xtabs                  package:base                  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, subset, na.action, exclude = c(NA, NaN),
           drop.unused.levels = FALSE)
     summary.xtabs(object, ...)

_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.  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 has already beed
          tabulated, see the examples below.

    data: a data frame, list or environment containing the variables to
          be cross-tabulated.

  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 `xtabs', which currently gives basic information and performs a
     chi-squared test for independence of factors (note that the
     function `chisq.test' in package ctest currently only handles 2-d
     tables).

_V_a_l_u_e:

     A contingency table in array representation of class `"xtabs"',
     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:

     data(esoph)
     ## `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))

     data(UCBAdmissions)
     ## 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 independece ...
     summary(xtabs(Freq ~ ., DF))

