Calculate Response with Confidence Interval.

Calculate Response \(Intercept + Slope * Refrencemethod\) with Corresponding Confidence Interval

MCResult.calcResponse(.Object, x.levels, alpha, ...)

Arguments

.Object

object of class "MCResult".

x.levels

a numeric vector with points for which response 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 point in vector x.levels.

See also

calcBias

Examples

    #library("mcr")
    data(creatinine,package="mcr")
    x <- creatinine$serum.crea
    y <- creatinine$plasma.crea
    # Deming regression fit.
    # The confidence intercals 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 )
#> Please note: 
#> 2 of 110 observations contain missing values and have been removed.
#> Number of data points in analysis is 108.
    calcResponse(model, x.levels=c(1,2,3))
#>    X         Y       Y.SE     Y.LCI    Y.UCI
#> X1 1 0.9956259 0.01784350 0.9602495 1.031002
#> X2 2 2.0501653 0.03186142 1.9869969 2.113334
#> X3 3 3.1047046 0.06488644 2.9760609 3.233348