## 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")
```