drfit                 package:drfit                 R Documentation

_F_i_t _d_o_s_e-_r_e_s_p_o_n_s_e _m_o_d_e_l_s

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

     Fit dose-response relationships to dose-response data and
     calculate biometric results for (eco)toxicity evaluation

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

       drfit(data, startlogEC50 = NA, chooseone = TRUE, probit = TRUE, logit = FALSE,
         weibull = FALSE, linlogit = FALSE, linlogitWrong = NA, allWrong = NA, 
         s0 = 0.5, b0 = 2, f0 = 0)

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

    data: A data frame containing dose-response data. The data frame
          has to contain at least a factor called "substance", a vector
          called "unit" containing the unit used for the dose, a column
          "response" with the response values of the test system
          normalized between 0 and 1 and a column "dose" with the
          numeric dose values. Such a data frame can be easily obtained
          if a compliant RODBC data source is available for use in
          conjunction with  the function 'drdata'.  

          If there is a column called "ok" and it is set to "no fit" in
          a specific line, then the corresponding data point will be
          excluded from the fitting procedure, although it will be
          plotted. 

startlogEC50: Especially for the linlogit model, a suitable log10 of
          the EC50 has to be given  by the user, since it is not
          correctly estimated for data showing hormesis with the
          default estimation method.

  probit: A boolean defining if cumulative density curves of normal
          distributions 'pnorm' are fitted against the decadic
          logarithm of the dose. Default ist TRUE.

   logit: A boolean defining if cumulative density curves of logistic
          distributions 'plogis' are fitted to the decadic logarithm of
          the dose. Default is FALSE.

 weibull: A boolean defining if the cumulative density curves of
          weibull distributions ('pweibull' with additionall location
          parameter and scale=1) are fitted to the decadic logarithm of
          the dose. Default is FALSE.

linlogit: A boolean defining if the linear-logistic function
          'linlogitf' as defined by van Ewijk and Hoekstra 1993 is
          fitted to the data. Default is FALSE.

linlogitWrong: An optional vector containing the names of the
          substances for which the linlogit function produces a wrong
          fit.

allWrong: An optional vector containing the names of the substances for
          which all functions produce a wrong fit.

chooseone: If TRUE (default), the models are tried in the order
          linlogit, probit, logit, weibull, and the first model that
          produces a valid fit is used. If FALSE, all models that are
          set to TRUE and that can be fitted will be reported.

      s0: If the weibull model is fitted, s0 gives the possibility to
          adjust the starting value for the shape parameter of
          'pweibull'.

   b0,f0: If the linearlogistic model is fitted, b0 and f0 give the
          possibility to adjust the starting values for the parameters
          b and f.

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

 results: A data frame containing at least one line for each substance.
          If the data did not show a mean response < 0.5 at the highest
          dose level, the modeltype is set to "none". Every successful
          fit is reported in one line. Parameters of the fitted curves
          are only reported if the fitted EC50 is not higher than the
          highest dose.  'n' is the number of dose-response curves in
          the raw data (repetitions in each point), 'lld' is the
          decadic logarithm of the lowest dose and 'lhd' is the decadic
          logarithm of the highest dose. For the "linlogit", "logit"
          and "probit" models, the parameter 'a' that is reported
          coincides with the logEC50, i.e the logEC50 is  one of the
          model parameters that is being fitted, and therefore a
          standard deviation 'std' is reported for the logEC50. In the 
          case of the "weibull" model, 'a' is a location parameter.
          Parameter 'b' in the case of the "linlogit" fit is the
          variable b from the 'linlogitf' function. In the case of
          "probit" fit it is the standard deviation of the fitted
          normal distribution, in the case of the "logit" fit it is the
          'scale' parameter in the 'plogis' function, and in the
          "weibull" fit it is the 'shape' parameter of the fitted
          'pweibull' function. Only the "linlogit" fit produces a 
          third parameter 'c' which is the variable f from the
          'linlogitf' function.

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

     Johannes Ranke  jranke@uni-bremen.de  <URL:
     http://www.uft.uni-bremen.de/chemie/ranke>

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

     data(antifoul)
     r <- drfit(antifoul)
     format(r,digits=2)

