

Contrast {base}                              R Documentation

_C_o_n_t_r_a_s_t _M_a_t_r_i_c_e_s

_U_s_a_g_e_:

     contr.helmert(n, contrasts=TRUE)
     contr.poly(n, contrasts=TRUE)
     contr.sum(n, contrasts=TRUE)
     contr.treatment(n, base=1, contrasts=TRUE)

_V_a_l_u_e_:

     A matrix with `n' rows and `k' columns, with `k=n-1' if
     `contrasts' is `TRUE' and `k=n' if `contrasts' is
     `FALSE'.

     The base argument to `contr.treatment()' allows you to
     specify which group is considered the baseline group.

     These functions are used for creating contrast matrices
     for use in fitting analysis of variance and regression
     models.  The columns of the resulting matrices contain
     contrasts which can be used for coding a factor with
     `n' levels.  The returned value contains the computed
     contrasts.  If the argument `contrasts' is `FALSE' then
     an additional column of ones is prepended to the
     matrix.

     Note that as from R version 0.62.2, `contr.poly'
     returns contrasts based on orthogonal (rather than raw)
     polynomials.

_S_e_e _A_l_s_o_:

     `contrasts', `C', and `aov', `glm', `lm'.

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

     (cH <- contr.helmert(4))
     apply(cH, 2,sum)# column sums are 0!
     crossprod(cH)# diagonal -- columns are orthogonal

     (cT <- contr.treatment(5))
     all(crossprod(cT) == diag(4))# TRUE: even orthonormal

     (cP <- contr.poly(3))# Linear and Quadratic
     zapsmall(crossprod(cP), dig=15) # orthonormal up to fuzz

