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COUNT (version 1.3.2)

poi.obs.pred: Table of Poisson counts: observed vs predicted proportions and difference

Description

poi.obs.pred is used to produce a table of a Poisson model count response with mean observed vs mean predicted proportions, and their difference.

Usage

poi.obs.pred(len, model)

Arguments

len
highest count for the table
model
name of the Poisson model created

Value

  • Countcount value
  • obsPropFreqObserved proportion of counts
  • avgpPredicted proportion of counts
  • DiffDifference in observed vs predicted

Details

poi.obs.pred is used to determine where disparities exist in the mean observed and predicted proportions in the range of model counts. poi.obs.pred is used in Table 6.15 and other places in Hilbe (2011). poi.obs.pred follows glm(), where both y=TRUE and model=TRUE options must be used.

References

Hilbe, J.M. (2011), Negative Binomial Regression, second edition, Cambridge University Press.

See Also

myTable

Examples

Run this code
data(medpar)
mdpar <- glm(los ~ hmo+white+type2+type3, family=poisson, data=medpar, y=TRUE, model=TRUE)
poi.obs.pred(len=25, model=mdpar)

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