Tidy summarizes information about the components of a model. A model component might be a single term in a regression, a single hypothesis, a cluster, or a class. Exactly what tidy considers to be a model component varies across models but is usually self-evident. If a model has several distinct types of components, you will need to specify which components to return.
# S3 method for drc tidy(x, conf.int = FALSE, conf.level = 0.95, ...)
x | A |
---|---|
conf.int | Logical indicating whether or not to include a confidence
interval in the tidied output. Defaults to |
conf.level | The confidence level to use for the confidence interval
if |
... | Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in |
The tibble has one row for each curve and term in the regression.
The curveid
column indicates the curve.
Other drc tidiers:
augment.drc()
,
glance.drc()
A tibble::tibble()
with columns:
Upper bound on the confidence interval for the estimate.
Lower bound on the confidence interval for the estimate.
The estimated value of the regression term.
The two-sided p-value associated with the observed statistic.
The value of a T-statistic to use in a hypothesis that the regression term is non-zero.
The standard error of the regression term.
The name of the regression term.
Index identifying the curve.
if (requireNamespace("drc", quietly = TRUE)) { library(drc) mod <- drm(dead / total ~ conc, type, weights = total, data = selenium, fct = LL.2(), type = "binomial" ) tidy(mod) tidy(mod, conf.int = TRUE) glance(mod) augment(mod, selenium) } #> # A tibble: 25 × 7 #> type conc total dead .fitted .resid .cooksd #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 1 0 151 3 0 0.0199 0 #> 2 1 100 146 40 0.199 0.0748 0.0000909 #> 3 1 200 116 31 0.414 -0.146 0.000104 #> 4 1 300 159 85 0.565 -0.0302 0.00000516 #> 5 1 400 150 102 0.667 0.0133 0.00000220 #> 6 1 500 140 112 0.737 0.0633 0.0000720 #> 7 2 0 141 2 0 0.0142 0 #> 8 2 100 153 30 0.246 -0.0495 0.000168 #> 9 2 200 142 59 0.369 0.0468 0.0000347 #> 10 2 300 139 82 0.451 0.139 0.0000430 #> # … with 15 more rows