite quadrature formula. Seven tables summarize the study. (Author/SLD)