poly3ci                package:MCPAN                R Documentation

_S_i_m_u_l_t_a_n_e_o_u_s _c_o_n_f_i_d_e_n_c_e _i_n_t_e_r_v_a_l_s _f_o_r _c_o_n_t_r_a_s_t_s _o_f _p_o_l_y-_3-_a_d_j_u_s_t_e_d _t_u_m_o_u_r _r_a_t_e_s

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

     Function to calculate simultaneous confidence intervals for
     several contrasts of poly-3-adjusted tumour rates in a oneway
     layout. Assuming a data situation as in Peddada(2005) or Bailer
     and Portier (1988). Simultaneous asymptotic CI for contrasts of
     tumour rates, assuming that standard normal approximation holds.

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

     poly3ci(time, status, f, type = "Dunnett", cmat = NULL, method = "BP", alternative = "two.sided", conf.level = 0.95)

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

    time: a numeric vector of times of death of the individuals

  status: a logical (or numeric, consisting of 0,1 only) vector giving
          the tumour status at time of death of each individual, where
          TRUE (1) = tumour present, FALSE (0) = no tumour present  

       f: a factor, giving the classification variable 

    type: a character string, giving the name of a contrast method, as
          defined in 'contrMat(multcomp)' 

    cmat: a optional contrast matrix 

  method: a single charcter string, specifying the method for
          adjustment, with options: "BP" (Bailer Portier: assuming
          poly-3-adjusted rates are binomial variables), "BW" (Bieler,
          Williams: delta method as in Bieler and Williams (1993))
          "ADD1" (as Bailer Portier, including an add1-adjustment on
          the raw tumour rates) "ADD2" (as Bailer Portier, including an
          add2-adjustment on the raw tumour rates following Agresti and
          Caffo (2000) for binomials) 

alternative: a single character string 

conf.level: a single numeric value, simultaneous confidence level 

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

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

     A object of class "poly3ci", a list containing: 

conf.int : a matrix with 2 columns: lower and upper confidence bounds,
          and M rows

alternative : character string, as input

conf.level: single numeric value, as input

estimate: a numeric vector with the point estimates of the contrasts

    time: as input

  status: as input

       f: as input

  method: as input

    cmat: as input, with colnames= factor levels of f

sample.est: a list containing sample estimates

_N_o_t_e:

     Please note that all methods here described are only
     approximative, and might violate the nominal level in certain
     situations. Please note further that appropriateness of the point
     estimates, and consequently of tests and confidence intervals is
     based on the assumptions in Bailer and Portier (1988), which might
     be a matter of controversies.

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

     Frank Schaarschmidt

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

     Assumption for poly-3-adjustment: Bailer, J.A. and Portier, C.J.
     (1988): Effects of treatment-induced mortality and tumor-induced
     mortality on tests for carcinogenicity in small samples.
     Biometrics 44, 417-431.

     Peddada, S.D., Dinse, G.E., and Haseman, J.K. (2005): A
     survival-adjusted quantal response test for comparing tumor
     incidence rates. Applied Statistics 54, 51-61.

     Bieler, G.S. and Williams, R.L. (1993): Ratio estimates, the Delta
     Method, and quantal response tests for increased carcinogenicity.
     Biometrics 49, 793-801.

     Statistical procedures and characterization of coverage
     probabilities are described in: Sill, M. (2007): .... Master
     thesis, Institute of Biostatistics, Leibniz University Hannover.

     Agresti, A. and Caffo, B.(2000): Simple and effective confidence
     intervals for proportions and differences of proportions result
     from adding two successes and two failures. American Statistician
     54, p. 280-288.

_S_e_e _A_l_s_o:

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

     data(methyl)
     methylD<-poly3ci(time=methyl$death, status=methyl$tumour, f=methyl$group, type = "Dunnett", method = "ADD1" )
     methylD
     plot(methylD, main="Simultaneous CI for Poly-3-adjusted tumour rates")

