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Construct an initial guess for logistic Emax model parameters

Source: R/api.R
emax_logistic_init.Rd

Constructs a data frame of starting values and parameter bounds for the logistic Emax model, using the same heuristic approach as emax_nls_init() applied to the empirical logit scale rather than the raw response.

Usage

emax_logistic_init(structural_model, covariate_model = NULL, data)

Arguments

structural_model

A two-sided formula of the form response ~ exposure

covariate_model

A list of two-sided formulas, each specifying a covariate model for a structural parameter. When NULL (the default), an intercept-only hyperbolic Emax model is assumed — equivalent to list(E0 ~ 1, Emax ~ 1, logEC50 ~ 1).

data

A data frame

Value

A data frame with columns parameter, covariate, start, lower, and upper

See also

emax_logistic(), emax_logistic_options()

Examples

# intercept-only hyperbolic Emax (default covariate_model)
emax_logistic_init(
  structural_model = rsp_2 ~ exp_1,
  data = emax_df
)
#> # A tibble: 3 × 5
#>   parameter covariate start  lower upper
#>   <chr>     <chr>     <dbl>  <dbl> <dbl>
#> 1 E0        Intercept -6.56 -48.8   35.7
#> 2 Emax      Intercept 19.6  -22.7   61.8
#> 3 logEC50   Intercept  8.91   7.07  10.8

# with a covariate on E0
emax_logistic_init(
  structural_model = rsp_2 ~ exp_1,
  covariate_model = list(E0 ~ cnt_a, Emax ~ 1, logEC50 ~ 1),
  data = emax_df
)
#> # A tibble: 4 × 5
#>   parameter covariate start  lower upper
#>   <chr>     <chr>     <dbl>  <dbl> <dbl>
#> 1 E0        cnt_a      0    -25.6   25.6
#> 2 E0        Intercept -6.56 -48.8   35.7
#> 3 Emax      Intercept 19.6  -22.7   61.8
#> 4 logEC50   Intercept  8.91   7.07  10.8