A Graphical Method for the Interpretation of Multinomial Logit Analysis

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Abstract
Multinomial logit analysis is a statistical technique for relating a set of continuous or discrete independent variables to a categorical dependent variable. The availability of statistical software and the publication of review articles dealing with logit analysis has resulted in increasing applications of the model. These applications have been limited by a failure to deal adequately with the magnitudes of the parameters, restricting discussion almost entirely to the direction of effects and their statistical significance. This limitation is a consequence of the large number of parameters involved and the nonlinearity of the effects. To deal with this problem, a graphical method is proposed to represent the magnitudes and statistical significance of all effects in a multinomial logit analysis. This allows for a clear interpretation of the relative magnitudes of effects both within and across independent variables. The article concludes with an example to illustrate the technique.

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