Test according to Lindner
Performs a test of significance according to Lindner
PXisM(m,n,Nt,k)
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 |
returns p for the test according to Linder
The test according to Lindner requires the packages parallel. All other parts of cfa do not.
J. Harloff <oachimharloff@joachimharloff.de>
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
# 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
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