Comparison of effective dose values

Comparison of a pair of effective dose values from independent experiments where only the estimates and their standard errors are reported.

comped(est, se, log = TRUE, interval = TRUE, operator = c("-", "/"),
  level = 0.95, df = NULL)

Arguments

est	a numeric vector of length 2 containing the two estimated ED values
se	a numeric vector of length 2 containing the two standard errors
log	logical indicating whether or not estimates and standard errors are on log scale
interval	logical indicating whether or not a confidence interval should be returned
operator	character string taking one of the two values "-" (default) or "/" corresponding to a comparison based on the difference or the ratio.
level	numeric value giving the confidence level
df	numeric value specifying the degrees of freedom for the percentile used in the confidence interval (optional)

Details

The choice "/" for the argument operator and FALSE for log will result in estimation of a socalled relative potency (sometimes also called a selectivity index).

The combination TRUE for log and "/" for operator only influences the confidence interval, that is no ratio is calculated based on logarithm-transformed effective dose values.

By default confidence interval relies on percentiles in the normal distribution.

In case the entire dataset is available the functions drm and (subsequently) EDcomp should be used instead.

Value

A matrix with the estimated difference or ratio and the associated standard error and the resulting confidence interval (unless not requested).

References

Wheeler, M. W. and Park, R. M. and Bailer, A. J. (2006) Comparing median lethal concentration values using confidence interval overlap or ratio tests, Environmental Toxicology and Chemistry, 25, 1441--1441.

Note

The development of the function comped is a side effect of the project on statistical analysis of toxicity data funded by the Danish EPA ("Statistisk analyse og biologisk tolkning af toksicitetsdata", MST j.nr. 669-00079).

See also

The function ED.drc calculates arbitrary effective dose values based on a model fit. The function EDcomp calculates relative potencies based on arbitrary effective dose values.

Examples

## Fitting the model
S.alba.m1 <- boxcox(drm(DryMatter~Dose, Herbicide, data=S.alba, fct = LL.4(),
pmodels=data.frame(Herbicide,1,1,Herbicide)), method = "anova")

## Displaying estimated ED values
ED(S.alba.m1, c(10, 90))
#> 
#> Estimated effective doses
#> 
#>                 Estimate Std. Error
#> e:Bentazone:10   18.0321     2.5790
#> e:Bentazone:90   44.7170     2.6095
#> e:Glyphosate:10  21.1807     4.1023
#> e:Glyphosate:90 203.0085    24.8259

## Making comparisons of ED50 in two ways and for both differences and ratios
compParm(S.alba.m1, "e", "/")
#> 
#> Comparison of parameter 'e' 
#> 
#>                      Estimate Std. Error t-value   p-value    
#> Bentazone/Glyphosate 0.433044   0.041805 -13.562 < 2.2e-16 ***
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

comped(c(28.396147, 65.573335), c(1.874598, 5.618945), log=FALSE, operator = "/")
#> 
#> Estimated ratio of effective doses
#> 
#>      Estimate Std. Error    Lower  Upper
#> [1,] 0.433044   0.046842 0.341235 0.5249
# similar result

compParm(S.alba.m1, "e", "-")
#> 
#> Comparison of parameter 'e' 
#> 
#>                      Estimate Std. Error t-value   p-value    
#> Bentazone-Glyphosate -37.1772     5.5365 -6.7149 6.681e-09 ***
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

comped(c(28.396147, 65.573335), c(1.874598, 5.618945), log=FALSE, operator = "-")
#> 
#> Estimated difference of effective doses
#> 
#>      Estimate Std. Error    Lower   Upper
#> [1,] -37.1772     5.9234 -48.7868 -25.567
# similar result

## Making comparisons of ED10 and ED90
comped(c(21.173, 44.718), c(11.87, 8.42), log=FALSE, operator = "/")
#> 
#> Estimated ratio of effective doses
#> 
#>       Estimate Std. Error     Lower  Upper
#> [1,]  0.473478   0.280013 -0.075336 1.0223

comped(c(21.173, 44.718), c(11.87, 8.42), log=FALSE, operator = "/", interval = FALSE)
#> 
#> Estimated ratio of effective doses
#> 
#>      Estimate Std. Error
#> [1,]  0.47348       0.28

comped(c(21.173, 44.718), c(11.87, 8.42), log=FALSE, operator = "-")
#> 
#> Estimated difference of effective doses
#> 
#>      Estimate Std. Error   Lower  Upper
#> [1,]  -23.545     14.553 -52.069 4.9786