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I've run a simple model using orm (i.e. reg <- orm(formula = y ~ x)) and I'm having trouble understanding how the model comes up with predicted values.

I can get predicted values using predict(reg, type = "mean") and I'm looking for some explanation of how the model output (i.e. intercepts and parameters) gets converted to a predicted value. The documentation for predict.orm has the following: "For an ordinal response variable, type="mean" computes the estimated mean Y by summing values of Y multiplied by the estimated Prob(Y=j)."

I'm not clear on what that means. I will say that the predicted values come out looking similar to an OLS model so I think I'm on track

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    $\begingroup$ If your question is primarily one of coding or issues of how a function works in a particular package it's likely off-topic here (see the link under Programming). If you still think your question is on topic on that basis, can you clarify your question as a primarily a statistical issue? $\endgroup$ – Glen_b Nov 3 '16 at 23:53
  • $\begingroup$ This seems like a statistical question asked in terms of R code to me. $\endgroup$ – gung Nov 4 '16 at 21:34

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