moprofile              package:ordinal              R Documentation

_P_r_o_d_u_c_e _M_a_r_g_i_n_a_l _O_r_d_i_n_a_l _T_i_m_e _P_r_o_f_i_l_e_s _f_o_r _P_l_o_t_t_i_n_g

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

     'mprofile' is used for plotting marginal ordinal profiles over
     time for for objects obtained from models obtained. It produces
     output for plotting highest probabilities and cumulative
     probabilities for marginal ordinal time profiles.

     See 'iprofile' for plotting individual ordinal profiles from
     recursive fitted values.

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

     plot(moprofile(z,curve.type="probability"),nind=1,observed=T,
          main=NULL,xlab=NULL,ylab=NULL,xlim=NULL,ylim=NULL,lty=NULL,
          pch=NULL,add=F,axes=F,bty="n",at=NULL,touch=F,...)

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

       z: An object of class 'lcr' or 'kalordinal' ('kalord').

curve.type: Specifies the type of curves to be plotted. Must either be
          "probability" for highest probabilities or "cumulative" for
          cumulative probabilities.

    nind: Observation number(s) of individual(s) to be plotted.

observed: If TRUE, adds the corresponding observations to the plot. If
          cumulative curves have been chosen, they are added as a
          subtitle.

    main: A main title for the plot.

    xlab: A label for the x-axis.

    ylab: A label for the y-axis.

    xlim: The x limits (min,max) of the plot.

    ylim: The y limits (min,max) of the plot.

     lty: A vector of integers or character strings specifying the line
          type to be used as the default in plotting lines. For further
          information, see 'par'.

     pch: A vector of integers or single characters specifying symbols
          to be used as the default in plotting points. For further
          information, see 'par'.

     add: If TRUE, the graph is added to an existing plot.

    axes: If FALSE, axes are not drawn around the plot.

     bty: A character string which determined the type of box which is
          drawn about plots. For further information, see 'par'.

      at: The points at which tick-marks are to be drawn. For further
          information, see 'axis'.

   touch: If TRUE, the x-axis and y-axis will touch each other.

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

     'moprofile' returns information ready for plotting by
     'plot.moprofile'.

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

     P.J. Lindsey

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

     'kalord', 'ioprofile', 'lcr', 'plot.ordinal', 'poprofile'.

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

     library(ordinal)

     #
     # Binary data
     #
     data(cardiac.indiv)

     y <- restovec(cardiac.indiv[,1:4],type="ordinal")

     cov <- tcctomat(as.matrix(cardiac.indiv[,5:10]))

     w <- rmna(y,ccov=cov)

     rm(cardiac.indiv,y,cov)

     # Time-constant and time-varying covariate with a frailty dependence.
     z <- kalord(w,distribution="binary",mu=~age+ren+cop+dia+sex+pmi+times,
                 ptvc=c(4.43357,-0.03128,-0.62602,-0.37679,-0.32969,-0.17013,
                        -0.12209,-0.09095),pinit=0.1196,dep="frailty")

     # Cumulative probability profiles.
     par(mfrow=c(2,2))
     plot(moprofile(z,"cum"),nind=1)
     plot(moprofile(z,"cum"),nind=117)
     plot(moprofile(z,"cum"),nind=c(1000,3000),add=T)
     par(mfrow=c(1,1))

     # Highest probability profiles.
     par(mfrow=c(2,2))
     plot(moprofile(z,"prob"),nind=2000)
     plot(moprofile(z,"prob"),nind=3001)
     plot(moprofile(z,"prob"),nind=c(3506,3521))
     plot(moprofile(z,"prob"),nind=400)
     par(mfrow=c(1,1))

     rm(w,z)

     #
     # Ordinal data
     #
     data(obese)

     resp <- cbind(codes(obese[,1])-1,codes(obese[,2])-1)
     freq <- obese[,4]

     age <- obese[,3]

     rm(obese)

     y <- restovec(resp,times=1:2,weights=freq,type="ordinal")

     tcc <- tcctomat(age,name="age")

     tvc <- tvctomat(matrix(times(y)^2,ncol=2),name="times2")

     w <- rmna(y,ccov=tcc,tvcov=tvc)

     rm(resp,freq,age,y,tcc,tvc)

     z <- lcr(w,mu=~age*times+times2)

     # Cumulative probability profiles.
     par(mfrow=c(2,2))
     plot(moprofile(z,"cum"),nind=1)
     plot(moprofile(z,"cum"),nind=4)
     plot(moprofile(z,"cum"),nind=8:9,add=T)
     par(mfrow=c(1,1))

     # Highest probability profiles.
     par(mfrow=c(2,2))
     plot(moprofile(z,"prob"),nind=1)
     plot(moprofile(z,"prob"),nind=4)
     plot(moprofile(z,"prob"),nind=c(8,9))
     plot(moprofile(z,"prob"),nind=16)
     par(mfrow=c(1,1))

     rm(w,z)

