modelFit                 package:drc                 R Documentation

_C_h_e_c_k_i_n_g _t_h_e _m_o_d_e_l _f_o_t

_D_e_s_c_r_i_p_t_i_o_n:

     Checking the fit of dose-response model by means of formal
     lack-of-fit tests or graphical procedures.

_U_s_a_g_e:

       modelFit(object, test = NULL, method = c("gof", "cum"))

_A_r_g_u_m_e_n_t_s:

  object: object of class 'drc'

    test: character string defining the test method to apply

  method: character string specifying the method to be used for
          assessing the model fit

_D_e_t_a_i_l_s:

     Currently two methods are available. For continuous data the
     clasical lack-of-fit test is applied  (Bates and Watts, 1988). The
     test compares the dose-response model to a more general ANOVA
     model using an approximate F-test. For quantal data the crude 
     goodness-of-fit test based on Pearson's statistic is used. None of
     these tests are very powerful. A significant test result is more
     alarming than a non-significant one. 

     More methods will become available in the future.

_V_a_l_u_e:

     An object of class 'anova' which will be displayed in much the
     same way as an ordinary ANOVA table.

_A_u_t_h_o_r(_s):

     Christian Ritz

_R_e_f_e_r_e_n_c_e_s:

     Bates, D. M. and Watts, D. G. (1988)  _Nonlinear Regression
     Analysis and Its Applications_,  New York: Wiley & Sons (pp.
     103-104).

_E_x_a_m_p_l_e_s:

     ## Comparing the four-parameter log-logistic model to a one-way ANOVA model using an approximate F test
     ## in other words applying a lack-of-fit test
     ryegrass.m1 <- drm(rootl ~ conc, data = ryegrass, fct = W1.4())
     modelFit(ryegrass.m1)   

