esoph                package:datasets                R Documentation

_S_m_o_k_i_n_g, _A_l_c_o_h_o_l _a_n_d (_O)_e_s_o_p_h_a_g_e_a_l _C_a_n_c_e_r

_D_e_s_c_r_i_p_t_i_o_n:

     Data from a case-control study of (o)esophageal cancer in
     Ile-et-Vilaine, France.

_U_s_a_g_e:

     esoph

_F_o_r_m_a_t:

     A data frame with records for 88 age/alcohol/tobacco combinations.

       [,1]  "agegp"      Age group            1  25-34 years
                                               2  35-44
                                               3  45-54
                                               4  55-64
                                               5  65-74
                                               6  75+
       [,2]  "alcgp"      Alcohol consumption  1   0-39 gm/day
                                               2  40-79
                                               3  80-119
                                               4  120+
       [,3]  "tobgp"      Tobacco consumption  1   0- 9 gm/day
                                               2  10-19
                                               3  20-29
                                               4  30+
       [,4]  "ncases"     Number of cases      
       [,5]  "ncontrols"  Number of controls   

_A_u_t_h_o_r(_s):

     Thomas Lumley

_S_o_u_r_c_e:

     Breslow, N. E. and Day, N. E. (1980) _Statistical Methods in
     Cancer Research. 1: The Analysis of Case-Control Studies._  IARC
     Lyon / Oxford University Press.

_E_x_a_m_p_l_e_s:

     require(stats)
     require(graphics) # for mosaicplot
     summary(esoph)
     ## effects of alcohol, tobacco and interaction, age-adjusted
     model1 <- glm(cbind(ncases, ncontrols) ~ agegp + tobgp * alcgp,
                   data = esoph, family = binomial())
     anova(model1)
     ## Try a linear effect of alcohol and tobacco
     model2 <- glm(cbind(ncases, ncontrols) ~ agegp + unclass(tobgp)
                                              + unclass(alcgp),
                   data = esoph, family = binomial())
     summary(model2)
     ## Re-arrange data for a mosaic plot
     ttt <- table(esoph$agegp, esoph$alcgp, esoph$tobgp)
     ttt[ttt == 1] <- esoph$ncases
     tt1 <- table(esoph$agegp, esoph$alcgp, esoph$tobgp)
     tt1[tt1 == 1] <- esoph$ncontrols
     tt <- array(c(ttt, tt1), c(dim(ttt),2),
                 c(dimnames(ttt), list(c("Cancer", "control"))))
     mosaicplot(tt, main = "esoph data set", color = TRUE)

