The experimental BCHOICE procedure performs Bayesian analysis for discrete choice models. Discrete choice models are used in marketing research to model decision makers’ choices among alternative products and services. The decision makers might be people, households, companies and so on, and the alternatives might be products, services, actions, or any other options or items about which choices must be made (Train, 2009). The collection of alternatives that are available to the decision makers is called a choice set. Discrete choice models are derived under the assumption of utility-maximizing behavior by decision makers. When individuals are asked to choose among a set of alternatives, they usually determine the level of utility that each alternative offers.

To use the BCHOICE procedure, you need to specify the model for the data. You can also supply a prior distribution for the parameters if you want something other than the default noninformative prior. PROC BCHOICE obtains samples from the corresponding posterior distributions, produces summary and diagnostic statistics, and saves the posterior samples in an output data set that can be used for further analysis.

The ICLIFETEST procedure performs nonparametric survival analysis for interval-censored data. You can use the ICLIFETEST procedure to compute nonparametric estimates of survival functions and to examine the equality of survival functions via statistical tests. The ICLIFETEST procedure is similar to the LIFETEST procedure. The two procedures share the same analytic objectives: estimating and summarizing subjects’ survival experiences and comparing them systematically. The distinction between these procedures lies in the types of data that they are designed to handle. The ICLIFETEST procedure is intended primarily for handling interval-censored data, whereas the LIFETEST procedure deals exclusively with right-censored data. You can use the ICLIFETEST procedure to analyze data that are left-censored, interval-censored, or right-censored. However, if the data to be analyzed contain only exact or right-censored observations, you should use the LIFETEST procedure because it provides specialized methods for right-censored data.

The experimental IRT procedure fits item response models. These models are widely used in education to calibrate and evaluate items in tests, questionnaires, and other instruments and to score subjects on their abilities, attitudes, or other latent traits. In recent years, IRT models have also become increasingly popular in health behavior, quality of life, and clinical research. The IRT procedure fits the Rasch model; one-, two-, three-, and four-parameter models; and the graded response model with a logistic or probit link. It enables different items to have different response models, performs multidimensional exploratory and confirmatory analysis, performs multiple-group analysis, and estimates factor scores.