Standardized estimates from categorical regression models

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Abstract
We consider the problem of interpreting categorical regression models, such as the polytomous logistic model, the continuation‐ratio model, the stereotype model, and the cumulative‐odds model. We present a method to convert categorical regression coefficients into estimates of standardized fitted probabilities, probability differences and probability ratios. We use a delta‐method approach to estimate standard errors. We then present a small simulation study to compare different transforms for setting confidence limits, and provide an illustration of our approach in an observational study of drug therapy of polymyositis.

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