eval.blockdesign          package:AlgDesign          R Documentation

_E_v_a_l_u_a_t_e_s _a _b_l_o_c_k_e_d _d_e_s_i_g_n.

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

     A blocked design is evaluated.

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

     eval.blockdesign(frml,design,blocksizes,rho=1,confounding=FALSE,center=FALSE)

_A_r_g_u_m_e_n_t_s:

    frml: The formula used to create the blocked design.

  design: The blocked design, which may be the design output by
          optBlock().

blocksizes: A vector of blocksizes for the design.

     rho: A vector, giving the ratios of whole to within variance
          components.

confounding: If confounding=TRUE, the confounding matrix will be
          output.

  center: If TRUE, numeric variables will be centered before frml is
          applied.

_V_a_l_u_e:

confounding: A matrix based on the design matrix in which the within
          block variables have been centered about their block means.
          The columns of this matrix which give  the regression
          coefficients of each variable regressed on the others. If C
          is the  confounding matrix, then -XC is a matrix of residuals
          of the variables regressed on  the other variables.

determinant.all.terms.within.terms.centered: (det(M)^(1/k), where 
          M=X'X/N and X is the model expanded N x k design matrix  in
          which the within block variables     have been centered about
          the grand mean.

within.block.efficiencies: The determinant criterion blocking
          efficiencies for the range  of rho's input. A high efficiency
          indicates that there is little intrablock information to be
          recovered in the analysis.

block.centered.properties: A matrix with four rows. The columns
          correspond to constant, whole block terms and within block
          terms:

             1.  The degrees of freedom for terms in the expanded
                model.  

             2.  The determinant of the block centered within block
                terms.  

             3.  The geometric mean of the block centered variances.  

             4.  The geometric mean of the ratio of centered to block
                centered variances. 

_A_u_t_h_o_r(_s):

     Bob Wheeler bwheeler@echip.com

     Please cite this program as follows:

     Wheeler, R.E. (2004). eval.blockdesign. _AlgDesign_. The R project
     for statistical computing <URL: http://www.r-project.org/>

