ecotox

install.packages("ecotox")

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

## 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

m <- LC_probit((response / total) ~ log10(dose),
                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

m_2 <- LC_probit((response / total) ~ dose,
                  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

## Additionally changes have been made to allow for the user 
## to use `cbind()` method when specificying the response variable  

m_3 <- LC_probit(cbind(response, survive) ~ log10(dose),
                  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 

## 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

m <- glm((response / total) ~ log10(dose),
         data = lamprey_tox[lamprey_tox$nominal_dose != 0, ],
         subset = c(month == "May"),
         weights = total,
         family = binomial(link = "probit"))


j <- glm((response / total) ~ log10(dose),
         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.

ratios <- ratio_test(model_1 = m, model_2 = j, 
                     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:

m_1 <- LC_probit((response / total) ~ log10(dose), p = c(50, 99),
weights = total,
data = lamprey_tox[lamprey_tox$nominal_dose != 0, ],
subset = c(month == "May"))



j_1 <- LC_probit((response / total) ~ log10(dose), p = c(50, 99),
weights = total,
data = lamprey_tox[lamprey_tox$nominal_dose != 0, ],
subset = c(month == "June"))



ratios_2 <- ratio_test(model_1 = m_1, model_2 = j_1, percentage = 50,
compare = "May - June", obj_type = "df")

ratios_2