mixtox (version 1.4.0)

getCI: Calculating Confidence Intervals

Description

calculating non-simultanous confidence intervals and prediction intervals

Usage

getCI(object, effv, Scaled = TRUE, sigLev = 0.05, sav = FALSE)

Arguments

object

object of class curveFit.

effv

numeric matrix of experimental responses with at least three replicates.

Scaled

indicating if effv was scaled or not(TRUE/FALSE) in continuous dose-response (rtype = 'continuous')

sigLev

significance level(default is 0.05).

sav

TRUE: save output to a default file; FALSE: output will not be saved; a custom file directory: save output to the custom file directory.

Value

xmat

effect concentration(s) and corresponding CIs and PIs

emat

effect(s) and and corresponding CIs and PIs

sav

TRUE: save output to a default file; FALSE: output will not be saved; a custom file directory: save output to the custom file directory.

Details

The Delta method (Dybowski et al, 2001) is used to construct confidence intervals for predicted responses.

References

Zhu, X.-W. and Chen, J.-Y. (2016). mixtox: An R Package for Mixture Toxicity Assessment. R Journal, 8(2). Dybowski, R. and Gant, V. (2001). Clinical applications of artificial neural networks. Cambridge University Press, Cambridge. Gryze, S. De, Langhans, I., and Vandebroek, M. (2007). Using the correct intervals for prediction: A tutorial on tolerance intervals for ordinary least-squares regression. Chemom. Intell. Lab. Syst., 87, 147-154.

Examples

# NOT RUN {
## example 1
x <- cytotox$Ni$x
rspn <- cytotox$Ni$y
obj <- curveFit(x, rspn, eq = 'Logit', param = c(12, 3), effv = c(0.05, 0.5), rtype = 'quantal')
getCI(obj, effv = c(0.05, 0.50))
# }