Effect of an effluent on the growth of mysid shrimp

Description

Juvenile mysid shrimp (Mysidopsis bahia) were exposed to up to 32% effluent in a 7-day survival and growth test. The average weight per treatment replicate of surviving organisms was measured.

Usage

data(M.bahia)

Format

A data frame with 40 observations on the following 2 variables.

conc

a numeric vector of effluent concentrations (%)

dryweight

a numeric vector of average dry weights (mg)

Details

The data are analysed in Bruce and Versteeg (1992) using a log-normal dose-response model (using the logarithm with base 10).

At 32% there was complete mortality, and this justifies using a model where a lower asymptote of 0 is assumed.

Source

Bruce, R. D. and Versteeg, D. J. (1992) A statistical procedure for modeling continuous toxicity data, Environ. Toxicol. Chem., 11, 1485–1494.

Examples

M.bahia.m1 <- drm(dryweight~conc, data=M.bahia, fct=LN.3())

## Variation increasing
plot(fitted(M.bahia.m1), residuals(M.bahia.m1))

## Using transform-both-sides approach
M.bahia.m2 <- boxcox(M.bahia.m1, method = "anova")
summary(M.bahia.m2)  # logarithm transformation

## Variation roughly constant, but still not a great fit
plot(fitted(M.bahia.m2), residuals(M.bahia.m2))

## Visual comparison of fits
plot(M.bahia.m1, type="all", broken=TRUE)
plot(M.bahia.m2, add=TRUE, type="none", broken=TRUE, lty=2)

ED(M.bahia.m2, c(10,20,50), ci="fls")

## A better fit
M.bahia.m3 <- boxcox(update(M.bahia.m1, fct = LN.4()), method = "anova")
#plot(fitted(M.bahia.m3), residuals(M.bahia.m3))
plot(M.bahia.m3, add=TRUE, type="none", broken=TRUE, lty=3, col=2)
ED(M.bahia.m3, c(10,20,50), ci="fls")