confreq (version 1.6.1-1)

confreq-package: Configural Frequencies Analysis Using Log-linear Modeling

Description

The package confreq offers some functions for Configural Frequencies Analysis (CFA) proposed by G.A. Lienert as an analysis of types and antitypes of persons or objects grouped according to their characteristic (response) pattern. The core principle in the package confreq is to use the function glm to compute the expected counts based on a model (design) matrix. The main functions are CFA and S2CFA (see details).

Author

• R.W. Alexandrowicz (function stirling_cfa())

Details

The simplest entry to the package confreq is to use the main function CFA, which will compute several coefficients of Configural Frequencies Analysis at once.

More sophisticated control can be achieved by using the several single functions like expected_cfa, design_cfg_cfa, chi_local_test_cfa , stirling_cfa , etc. ...

Two-Sample-CFA, to detect discriminating pattern between two (sub-) samples, can be performed with the function S2CFA

For further description see description of the respective functions.

A good introduction into the theory and applications of Configural Frequencies Analysis is given in the Textbook 'Person-Centered Methods' by Mark Stemmler (see references).

Additional Information: Some users running R on 'Linux like' OS distributions (like e.g. Ubuntu -- and in rare cases MAC OS) might report trouble during installation of confreq due to the package dependency gmp, which is used in confreq to perform the exact binomial test. This (miss-)behavior can usually traced back to a missing of 'the GNU Multiple Precision Arithmetic Library' in the respective OS installation. To fix this, users might consider to run the following Ubuntu Linux command in a terminal to install the latest GMP Library:

'sudo apt-get install libgmp3-dev'.

For additional information see also http://www.mathemagix.org/www/mmdoc/doc/html/external/gmp.en.html and https://gmplib.org/.

Annotation: The foundations for this R-Package were established and discussed in Rothenberge (2011) and (finally) in Klagenfurt at FGME 2013 with Rainer Alexandrowicz and Mark Stemmler ...

References

von Eye, A. (2002). Configural Frequency Analysis. Methods, Models, and Applications. Mahwah, NJ, LEA.

Krauth, J., & Lienert, G. A. (1973). Die Konfigurationsfrequenzanalyse (KFA) und ihre Anwendung in Psychologie und Medizin: ein multivariates nichtparametrisches Verfahren zur Aufdeckung von Typen und Syndromen; mit 70 Tabellen. Freiburg; München: Alber Karl.

Lazarsfeld, P. F., & Henry, N. W. (1968). Latent structure analysis. Boston: Houghton Mifflin.

Lienert, G. A. (1978). Verteilungsfreie Methoden in der Biostatistik (Band II) [Non-parametrical methods in the field of biometrics (Vol. II)]. Meisenheim am Glan, Germany: Hain.

Lienert, G. A. (1971). Die Konfigurationsfrequenzanalyse: I. Ein neuer Weg zu Typen und Syndromen. Zeitschrift für Klinische Psychologie und Psychotherapie, 19(2), 99-115.

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 ########
data(LienertLSD)
LienertLSD
CFA(LienertLSD)
## testing with (full) interactions
CFA(LienertLSD,form="~ C + T + A + C:T + C:A + T:A + C:T:A")
## testing the null model
CFA(LienertLSD,form="null")
#######################
data(suicide)
suicide
# suicide data is in non tabulated data representation 
# so it must be tabulated !
CFA(dat2fre(suicide))