ConstructMap produces Wright maps that align person estimates with item estimates on a logit scale, and item characteristic and cumulative probability curves. It estimates item parameters using marginal maximum likelihood techniques. Integrals are approximated using quadrature or Monte Carlo methods, with user-defined number of nodes and upper and lower bounds of the latent traits. Users may also define convergence criteria and iteration limits. Differential item functioning and item bias can be explored by partitioning the response data on user-defined grouping criteria. Traditional item-analysis statistics are produced by ConstructMap as well as item response modeling fit statistics.ConstructMap produces the following reports and maps: