# MCResult.calcBias: Systematical Bias Between Reference Method and Test Method In mcr: Method Comparison Regression

## Description

Calculate systematical bias between reference and test methods at the decision point Xc as Bias(Xc) = Intercept + (Slope-1) * Xc with corresponding confidence intervals.

## Usage

 ```1 2``` ```MCResult.calcBias(.Object, x.levels, type = c("absolute", "proportional"), percent = TRUE, alpha = 0.05, ...) ```

## Arguments

 `.Object` object of class "MCResult". `type` One can choose between absolute (default) and proportional bias (`Bias(Xc)/Xc`). `percent` logical value. If `percent = TRUE` the proportional bias will be calculated in percent. `x.levels` a numeric vector with decision points for which bias schould be calculated. `alpha` numeric value specifying the 100(1-`alpha`)% confidence level of the confidence interval (Default is 0.05). `...` further parameters

## Value

response and corresponding confidence interval for each decision point from x.levels.

`plotBias`

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18``` ```#library("mcr") data(creatinine,package="mcr") x <- creatinine\$serum.crea y <- creatinine\$plasma.crea # Deming regression fit. # The confidence intervals for regression coefficients # are calculated with analytical method model <- mcreg( x,y,error.ratio = 1,method.reg = "Deming", method.ci = "analytical", mref.name = "serum.crea", mtest.name = "plasma.crea", na.rm=TRUE ) # Now we calculate the systematical bias # between the testmethod and the reference method # at the medical decision points 1, 2 and 3 calcBias( model, x.levels = c(1,2,3)) calcBias( model, x.levels = c(1,2,3), type = "proportional") calcBias( model, x.levels = c(1,2,3), type = "proportional", percent = FALSE) ```

### Example output

```Please note:
2 of 110 observations contain missing values and have been removed.
Number of data points in analysis is 108.
Level         Bias         SE         LCI       UCI
X1     1 -0.004374069 0.01784350 -0.03975054 0.0310024
X2     2  0.050165272 0.03186142 -0.01300309 0.1133336
X3     3  0.104704613 0.06488644 -0.02393907 0.2333483
Level Prop.bias(%)       SE        LCI      UCI
X1     1   -0.4374069 1.784350 -3.9750541 3.100240
X2     2    2.5082636 1.593071 -0.6501545 5.666682
X3     3    3.4901538 2.162881 -0.7979691 7.778277
Level    Prop.bias         SE          LCI        UCI
X1     1 -0.004374069 0.01784350 -0.039750541 0.03100240
X2     2  0.025082636 0.01593071 -0.006501545 0.05666682
X3     3  0.034901538 0.02162881 -0.007979691 0.07778277
```

mcr documentation built on May 30, 2017, 6:15 a.m.