glucose                 package:ggm                 R Documentation

_G_l_u_c_o_s_e _c_o_n_t_r_o_l

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

     Data on glucose control of diabetes patients.

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

     data(glucose)

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

     A data frame with 68 observations on the following 8 variables.

     _Y a numeric vector, Glucose control (glycosylated haemoglobin),
          values up to about 7 or 8 indicate good glucose control.

     _X a numeric vector, a score for knowledge about the illness.

     _Z a numeric vector, a score for fatalistic externality (mere
          chance determines what occurs).

     _U a numeric vector, a score for social externality (powerful
          others are responsible).

     _V a numeric vector, a score for internality (the patient is him or
          herself responsible).

     _W a numeric vector, duration of the illness in years.

     _A a factor, level of education, with levels '1': at least 13 years
          of formal schooling, '2': less then 13 years.

     _B a factor, gender with levels '1': females, '2': males.

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

     Data on 68 patients with fewer than 25 years of diabetes. They
     were collected at the University of Mainz to identify
     psychological and socio-economic variables possibly important for
     glucose control, when patients choose the appropriate dose of
     treatment depending on the level of blood glucose measured several
     times per day.

     The variable   of primary interest is 'Y', glucose control,
     measured by  glycosylated haemoglobin. 'X', knowledge about the
     illness, is a response of secondary interest. Variables 'Z', 'U'
     and 'V' measure patients' type of attribution, called fatalistic
     externality, social externality and internality. These are
     intermediate variables. Background   variables are 'W', the
     duration of the illness, 'A' the duration of formal schooling and
     'B', gender. These are intrinsic variables.

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

     Cox & Wermuth (1996), p. 229.

_R_e_f_e_r_e_n_c_e_s:

     Cox, D. R. & Wermuth, N. (1996). _Multivariate dependencies_.
     London: Chapman & Hall.

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

     data(glucose)
     ## See Cox & Wermuth (1996), Figure 6.3 p. 140
     coplot(Y ~ W | A, data=glucose)

