LVS provides three types of model comparison (LRT, AIC, and BIC) using the package MASS. The stepwise regression uses both directions (step up and step down) and selects the best model (best predictors).
All three criteria assess model fit. LRT is based on log likelihood ratio (k = qchisq(1-p, df=1), where for p=0.05, k = 3.84). For more information on AIC ( Akaike Information Criterion ) and BIC (Bayesian information criterion) – see http://www.jmp.com/support/help/Likelihood_AICc_and_BIC.shtml.
Steps to perform stepwise regression in LVS:
- Upload csv or excel file – Panel DATA
- Go to Panel INFERENTIAL STATISTICS – tab MODELING
- Select your regression model (dependent and independent factors), type of regression (see tab REGRESSION) and click RUN regression.
- Go to STEPWISE REGRESSION tab and click RUN stepwise model.
- Return to Modeling and Regression and update your selection with the best fitted model.
As always, your feedback and suggestions are greatly appreciated! (LVS Team)