S2CFA | R Documentation |
Calculates coefficients for the two-sample CFA. Instead of differentiating between 'Types' and 'Antitypes', two-sample CFA looks for discrimination types, that is configurations with significant differences in frequencies between two sub samples.
S2CFA(patternfreq, alpha = 0.05, ccor = FALSE, ...)
patternfreq |
an object of class |
alpha |
a numeric giving the alpha level for testing (default set to |
ccor |
a logical (TRUE / FALSE) determining whether to apply a continuity correction or not. When set to |
... |
additional parameters passed through to other functions. |
no details at the moment ...
an object of class S2CFA
with results.
Stemmler, M. (2020). Person-Centered Methods – Configural Frequency Analysis (CFA) and Other Methods for the Analysis of Contingency Tables. Cham Heidelberg New York Dordrecht London: Springer.
Stemmler, M., & Hammond, S. (1997). Configural frequency analysis of dependent samples for intra-patient treatment comparisons. Studia Psychologica, 39, 167–175.
####################################### ############### some examples ######### ######### example from Marks Textbook data(Lienert1978) res1 <- S2CFA(Lienert1978) summary(res1) res2 <- S2CFA(Lienert1978, ccor=TRUE) # with continuity correction summary(res2) ######### example with biger numbers data(suicide) ftab(suicide) # 'Epoche' may divide the sample into 2 subsamples suicide_2s <- suicide[, c(1,3,2) ] # reorder data that 'Epoche' is the last column ftab(suicide_2s) # check reordering suicide_2s_fre <- dat2fre(suicide_2s) res3 <- S2CFA(suicide_2s_fre) summary(res3) res4 <- S2CFA(suicide_2s_fre, ccor=TRUE) # with continuity correction summary(res4)
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