multcompTs           package:multcompView           R Documentation

"_T" _d_e_p_i_c_t_i_o_n _o_f _u_n_d_i_f_f_e_n_t_i_a_t_e_d _c_l_a_s_s_e_s

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

     Convert a logical vector or a vector of p-values or a correlation
     or distance matrix into a matrix with an associated visual display
     to show whether the differences between items exceed a threshold. 
     Designed for use with the output of functions like TukeyHSD,
     dist{stats}, simint, simtest, csimint, csimtest{multcomp},
     friedmanmc, kruskalmc{pgirmess}.

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

       multcompTs(x, compare="<", threshold=0.05,
                            sep=".")

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

       x: One of the following: (1) A square, symmetric matrix with row
          names. (2) A vector with hyphenated names, which identify
          individual items or factor levels after "strsplit(..., '-')".
            (3) An object of class "dist".

          If x (or x[1]) is not already of class "logical", it is
          replaced with do.call(compare, list(x, threshold)), which by
          default converts numbers (typically p-values) less than 0.05
          to TRUE and everything else to FALSE.  If x is a matrix, its
          diagonal must be or must convert to FALSE.   

 compare: function or binary operator;  not used if class(x) is
          "logical".   

threshold: Second (reference) argument to "compare".   

     sep: Concatonation character for names of objects with identical
          similarity / dissimilarity patterns. The output of multcompTs
          is matrix for which the number of rows = (number of columns +
          number of uses of the "sep" character).   

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

     Produces a matrix of class "multcompTs", describing the
     "undifferentiated classes" that identify the other factor levels
     or items that are not distinct or not significantly different from
     the "base" of the "T";  if two or more levels have the same
     pattern of significant differences, the two are combined into one
     "T" with two "bases".  The resulting T's are similar to the
     "undifferentiated classes" discussed by Donaghue (2004).

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

     An object of class "multcompTs", which is a matrix of values {-1,
     0, 1}, with one row for each level compared and one column for
     each "T", read as follows:   1 = base of the "T" represented by
     that column, 0 = level(s) not significantly different, and (-1) =
     leves(s) significantly different. If two or more levels have the
     same pattern of significant and insignificant differences, they
     are combined into a single column that can be represented by a "T"
     with multiple bases.  The column name will be a character string
     concatonating all row names with "1" in that column separated by
     the "sep" character.  Thus, the matrix should have as many 1's as
     it has rows.  Also, the lower triangular portion should have as
     many "-1's" as there are "TRUE" (e.g., significant) differences
     among the comparisons.

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

     Spencer Graves and Hans-Peter Piepho

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

     John R. Donaghue (2004) "Implementing Shaffer's multiple
     comparison procedure for a large number of groups", pp. 1-23 in
     Benjamini, Bretz and Sarkar (eds) Recent Developments in Multiple
     Comparison Procedures (Institute of Mathematical Statistics
     Lecture Notes-Monograph Series vol. 47)

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

     'multcompBoxplot'  'multcompLetters'  'plot.multcompTs' 'vec2mat'

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

     dif3 <- c(FALSE, FALSE, TRUE)
     names(dif3) <- c("a-b", "a-c", "b-c")
     multcompTs(dif3)

     dif4 <- c(.01, .02, .03, 1)
     names(dif4) <- c("a-b", "a-c", "b-d", "a-d")
     (diff4.T <- multcompTs(dif4))
     plot(diff4.T)

