birthwt                 package:MASS                 R Documentation

_R_i_s_k _F_a_c_t_o_r_s _A_s_s_o_c_i_a_t_e_d _w_i_t_h _L_o_w _I_n_f_a_n_t _B_i_r_t_h _W_e_i_g_h_t

_D_e_s_c_r_i_p_t_i_o_n:

     The 'birthwt' data frame has 189 rows and 10 columns. The data
     were collected at Baystate Medical Center, Springfield, Mass
     during 1986.

_U_s_a_g_e:

     data(birthwt)

_F_o_r_m_a_t:

     This data frame contains the following columns:

     '_l_o_w' indicator of birth weight less than 2.5kg

     '_a_g_e' mother's age in years

     '_l_w_t' mother's weight in pounds at last menstrual period

     '_r_a_c_e' mother's race ('1' = white, '2' = black, '3' = other)

     '_s_m_o_k_e' smoking status during pregnancy

     '_p_t_l' number of previous premature labours

     '_h_t' history of hypertension

     '_u_i' presence of uterine irritability

     '_f_t_v' number of physician visits during the first trimester

     '_b_w_t' birth weight in grams

_S_o_u_r_c_e:

     Hosmer, D.W. and Lemeshow, S. (1989) _Applied Logistic
     Regression._ New York: Wiley

_R_e_f_e_r_e_n_c_e_s:

     Venables, W. N. and Ripley, B. D. (2002) _Modern Applied
     Statistics with S._ Fourth edition.  Springer.

_E_x_a_m_p_l_e_s:

     attach(birthwt)
     race <- factor(race, labels = c("white", "black", "other"))
     ptd <- factor(ptl > 0)
     ftv <- factor(ftv)
     levels(ftv)[-(1:2)] <- "2+"
     bwt <- data.frame(low = factor(low), age, lwt, race,
         smoke = (smoke > 0), ptd, ht = (ht > 0), ui = (ui > 0), ftv)
     detach("birthwt")
     options(contrasts = c("contr.treatment", "contr.poly"))
     glm(low ~ ., binomial, bwt)

