Add or remove a covariate term from an Emax regression
Usage
emax_add_term(object, formula, quiet = FALSE)
emax_remove_term(object, formula, quiet = FALSE)Examples
mod_0 <- emax_nls(response_1 ~ exposure_1, list(E0 ~ 1, Emax ~ 1, logEC50 ~ 1), emax_df)
mod_1 <- emax_nls(response_1 ~ exposure_1, list(E0 ~ cnt_a, Emax ~ 1, logEC50 ~ 1), emax_df)
emax_add_term(mod_0, E0 ~ cnt_a)
#> Structural model:
#>
#> Exposure: exposure_1
#> Response: response_1
#> Emax type: hyperbolic
#>
#> Covariate model:
#>
#> E0: E0 ~ 1 + cnt_a
#> Emax: Emax ~ 1
#> logEC50: logEC50 ~ 1
#>
#> Coefficient table:
#>
#> label estimate std_error t_statistic p_value ci_lower ci_upper
#> 1 E0_Intercept 4.99 0.0740 67.5 3.21e-219 4.85 5.14
#> 2 E0_cnt_a 0.498 0.0113 44.2 4.30e-155 0.476 0.520
#> 3 Emax_Intercept 10.0 0.104 96.3 7.23e-277 9.80 10.2
#> 4 logEC50_Intercept 8.27 0.0366 226. 0 8.19 8.34
#>
#> Variance-covariance matrix:
#>
#> E0_Intercept E0_cnt_a Emax_Intercept logEC50_Intercept
#> E0_Intercept 0.00548 -6.2e-04 -2.2e-03 4.3e-04
#> E0_cnt_a -0.00062 1.3e-04 4.2e-05 2.5e-05
#> Emax_Intercept -0.00224 4.2e-05 1.1e-02 2.6e-03
#> logEC50_Intercept 0.00043 2.5e-05 2.6e-03 1.3e-03
emax_remove_term(mod_1, E0 ~ cnt_a)
#> Structural model:
#>
#> Exposure: exposure_1
#> Response: response_1
#> Emax type: hyperbolic
#>
#> Covariate model:
#>
#> E0: E0 ~ 1
#> Emax: Emax ~ 1
#> logEC50: logEC50 ~ 1
#>
#> Coefficient table:
#>
#> label estimate std_error t_statistic p_value ci_lower ci_upper
#> 1 E0_Intercept 7.41 0.121 61.0 7.36e-204 7.17 7.65
#> 2 Emax_Intercept 9.84 0.244 40.3 1.80e-142 9.37 10.3
#> 3 logEC50_Intercept 8.17 0.0904 90.3 8.34e-267 7.98 8.34
#>
#> Variance-covariance matrix:
#>
#> E0_Intercept Emax_Intercept logEC50_Intercept
#> E0_Intercept 0.0147 -0.012 0.0032
#> Emax_Intercept -0.0124 0.060 0.0146
#> logEC50_Intercept 0.0032 0.015 0.0082