model.extract             package:stats             R Documentation

_E_x_t_r_a_c_t _C_o_m_p_o_n_e_n_t_s _f_r_o_m _a _M_o_d_e_l _F_r_a_m_e

_D_e_s_c_r_i_p_t_i_o_n:

     Returns the response, offset, subset, weights or other special
     components of a model frame passed as optional arguments to
     'model.frame'.

_U_s_a_g_e:

     model.extract(frame, component)
     model.offset(x)
     model.response(data, type = "any")
     model.weights(x)

_A_r_g_u_m_e_n_t_s:

frame, x, data: A model frame.

component: literal character string or name. The name of a component to
          extract, such as '"weights"', '"subset"'.

    type: One of '"any"', '"numeric"', '"double"'. Using the either of
          latter two coerces the result to have storage mode
          '"double"'.

_D_e_t_a_i_l_s:

     'model.extract' is provided for compatibility with S, which does
     not have the more specific functions.  It is also useful to
     extract e.g. the 'etastart' and 'mustart' components of a 'glm'
     fit.

     'model.offset' and 'model.response' are equivalent to
     'model.extract(, "offset")' and 'model.extract(, "response")'
     respectively.  'model.offset' sums any terms specified by 'offset'
     terms in the formula or by 'offset' arguments in the call
     producing the model frame: it does check that the offset is
     numeric.

     'model.weights' is slightly different from 'model.frame(,
     "weights")' in not naming the vector it returns.

_V_a_l_u_e:

     The specified component of the model frame, usually a vector.

_S_e_e _A_l_s_o:

     'model.frame', 'offset'

_E_x_a_m_p_l_e_s:

     a <- model.frame(cbind(ncases,ncontrols) ~ agegp+tobgp+alcgp, data=esoph)
     model.extract(a, "response")
     stopifnot(model.extract(a, "response") == model.response(a))

     a <- model.frame(ncases/(ncases+ncontrols) ~ agegp+tobgp+alcgp,
                      data = esoph, weights = ncases+ncontrols)
     model.response(a)
     model.extract(a, "weights")

     a <- model.frame(cbind(ncases,ncontrols) ~ agegp,
                      something = tobgp, data = esoph)
     names(a)
     stopifnot(model.extract(a, "something") == esoph$tobgp)

