hiv                  package:Icens                  R Documentation

_I_n_t_e_r_v_a_l_s _f_o_r _i_n_f_e_c_t_i_o_n _t_i_m_e _a_n_d _d_i_s_e_a_s_e _o_n_s_e_t _f_o_r _2_5_7
_h_e_m_o_p_h_i_l_i_a_c _p_a_t_i_e_n_t_s.

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

     The 'hiv' data frame has 257 rows and 4 columns.

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

     This data frame contains the following columns:

     _y_L The left end point of the infection time interval.

     _y_R The right end point of the infection time interval.

     _z_L The left end point of the disease onset interval.

     _z_R The right end point of the disease onset interval.

     _A_g_e Coded as 1 if the estimated age at infection was less than 20 
          and 2 if the estimated age at infection was greater than 20.

     _T_r_t Treatment, Light or Heavy

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

     The setting is as follows. Individuals were infected with the HIV
     virus at some unknown time they subsequently develop AIDS at a
     second unknown time. The data consist of two intervals, (y_L, y_R)
     and (z_L,z_R), such that the infection time was in the first
     interval and the time of disease onset was in the second interval.
     A quantity of interest is the incubation time of the disease which
     is T=Z-Y. The authors argue persuasively that this should be
     considered as bivariate interval censored data. They note that
     simply forming the differences (z_L-y_R, z_R-y_L) and analysing
     the resultant data assumes an incorrect likelihood. DeGruttola and
     Lagakos transform the problem slightly to study the joint
     distribution of Y and T=Z-Y. This is equivalent to estimating the
     joint distribution of Z and Y then transforming. The data, as
     reported, have been discretized into six month intervals.

     We use the data as reported in Table 1 of DeGruttola and Lagakos,
     1989. The patients were 257 persons with Type A or B hemophilia
     treated at two hospitals in France. They were then examined
     intermittently (as they came in for treatment?) and their HIV and
     AIDS status was determined. Kim, De Gruttola and Lagakos report
     some covariate information and their paper is concerned with the
     modeling of that information. In this paper we concentrate only on
     the event times and ignore the covariate information; that topic
     being worthy of separate investigation.

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

     DeGruttola, V. and Lagakos, S.W., 1989, _Analysis of
     doubly-censored survival data, with application to {AIDS}_,
     Biometrics.

     Kim, Mimi Y. and De Gruttola, Victor G. and Lagakos, Stephen W.,
     1993, _Analyzing Doubly Censored Data With Covariates, With
     Application to  AIDS_, Biometrics.

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

     data(hiv)

