data.bs.Rd
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.
if (FALSE) { ############################################################################# # 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 ) }