smi                 package:mitools                 R Documentation

_M_u_l_t_i_p_l_e _i_m_p_u_t_a_t_i_o_n_s

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

     An 'imputationList' object containing five imputations of data
     from the Victorian Adolescent Health Cohort Study.

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

     data(smi)

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

     The underlying data are in a data frame with 1170 observations on
     the following 12 variables.

     _i_d a numeric vector

     _w_a_v_e a numeric vector

     _m_m_e_t_r_o a numeric vector

     _p_a_r_s_m_k a numeric vector

     _d_r_k_f_r_e a factor with levels 'Non drinker' 'not in last wk' '<3
          days last wk' '>=3 days last wk'

     _a_l_c_d_o_s a factor with levels 'Non drinker' 'not in last wk' 'av
          <5units/drink_day' 'av =>5units/drink_day'

     _a_l_c_d_h_i a numeric vector

     _s_m_k a factor with levels 'non/ex-smoker' '<6 days' '6/7 days'

     _c_i_s_t_o_t a numeric vector

     _m_d_r_k_f_r_e a numeric vector

     _s_e_x a numeric vector

     _d_r_i_n_k_r_e_g a logical vector

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

     Carlin, JB, Li, N, Greenwood, P, Coffey, C. (2003) "Tools for
     analysing multiple imputed datasets" The Stata Journal 3; 3: 1-20.

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

     data(smi)
     with(smi, table(sex, drkfre))
     model1<-with(smi, glm(drinkreg~wave*sex, family=binomial()))
     MIcombine(model1)
     summary(MIcombine(model1))

