# robust: Algorithm that implements the robust method for reference... In referenceIntervals: Reference Intervals

## Description

The robust method is an iterative method that determines the most appropriate weighted mean of the data and then calculates the desired reference interval.

## Usage

 `1` ```robust(data, indices = c(1:length(data)), refConf = 0.95) ```

## Arguments

 `data` Vector of data. `indices` Indices of data to use for calculations. `refConf` Desired coverage of the reference interval. Default is 95 interval.

## Value

Returns a vector containing the lower and upper limits of the reference interval.

Daniel Finnegan

## References

Defining, Establishing, and Verifying Reference Intervals in the Clinical Laboratory; Approved Guideline - 3rd Edition (C28-A3)

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54``` ```robust(set50) robust(horn.outliers(set20)\$subset) ## The function is currently defined as function (data, indices = c(1:length(data)), refConf = 0.95) { data = sort(data[indices]) n = length(data) median = summary(data)[[3]] Tbi = median TbiNew = 10000 c = 3.7 MAD = summary(abs(data - median))[[3]] MAD = MAD/0.6745 smallDiff = FALSE repeat { ui = (data - Tbi)/(c * MAD) ui[ui < -1] = 1 ui[ui > 1] = 1 wi = (1 - ui^2)^2 TbiNew = (sum(data * wi)/sum(wi)) if ((abs(TbiNew - Tbi)) < 1e-06) { break } Tbi = TbiNew } ui = NULL ui = (data - median)/(205.6 * MAD) sbi205.6 = 205.6 * MAD * sqrt((n * sum(((1 - ui[ui > -1 & ui < 1]^2)^4) * ui[ui > -1 & ui < 1]^2))/(sum((1 - ui[ui > -1 & ui < 1]^2) * (1 - 5 * ui[ui > -1 & ui < 1]^2)) * max(c(1, -1 + sum((1 - ui[ui > -1 & ui < 1]^2) * (1 - 5 * ui[ui > -1 & ui < 1]^2)))))) ui = NULL ui = (data - median)/(3.7 * MAD) sbi3.7 = 3.7 * MAD * sqrt((n * sum(((1 - ui[ui > -1 & ui < 1]^2)^4) * ui[ui > -1 & ui < 1]^2))/(sum((1 - ui[ui > -1 & ui < 1]^2) * (1 - 5 * ui[ui > -1 & ui < 1]^2)) * max(c(1, -1 + sum((1 - ui[ui > -1 & ui < 1]^2) * (1 - 5 * ui[ui > -1 & ui < 1]^2)))))) ui = NULL ui = (data - Tbi)/(3.7 * sbi3.7) St3.7 = 3.7 * sbi3.7 * sqrt((sum(((1 - ui[ui > -1 & ui < 1]^2)^4) * ui[ui > -1 & ui < 1]^2))/(sum((1 - ui[ui > -1 & ui < 1]^2) * (1 - 5 * ui[ui > -1 & ui < 1]^2)) * max(c(1, -1 + sum((1 - ui[ui > -1 & ui < 1]^2) * (1 - 5 * ui[ui > -1 & ui < 1]^2)))))) tStatistic = qt(1 - ((1 - refConf)/2), (n - 1)) margin = tStatistic * sqrt(sbi205.6^2 + St3.7^2) robustLower = Tbi - margin robustUpper = Tbi + margin RefInterval = c(robustLower, robustUpper) return(RefInterval) } ```

referenceIntervals documentation built on May 30, 2017, 3:08 a.m.