Quantal Response

Quantal Response is a statistical package which provides a set of procedures for estimating models in which the dependent variable is qualitative in some way. These models are particularly useful for researchers in the social, behavioral, and biomedical sciences, as well as economics, public choice, education, and marketing.

Features

• Efficiently handles large data sets
• Estimates unknown parameters
• Provides a variety of goodness-of-fit measures
• All regression procedures can be run at a specified data range
• Performs multiple linear hypothesis testing with any form
• Accommodates both numeric and character variables

Main Models

• LOGIT: Estimates multinomial logit model, in which qualitative choices have more than two categories
• ORDERED: Estimates the ordered logit or ordered probit models in which the choice variable is inherently ordered
• PROBIT: Estimates the binomial probit model
• PSNREG: Estimates the poisson regression model
• QTEST: Tests the linear hypotheses

Available for Windows NT, Windows 9x, and UNIX versions of GAUSS.