td2pLL_anova: ANOVA pre-test in the TDR analysis pipeline

In jcduda/td2pLL: Fitting a time-dose two-parameter log-logistic model to time-dose-response data

ANOVA pre-test in the TDR analysis pipeline

Description

In the time-dose-response (TDR) analysis pipeline, data where in addition to dose (or concentration) and response, also time (e.g. exposure times) are measured, it is checked in a (nested) anova based pre-test if the td2pLL model is appropriate. That means, it is checked if the exposure time has an effect on the dose-response relationship or not.

Usage

td2pLL_anova(data, alpha = 0.05)

Arguments

data	(data.frame()) Numeric data frame containing the response resp, time and dose.
alpha	(numeric(1)) The significance level.

Details

A nested anova is performed where a null model is tested against a full model. The null model is a regular 2pLL model with upper and lower limit 100 and 0, respectively. The (exposure) time variable is ignored and a single dose-response curve is fitted for the null model. In the full model, an individual ED50 value is calculated for each (exposure) time level. However, only one common h parameter is included in the full model. Hence, if the test rejects the null model, there seems to be significant evidence that (exposure) time has an effect on the dose-response relationship. Thus, the td2pLL model will be used during the fitting step of the TDR analysis pipeline. Otherwise, if there is no significant evidence of the influence of (exposure) time on the dose-response relationship, a simple 2pLL model is used in the fitting step that ignores (exposure) time. For more details see Duda et al. (2021).

Examples

data(cytotox)
data_subset <- cytotox[cytotox$compound == "ASP", c("expo", "dose", "resp")]
colnames(data_subset)[1] <- "time"
td2pLL_anova(data = data_subset)

jcduda/td2pLL documentation built on May 14, 2022, 6:48 p.m.