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ec50estimator helps scientists estimate EC50 from
grouped dose-response datasets. It wraps the modelling engine from
drc in a workflow that is easier to use for experiments
with many isolates, fields, fungicides, years, or other strata.
The package is built around one practical sequence:
ggplot2.Install the stable release from CRAN.
install.packages("ec50estimator")Install the development version from GitHub.
pak::pak("AlvesKS/ec50estimator")library(ec50estimator)
library(drc)
data(multi_isolate)
example_data <- subset(
multi_isolate,
isolate %in% 1:5 & fungicida == "Fungicide A"
)
check_ec50_data(
example_data,
response = "growth",
dose = "dose",
isolate = "isolate",
strata = "field"
)
fit <- ec50_multimodel(
growth ~ dose,
data = example_data,
isolate_col = "isolate",
strata_col = "field",
fct = list(drc::LL.3(), drc::LL.4(), drc::W2.3()),
interval = "delta"
)
best_model(fit)
plot_EC50_curves(fit, models = "best")
report_ec50(fit, models = "best")fit is still a data frame, so existing workflows that
call head(fit) or write the estimates to a file continue to
work. It also stores the fitted drc models and metadata
needed by helper functions:
curve_data(fit)
fitted_models(fit)
ec50_metadata(fit)
predict_ec50(fit, dose = c(0.001, 0.01, 0.1), models = "best")
plot_residuals(fit, models = "best")See the pkgdown site for the recommended workflow: https://alvesks.github.io/ec50estimator/.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.