bladdercancer             package:HSAUR             R Documentation

_B_l_a_d_d_e_r _C_a_n_c_e_r _D_a_t_a

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

     Data arise from 31 male patients who have been treated for 
     superficial bladder cancer, and give the number of recurrent
     tumours during  a particular time after the removal of the primary
     tumour, along with the size of the  original tumour.

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

     data("bladdercancer")

_F_o_r_m_a_t:

     A data frame with 31 observations on the following 3 variables.

     '_t_i_m_e' the duration.

     '_t_u_m_o_r_s_i_z_e' a factor with levels '<=3cm' and '>3cm'.

     '_n_u_m_b_e_r' number of recurrent tumours.

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

     The aim is the estimate the effect of size of tumour on the number
       of recurrent tumours.

_S_o_u_r_c_e:

     G. U. H. Seeber (1998), Poisson Regression. In: _Encyclopedia of
     Biostatistics_ (P. Armitage and T. Colton, eds), John Wiley &
     Sons, Chichester.

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

       data("bladdercancer", package = "HSAUR")
       mosaicplot(xtabs(~ number + tumorsize, data = bladdercancer))

