The Parameter Estimates report gives estimates and standard errors of the coefficients of utility associated with the effects listed in the Term column. The coefficients associated with attributes are sometimes referred to as part-worths. When the Firth Bias-Adjusted Estimates option is selected in the launch window, the parameter estimates are based on the Firth bias-corrected maximum likelihood estimators. These estimates considered to be more accurate than MLEs without bias correction. For more information about utility, see Utility and Probabilities.
The following fit statistics are shown as part of the report and can be used to compare models: AICc (corrected Akaike’s Information Criterion), BIC (Bayesian Information Criterion), −2Loglikelihood, and −2Firth Loglikelihood. See Likelihood, AICc, and BIC in Fitting Linear Models.
The −2Firth Loglikelihood fit statistic is included in the report when the Firth Bias-Adjusted Estimates option is selected in the launch window. Note that this option is checked by default. The decision to use or not use the Firth Bias-Adjusted Estimates does not affect the AICc score or the −2Loglikelihood results.
Note: For each of these statistics, a smaller value indicates a better fit.