Postestimation Analysis with Stata by SPost13 commands of Survey Data analyzed by MNLM

Data coming back from a brand survey have been analysed by a regression model for nominal outcomes, also known as the Multinomial Logit Model. The Multinomial Logit Model (MNLM) belongs to a multivariate version of Generalized Linear Models (GLM), a class of models popularized by McCullagh and Nelder (1982) and widely used in many different fields (Social Sciences, Biomedical Sciences, Epidemiology, Public Health, Genetic, Zoology, Education, but also Marketing Researches, Survey Analysis and Product/Process/Service Quality Control). The interpretation of these regression models requires a background knowledge that is not always common, especially in business application fields. Data must be “readable” to anyone who has the responsibility to take serious decision, which can strongly influence not only the business of a company but also the safety and the quality of its products/processes and services. The scope of this presentation is to show and highlight the advantages of the implementation of Spost13 commands, setup by J. Scott Long and J. Freese, as very useful tools for making easier the interpretation of results coming from the implementation of this regression model for nominal response variables.