xtabs                 package:stats                 R Documentation

_C_r_o_s_s _T_a_b_u_l_a_t_i_o_n

_D_e_s_c_r_i_p_t_i_o_n:

     Create a contingency table from cross-classifying factors, usually
     contained in a data frame, using a formula interface.

_U_s_a_g_e:

     xtabs(formula = ~., data = parent.frame(), subset, na.action,
           exclude = c(NA, NaN), drop.unused.levels = FALSE)

_A_r_g_u_m_e_n_t_s:

 formula: a formula object with the cross-classifying variables
          (separated by '+') on the right hand side (or an object which
          can be coerced to a formula).  Interactions are not allowed. 
          On the left hand side, one may optionally give a vector or a
          matrix of counts; in the latter case, the columns are
          interpreted as corresponding to the levels of a variable. 
          This is useful if the data have already been tabulated, see
          the examples below.

    data: an optional matrix or data frame (or similar: see
          'model.frame') containing the variables in the formula
          'formula'.  By default the variables are taken from
          'environment(formula)'.

  subset: an optional vector specifying a subset of observations to be
          used.

na.action: a function which indicates what should happen when the data
          contain 'NA's.

 exclude: a vector of values to be excluded when forming the set of
          levels of the classifying factors.

drop.unused.levels: a logical indicating whether to drop unused levels
          in the classifying factors.  If this is 'FALSE' and there are
          unused levels, the table will contain zero marginals, and a
          subsequent chi-squared test for independence of the factors
          will not work.

_D_e_t_a_i_l_s:

     There is a 'summary' method for contingency table objects created
     by 'table' or 'xtabs', which gives basic information and performs
     a chi-squared test for independence of factors (note that the
     function 'chisq.test' currently only handles 2-d tables).

     If a left hand side is given in 'formula', its entries are simply
     summed over the cells corresponding to the right hand side; this
     also works if the lhs does not give counts.

_V_a_l_u_e:

     A contingency table in array representation of class 'c("xtabs",
     "table")', with a '"call"' attribute storing the matched call.

_S_e_e _A_l_s_o:

     'table' for traditional cross-tabulation, and
     'as.data.frame.table' which is the inverse operation of 'xtabs'
     (see the 'DF' example below).

_E_x_a_m_p_l_e_s:

     ## 'esoph' has the frequencies of cases and controls for all levels of
     ## the variables 'agegp', 'alcgp', and 'tobgp'.
     xtabs(cbind(ncases, ncontrols) ~ ., data = esoph)
     ## Output is not really helpful ... flat tables are better:
     ftable(xtabs(cbind(ncases, ncontrols) ~ ., data = esoph))
     ## In particular if we have fewer factors ...
     ftable(xtabs(cbind(ncases, ncontrols) ~ agegp, data = esoph))

     ## This is already a contingency table in array form.
     DF <- as.data.frame(UCBAdmissions)
     ## Now 'DF' is a data frame with a grid of the factors and the counts
     ## in variable 'Freq'.
     DF
     ## Nice for taking margins ...
     xtabs(Freq ~ Gender + Admit, DF)
     ## And for testing independence ...
     summary(xtabs(Freq ~ ., DF))

     ## Create a nice display for the warp break data.
     warpbreaks$replicate <- rep(1:9, len = 54)
     ftable(xtabs(breaks ~ wool + tension + replicate, data = warpbreaks))