‘ecotox’ was
created as simple approach to using either probit or logit analysis to
calculate lethal concentration (LC) or time (LT) and the appropriate
fiducial confidence limits desired for selected LC or LT for
ecotoxicology studies (Finney 1971; Wheeler et al. 2006; Robertson et
al. 2007). The simplicity of ‘ecotox’ comes from
the syntax it implies within its functions which are similar to
functions like glm()
and lm().
In addition to the simplicity of the syntax, a comprehensive tibble is
produced which gives the user a predicted LC or LT value for the desired
level and a suite of parameters such as fiducial confidence limits,
z-value, and slope. ‘ecotox’ was built
for and is published in Hlina et al. *In Review*.

You can install the CRAN released version of ‘ecotox’ from CRAN with:

`install.packages("ecotox")`

You can install the developer version of ‘ecotox’ from github with:

```
install.packages("devtools")
::install_github("benjaminhlina/ecotox") devtools
```

This is an example which uses the LC_probit function to calculate a
LC_{50} and LC_{99} for a probit analysis:

```
## Calculate LC50 and LC99
head(lamprey_tox)
## within the dataframe used, control dose, unless produced a value
## during experimentation, are removed from the dataframe,
## as glm cannot handle values of infinite. Other statistical programs
## make note of the control dose but do not include within analysis.
## calculate LC50 and LC99 for May
<- LC_probit((response / total) ~ log10(dose),
m p = c(50, 99),
weights = total,
data = lamprey_tox[lamprey_tox$nominal_dose != 0, ],
subset = c(month == "May"))
## view calculated LC50 and LC99 for seasonal toxicity of a pisicide,
## 3-trifluoromethyl-4-nitrophenol (TFM) to lamprey in 2011
m
## several new features include 1) being able to change the output length
## 2) you can indicate whether the x variable has been log10 transformed or
## not if it has the output will take that into consideration
<- LC_probit((response / total) ~ dose,
m_2 p = c(50, 99),
weights = total,
data = lamprey_tox,
subset = c(month == "May"),
log_x = FALSE,
long_output = FALSE)
## view calculated LC50 and LC99 for seasonal toxicity of a pisicide,
## 3-trifluoromethyl-4-nitrophenol (TFM) to lamprey in 2011.
m_2
```

See StackExchange post about differences in using
`cbind()`

vs. `response / total`

cbind()
function in R for a logistic regression.

```
## Additionally changes have been made to allow for the user
## to use `cbind()` method when specificying the response variable
<- LC_probit(cbind(response, survive) ~ log10(dose),
m_3 p = c(50, 99),
data = lamprey_tox[lamprey_tox$nominal_dose != 0, ],
subset = c(month == "May"))
m_3
# notice that m and m_3 produce the same results, however m_3 will produce
# a warning to ensure you have not weighted the model as it is not necessary
```

Example of using `ratio_test`

from Wheeler
et al. 2006 to determine differences in LC values:

```
## A new function `ratio_test` has been added
# view lamprey_tox data
head(lamprey_tox)
# using glm() to detemine LC values using probit model for May and June
<- glm((response / total) ~ log10(dose),
m data = lamprey_tox[lamprey_tox$nominal_dose != 0, ],
subset = c(month == "May"),
weights = total,
family = binomial(link = "probit"))
<- glm((response / total) ~ log10(dose),
j data = lamprey_tox[lamprey_tox$nominal_dose != 0, ],
subset = c(month == "June"),
weights = total,
family = binomial(link = "probit"))
# now that both May and June models have been made. use ratio_test to
# compare LC50 values or whatever LC values of interest.
<- ratio_test(model_1 = m, model_2 = j,
ratios percentage = 50,
compare = "May - June")
# view ratio test results
ratios
# you can also use LC_* or LT_* objects to create the models and use ratio test:
<- LC_probit((response / total) ~ log10(dose), p = c(50, 99),
m_1 weights = total,
data = lamprey_tox[lamprey_tox$nominal_dose != 0, ],
subset = c(month == "May"))
<- LC_probit((response / total) ~ log10(dose), p = c(50, 99),
j_1 weights = total,
data = lamprey_tox[lamprey_tox$nominal_dose != 0, ],
subset = c(month == "June"))
<- ratio_test(model_1 = m_1, model_2 = j_1, percentage = 50,
ratios_2 compare = "May - June", obj_type = "df")
ratios_2
```

Finney, D.J., 1971. Probit analysis. Cambridge University Press, Cambridge, England. ISBN: 052108041X

Wheeler, M.W., Park, R.M., and Bailey, A.J. 2006. Comparing median lethal concentration values using confidence interval overlap or ratio tests. Environ. Toxic. Chem. 25(5), 1441-1444. 10.1897/05-320R.1

Robertson, J.L., Savin, N.E., Russell, R.M. and Preisler, H.K., 2007. Bioassays with arthropods. CRC press. ISBN: 0849323312

When using this package please cite the following publication:

Hlina, B.L., Birceanu, O., Robinson, C.S., Dhiyebi, H., Wilkie, M.P.

*In Press*.The relationship between thermal physiology and lampricide sensitivity in larval sea lamprey (*Petromyzon marinus*). Journal of Great Lakes Research.10.1016/j.jglr.2021.10.002Version 1.4.4 written by Benjamin L. Hlina, Carleton University, Ottawa, Ontario, Canada. Written in ‘Programming Language R’, R version 4.1.1 (2021-08-10) – “Kick Things”. Source code is available at ‘ecotox’ or by contacting Benjamin L. Hlina at benjamin.hlina@gmail.com