PXisM: Test according to Lindner In cfa: Configural Frequency Analysis (CFA)

Description

Performs a test of significance according to Lindner

Usage

 `1` ```PXisM(m,n,Nt,k) ```

Arguments

 `m` Observed frequency of the observation tested `n` Marginal sums of the parameters realized in the configuration to be tested (vector) `Nt` Sample size of configurations `k` Number of parameters

Value

returns p for the test according to Linder

Note

The test according to Lindner requires the packages parallel. All other parts of cfa do not.

Author(s)

J. Harloff <oachimharloff@joachimharloff.de>

References

Lindner, K.: Eine exakte Auswertungsmethode zur Konfigurationsfrequenzanalyse [An exact procedure for the configural frequency analysis]. Psycholog Beitraege 26, 393?415 (1984)

Harloff, Joachim, An efficient algorithm for Lindners test (configural frequency analysis), Qual Quant DOI 10.1007/s11135-011-9499-9

`cfa`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19``` ```# Does not work with windows since there is no parallel for it if (require(parallel)) { lk<-4 # number of parameters ln<-c(59,57,59,58) # marginal sums of the parameters realized in the configuration to be tested lNt<-116 # sample size of configurations lm0<-16 # observed frequency of the configuration tested # New algorithm starttime=proc.time() pHXsmallerequalM0<-sum(unlist(mclapply(0:lm0,PXisM,ln,lNt,lk))) pHXequalM0<-PXisM(lm0,ln,lNt,lk) pHlargerequalM0<-sum(unlist(mclapply(lm0: min(ln),PXisM,ln,lNt,lk))) stoptime<-proc.time() list(pHXsmallerequalM0=pHXsmallerequalM0,pHXequalM0=pHXequalM0,pHlargerequalM0=pHlargerequalM0, timed.required=stoptime-starttime) # End of the new algorithm } ```