Datasets from Borg and Staufenbiel (2007)
Datasets of the book of Borg and Staufenbiel (2007) Lehrbuch Theorien and Methoden der Skalierung.
data(data.bs07a)
The dataset data.bs07a contains the data
Gefechtsangst (p. 130) and contains 8 of the original 9 items.
The items are symptoms of anxiety in engagement. GF1: starkes Herzklopfen, GF2: flaues Gefuehl in der
Magengegend, GF3: Schwaechegefuehl, GF4: Uebelkeitsgefuehl,
GF5: Erbrechen, GF6: Schuettelfrost,
GF7: in die Hose urinieren/einkoten, GF9: Gefuehl der
Gelaehmtheit
The format is
'data.frame': 100 obs. of 9 variables: $ idpatt: int 44 29 1 3 28 50 50 36 37 25 ... $ GF1 : int 1 1 1 1 1 0 0 1 1 1 ... $ GF2 : int 0 1 1 1 1 0 0 1 1 1 ... $ GF3 : int 0 0 1 1 0 0 0 0 0 1 ... $ GF4 : int 0 0 1 1 0 0 0 1 0 1 ... $ GF5 : int 0 0 1 1 0 0 0 0 0 0 ... $ GF6 : int 1 1 1 1 1 0 0 0 0 0 ... $ GF7 : num 0 0 1 1 0 0 0 0 0 0 ... $ GF9 : int 0 0 1 1 1 0 0 0 0 0 ...
MORE DATASETS
Borg, I., & Staufenbiel, T. (2007). Lehrbuch Theorie und Methoden der Skalierung. Bern: Hogrefe.
## Not run: ############################################################################# # EXAMPLE 07a: Dataset Gefechtsangst ############################################################################# data(data.bs07a) dat <- data.bs07a items <- grep( "GF", colnames(dat), value=TRUE ) #************************ # Model 1: Rasch model mod1 <- TAM::tam.mml(dat[,items] ) summary(mod1) IRT.WrightMap(mod1) #************************ # Model 2: 2PL model mod2 <- TAM::tam.mml.2pl(dat[,items] ) summary(mod2) #************************ # Model 3: Latent class analysis (LCA) with two classes tammodel <- " ANALYSIS: TYPE=LCA; NCLASSES(2) NSTARTS(5,10) LAVAAN MODEL: F=~ GF1__GF9 " mod3 <- TAM::tamaan( tammodel, dat ) summary(mod3) #************************ # Model 4: LCA with three classes tammodel <- " ANALYSIS: TYPE=LCA; NCLASSES(3) NSTARTS(5,10) LAVAAN MODEL: F=~ GF1__GF9 " mod4 <- TAM::tamaan( tammodel, dat ) summary(mod4) #************************ # Model 5: Located latent class model (LOCLCA) with two classes tammodel <- " ANALYSIS: TYPE=LOCLCA; NCLASSES(2) NSTARTS(5,10) LAVAAN MODEL: F=~ GF1__GF9 " mod5 <- TAM::tamaan( tammodel, dat ) summary(mod5) #************************ # Model 6: Located latent class model with three classes tammodel <- " ANALYSIS: TYPE=LOCLCA; NCLASSES(3) NSTARTS(5,10) LAVAAN MODEL: F=~ GF1__GF9 " mod6 <- TAM::tamaan( tammodel, dat ) summary(mod6) #************************ # Model 7: Probabilistic Guttman model mod7 <- sirt::prob.guttman( dat[,items] ) summary(mod7) #-- model comparison IRT.compareModels( mod1, mod2, mod3, mod4, mod5, mod6, mod7 ) ## End(Not run)
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