qqrank: Load-Deviance Ranking
In phalen: Phalen Algorithms and Functions

Description Usage Arguments Details Value Author(s) See Also Examples

View source: R/qqrank.R

Rank by size and deviance from the hypothesized mean.

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qqrank(X, INDEX, alternative = c("two.sided", "less", "greater"), 
       absrank = TRUE, N = NA, b = NA, plotpenalty = TRUE, 
       allowed.error = 0.005)

`X`	A numeric vector.
`INDEX`	A factor of length `X`.
`alternative`	The alternative hypothesis. Accepts `"two.sided"`, `"less"`, or `"greater"`.
`absrank`	If `TRUE`, `INDEX` means greater than or less than the population mean will produce a positive `qqscore`. If `FALSE`, `INDEX` means greater than the population mean will have a positive `qqscore` and `INDEX` means less than the population mean will have a negative `qqscore`. The default is `TRUE`.
`N`	The number of observations below which a growth penalty is applied. `N` is passed to `x1` argument of `glpenalty`.
`b`	A positive numeric value representing the growth rate of the `glpenalty`.
`plotpenalty`	If `TRUE`, the `glpenalty` is plotted. The default is `TRUE`.
`allowed.error`	The allowed difference between `glpenalty` and `1` at `N`. The default is `0.005`.

qqrank ranks by size and deviance from the hypothesized mean using either the Binomial Test or Welch's t-Test. Restated, qqrank is a function of a size penalty, test statistic or variant thereof, and p-value.

`qqrankmatrix`	A data frame containing the size, mean, standard deviation, and qqrank of each `INDEX`.
`test.used`	The statistical test used to measure deviance from the mean.
`pop.mean`	The mean of `X`.
`pop.sd`	The standard deviation of `X`.

Robert P. Bronaugh

glpenalty t.test binom.test

  # which hospital has the "worst" readmissions? (note: the average
  # readmission rate is 17.13%
  data(ipadmits)
  attach(ipadmits)
  ip.ag = data.frame('sum' = tapply(ipadmits$isReadmission,ipadmits$HospID,sum),
                     'avg' = tapply(ipadmits$isReadmission,ipadmits$HospID,mean))
  
  # hospital 9 has the most readmissions (1,094), but the percent of readmissions
  # is low at 14%, less than the population average. 
  ip.ag[order(-ip.ag$sum),][1,]
  
  # hostpital 80 has the highest percentage of readmissions 87.5%, but only
  # 7 readmissions over all. 
  ip.ag[order(-ip.ag$avg),][1,]
  
  # using qqrank and penalizing samples less than N = 250 at a growth
  # rate of b = 0.05, Hospital 39 has 1606 readmissions with a readmission
  # percent of 38%. 
  qqr = qqrank(ipadmits$isReadmission,ipadmits$HospID
               ,alternative = "greater",N = 250, b = 0.05)
  round(qqr$rankmatrix,2)
  
  # relax sample penalty and rank on both sides of the mean
  # Hospital 21 has the "best" readmission track record.
  qqr = qqrank(ipadmits$isReadmission,ipadmits$HospID
               ,alternative = "two.sided",absrank = FALSE,N = 30, b = 0.1)
  round(qqr$rankmatrix,2)
  detach(ipadmits)