scfa                   package:cfa                   R Documentation

_O_n_e _s_a_m_p_l_e _C_F_A

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

     Performs a configuration frequency analysis if only one set of
     counts exists. This function is not generally called by the user
     but will be used by 'cfa()'.

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

     scfa(cfg, cnt=NA, sorton="chisq", sort.descending=TRUE, format.labels=TRUE)

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

     cfg: Contains the configurations. This can be a dataframe or a
          matrix. The dataframe can contain numbers, characters,
          factors or booleans. The matrix can consist of numbers,
          characters or booleans  (factors are implicitely re-converted
          to numerical levels). There must be >=3 columns.

     cnt: Contains the counts for the configuration. If it is set to
          NA, a count of one is assumed for every row. This allows
          untabulated data to be processed. 'cnts' is a vector.

  sorton: Determines the sorting order of the output. Can be set to
          'chisq', 'n', or 'label'.

sort.descending: Sort in descending order 

format.labels: Format the labels of the configuration. This makes to
          output wider but it will increase the readability.

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

     This function is the "engine" 'cfa()' will use. It does the
     aggregation, summing up, and will calculate chi squared. All tests
     of significance are left to  'cfa()'

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

     The function returns the following list: 

  labels: Configuration label

n.levels: Number of levels for each configuration

    sums: Sums for each configuration and each variable in the
          configuration

  counts: Observed n of the given configuration

expected: Expected n for the given configuration

   chisq: Chi squared for each configuration

_N_o_t_e:

     There are no hard-coded limits in the program so even large tables
     can be processed.

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

     Stefan Funke <s.funke@t-online.de>

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

     Krauth J., Lienert G. A. (1973, Reprint 1995) Die
     Konfigurationsfrequenzanalyse (KFA) und ihre Anwendung in
     Psychologie und Medizin, Beltz Psychologie Verlagsunion

     Lautsch, E., von Weber S. (1995) Methoden und Anwendungen der
     Konfigurationsfrequenzanalyse  Psychologie und Medizin, Beltz
     Psychologie Verlagsunion

     Eye, A. von (1990) Introduction to configural frequency analysis.
     The search for types and anti-types in cross-classification. 
     Cambride 1990

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

     'cfa', 'mcfa'

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

      
     # library(cfa) if not yet loaded
     # Some random configurations:
     configs<-cbind(c("A","B")[rbinom(250,1,0.3)+1],c("C","D")[rbinom(250,1,0.1)+1],
               c("E","F")[rbinom(250,1,0.3)+1],c("G","H")[rbinom(250,1,0.1)+1])
     counts<-trunc(runif(250)*10)
     scfa(configs,counts) 

