Create multiple response set/multiple dichotomy set from variables
These functions are intended for usage with tables - tables,
cro, cro_fun. Result of mrset is considered as
muliple-response set with category encoding and result of mdset is
considered as multiple response set with dichotomy (dummy) encoding e. g.
with 0 or 1 in the each column. Each column in the dichotomy is
indicator of absence or presence of particular feature. Both functions don't
convert its arguments to anything - it is supposed that arguments already
have appropriate encoding. For conversation see as.dichotomy or
as.category.
mrset_f and mdset_f select variables by fixed pattern. Fixed
pattern can be unquoted. For details see ..f.
mrset_p and mdset_p select variables for
multiple-responses by perl-style regular expresssion. For details see ..p.
mrset_t and mdset_t select variables by expanding text
arguments. For details see ..t and text_expand.
mrset(..., label = NULL) mdset(..., label = NULL) mrset_f(..., label = NULL) mdset_f(..., label = NULL) mrset_p(..., label = NULL) mdset_p(..., label = NULL) mrset_t(..., label = NULL) mdset_t(..., label = NULL)
... |
variables |
label |
character optional label for multiple response set |
data.frame of class category/dichotomy
data(product_test)
calc_cro_cpct(product_test, mrset(a1_1 %to% a1_6))
# same result
calc_cro_cpct(product_test, mrset_f(a1_))
# same result
calc_cro_cpct(product_test, mrset_p("a1_"))
# same result
calc_cro_cpct(product_test, mrset_t("a1_{1:6}"))Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.