ChickWeight               package:nls               R Documentation

_W_e_i_g_h_t _v_e_r_s_u_s _a_g_e _o_f _c_h_i_c_k_s _o_n _d_i_f_f_e_r_e_n_t _d_i_e_t_s

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

     The `ChickWeight' data frame has 578 rows and 4 columns from an
     experiment on the effect of diet on early growth of chicks.

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

     This data frame contains the following columns:

     _w_e_i_g_h_t a numeric vector giving the body weight of the
            chick (gm).

     _T_i_m_e a numeric vector giving the number of days since
            birth when the measurement was made.

     _C_h_i_c_k an ordered factor with levels `18' < ...{} < `48'
            giving a unique identifier for the chick.  The ordering of
            the levels groups chicks on the same diet together and
            orders them according to their final weight (lightest to
            heaviest) within diet.

     _D_i_e_t a factor with levels 1,...{},4 indicating which
            experimental diet the chick received.

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

     The body weights of the chicks were measured at birth and every
     second day thereafter until day 20.  They were also measured on
     day 21.  There were four groups on chicks on different protein
     diets.

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

     Crowder, M. and Hand, D. (1990), Analysis of Repeated Measures,
     {Chapman and Hall} (example 5.3)

     Hand, D. and Crowder, M. (1996), Practical Longitudinal Data
     Analysis, Chapman and Hall (table A.2)

     Pinheiro, J. C. and Bates, D. M. (2000) Mixed-effects Models in S
     and S-PLUS, Springer.

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

     library(nls)
     data(ChickWeight)
     coplot(weight ~ Time | Chick, data = ChickWeight,
         type = "b", show = FALSE)
     ## fit a representative chick
     fm1 <- nls(weight ~ SSlogis( Time, Asym, xmid, scal ),
         data = ChickWeight, subset = Chick == 1)
     summary( fm1 )

