plotAverageModel: Plot for the model-averaged response values and bmd
In alfcrisci/bmdModeling: Benchmark dose modeling

Plot for the model-averaged response values and bmd

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plotAverageModel(proastData, xans, yans, nans = 0, bmd, modelResults,
  bootstrapBmd = NULL, bootstrapModelResults = NULL,
  confidenceLevel = 0.9, naiveApproach = FALSE)

`proastData`	list, data in proast format as returned by f.scan()
`xans`	integer, indicates the column in proastData$data containing x-values (dose)
`yans`	integer, indicates the column in proastData$data containing y-values (response)
`nans`	integer, indicates the column in proastData$data containing sample size; if irrelevant set to 0; default value is 0
`bmd`	numeric value, the estimated model-averaged BMD as returned by optimizeBmd()
`modelResults`	list, with results for fitted model for bmd; contains at least npar, loglik, model.ans, regr.par, CES and ces.ans; these are by default included in result from f.proast(); Eventually contains also fct1 and fct2 if factors are included for the model parameters
`bootstrapBmd`	numeric vector, estimated bmd for each of the bootstrap data sets as returned by bootstrapBmd(); default value is NULL
`bootstrapModelResults`	list with for each of the bootstrap data sets results of the fitted model; should contain at least see param modelResults above; as returned by bootstrapBmd(); default value is NULL
`confidenceLevel`	numeric, defines constructed confidence interval for bmd, e.g. if 0.9 then lower and upper bound of 90 default value is 0.9
`naiveApproach`	boolean, TRUE if the model-averaged BMD is estimated as the weighted average of bmd values, FALSE if the model-averaged BMD is estimated based on weighted average of response values; default value is FALSE