S2CFA {confreq} | R Documentation |
Configural Frequencies Analysis for two Samples.
Description
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.
Usage
S2CFA(patternfreq, alpha = 0.05, ccor = FALSE, ...)
Arguments
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. |
Details
no details at the moment ...
Value
an object of class S2CFA
with results.
References
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.
Examples
#######################################
############### 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)