isBalanced               package:nlme               R Documentation

_C_h_e_c_k _a _D_e_s_i_g_n _f_o_r _B_a_l_a_n_c_e

_D_e_s_c_r_i_p_t_i_o_n:

     Check the design of the experiment or study for balance.

_U_s_a_g_e:

     isBalanced(object, countOnly, level)

_A_r_g_u_m_e_n_t_s:

  object: A 'groupedData' object containing a data frame and a formula
          that describes the roles of variables in the data frame.  The
          object will have one or more nested grouping factors and a
          primary covariate.

countOnly: A logical value indicating if the check for balance should
          only consider the number of observations at each level of the
          grouping factor(s).  Defaults to 'FALSE'.

   level: an optional integer vector specifying the desired prediction
          levels. Levels increase from outermost to innermost grouping,
          with level 0 representing the population (fixed effects)
          predictions. Defaults to the innermost level.

_D_e_t_a_i_l_s:

     A design is balanced with respect to the grouping factor(s) if
     there are the same number of observations at each distinct value
     of the grouping factor or each combination of distinct levels of
     the nested grouping factors.  If 'countOnly' is 'FALSE' the design
     is also checked for balance with respect to the primary covariate,
     which is often the time of the observation.  A design is balanced
     with respect to the grouping factor and the covariate if the
     number of observations at each distinct level (or combination of
     levels for nested factors) is constant and the times at which the
     observations are taken (in general, the values of the primary
     covariates) also are constant.

_V_a_l_u_e:

     'TRUE' or 'FALSE' according to whether the data are balanced or
     not

_A_u_t_h_o_r(_s):

     Jose Pinheiro Jose.Pinheiro@pharma.novartis.com and Douglas Bates
     bates@stat.wisc.edu

_S_e_e _A_l_s_o:

     'table', 'groupedData'

_E_x_a_m_p_l_e_s:

     data(Orthodont)
     isBalanced(Orthodont)                    # should return TRUE
     isBalanced(Orthodont, countOnly = TRUE)  # should return TRUE
     data(Pixel)
     isBalanced(Pixel)                        # should return FALSE
     isBalanced(Pixel, level = 1)             # should return FALSE

