Coefficients for an Emax regression

Returns the named vector of fitted parameter values. Parameters involving a log transformation (logEC50, logHill) are returned on the log scale by default, which is the scale on which they are estimated.

Usage

# S3 method for class 'emaxnls'
coef(object, back_transform = FALSE, ...)

Arguments

object

An emaxnls or emaxlogistic object

back_transform

Should log-scaled parameters (logEC50, logHill) be back-transformed to original scale?

...

Ignored

Value

A named numeric vector of parameter estimates

Details

Setting back_transform = TRUE exponentiates logEC50 and logHill and drops the log prefix from their names, expressing them on the concentration scale rather than the log-concentration scale on which they are estimated. confint() and vcov() are not affected by this argument and always return results on the log-concentration scale. The summary() method also accepts back_transform = TRUE and applies the same transformation to its coefficient table, including the confidence interval columns.

Examples

mod_c <- emax_nls(
  structural_model = rsp_1 ~ exp_1, 
  covariate_model = list(E0 ~ cnt_a, Emax ~ 1, logEC50 ~ 1), 
  data = emax_df,
  opts = emax_nls_options(max_time = 10)
)

# coefficients on the estimation scale
coef(mod_c)
#>          E0_cnt_a      E0_Intercept    Emax_Intercept logEC50_Intercept 
#>         0.4861467         5.0548075         9.9697250         8.2688405 

# coefficients with log-scale parameters back-transformed
coef(mod_c, back_transform = TRUE)
#>       E0_cnt_a   E0_Intercept Emax_Intercept EC50_Intercept 
#>      0.4861467      5.0548075      9.9697250   3900.4236534 

mod_b <- emax_logistic(
  structural_model = rsp_2 ~ exp_1,
  covariate_model = list(E0 ~ cnt_a, Emax ~ 1, logEC50 ~ 1),
  data = emax_df,
  opts = emax_logistic_options(max_time = 10)
)
coef(mod_b)
#>          E0_cnt_a      E0_Intercept    Emax_Intercept logEC50_Intercept 
#>         0.6587629        -5.0003872         8.1156731         9.7832270