Generic summary function for drFit objects

Usage

# S3 method for drFit
summary(object, ...)

Arguments

object: object of class drFit
...: Additional arguments. This has currently no effect and is only meant to fulfill the requirements of a generic function.

Value

A dataframe with parameters for all samples extracted from the dose-response analysis.

Examples

# \donttest{
# Create random growth data set
rnd.data1 <- rdm.data(d = 35, mu = 0.8, A = 5, label = 'Test1')
rnd.data2 <- rdm.data(d = 35, mu = 0.6, A = 4.5, label = 'Test2')

rnd.data <- list()
rnd.data[['time']] <- rbind(rnd.data1$time, rnd.data2$time)
rnd.data[['data']] <- rbind(rnd.data1$data, rnd.data2$data)

# Run growth curve analysis workflow
gcFit <- growth.gcFit(time = rnd.data$time,
                       data = rnd.data$data,
                       parallelize = FALSE,
                       control = growth.control(fit.opt = 's',
                                                suppress.messages = TRUE))

# Perform dose-response analysis
drFit <- growth.drFit(gcTable = gcFit$gcTable,
                 control = growth.control(dr.parameter = 'mu.spline'))
#> 
#> === EC 50 Estimation ==============================
#> ---------------------------------------------------
#> --> Checking data ...
#> --> Number of distinct tests found: 2 
#> --> Valid datasets per test: 
#>       TestID Number
#>       Test1  35    
#>       Test2  35    

# Inspect results
summary(drFit)
#>    Test log.x log.y Samples EC50.Estimate EC50.Std..Error EC50.Lower EC50.Upper
#> 1 Test1 FALSE FALSE       0     0.1600828     0.002515864  0.1549581  0.1652074
#> 2 Test2 FALSE FALSE       0     0.1165660     0.001749722  0.1130019  0.1201301
#>       yEC50      test model
#> 1 0.3312132 mu.spline  W1.3
#> 2 0.2355672 mu.spline  W1.3
# }