Rcurvep (version 1.3.1)

summarize_fit_output: Summarize the results from the parametric fitting using types of models

Description

The function first extracts the activity data based on the fit the supplied input parameters. In addition, summary of activity data (e.g., confidence interval, hit confidence) can be produced.

Usage

summarize_fit_output(
  d,
  thr_resp = 20,
  perc_resp = 10,
  ci_level = 0.95,
  extract_only = FALSE
)

Value

A list of named components: result and result_nested (and act_summary). The result and result_nested are the copy from the output of run_fit(). An act_set is added under the result component. If (extract_only = FALSE), an act_summary is added.

Arguments

d

The output from the run_fit().

thr_resp

The response cutoff to calculate the potency. Default = 20 (POD20)

perc_resp

The percentage cutoff to calculate the potency. Default = 10 (EC10).

ci_level

The confidence level for the activity metrics. Default is = 0.95.

extract_only

Whether act_summary data should be produced. Default = FALSE.

Hit definition

cnst

If the cnst is the winning model and the median of responses larger than the thr_resp, it is considered as an hit. The median of responses is reported as Emax and the lowest tested concentration is reported as EC50, POD, ECxx.

hill

The hit (=1) is considered having POD < max tested concentration.

cc2

The hit value is from the cc2 value

Output structure

output |- result (list) | |- fit_set (tibble, all output from the respective fit model included) | |- resp_set (tibble) | |- act_set (tibble, EC50, ECxx, Emax, POD, slope, hit) | |- result_nested (tibble) |- act_summary (tibble, confidence interval)

activity metrics

hit

hit call, see above definition

EC50

half maximal effect concentration

ECxx

effect concentration at XX percent, depending on the perc_resp

POD

point-of-departure, depending on the thr_resp

Emax

max effect - min effect from the fit

slope

slope factor from the fit

Details

A tibble, act_set is generated. When (extract_only = FALSE), a tibble, act_summary is generated with confidence intervals of the activity metrics. The quantile approach is used to calculate the confidence interval. Currently only bootstrap calculations from hill (3-parameter) can generate confidence interval For potency activity metrics, if value is NA, highest tested concentration is used in the summary. For other activity metrics, if value is NA, 0 is used in the summary.

See Also

run_fit()

Examples

# generate some fit outputs

# \donttest{
## fit only
fitd1 <- run_fit(zfishbeh, modls = "cc2")

## fit + bootstrap samples
fitd2 <- run_fit(zfishbeh, n_samples = 3, modls = "hill")

## fit using hill + cnst
fitd3 <- run_fit(zfishbeh, modls = c("hill", "cnst"))


# only to extract the activity data
sumd1 <- summarize_fit_output(fitd1, extract_only = TRUE)
sumd3 <- summarize_fit_output(fitd3, extract_only = TRUE)

# calculate EC20 instead of default EC10
sumd1 <- summarize_fit_output(fitd1, extract_only = TRUE, perc_resp  = 20)

# calculate POD using a higher noise level (e.g., 40)
## this number depends on the response unit
sumd1 <- summarize_fit_output(fitd1, extract_only = TRUE, thr_resp  = 40)

# calculate confidence intervals based on the bootstrap samples
sumd2 <- summarize_fit_output(fitd2)

# }