sirt (version 1.14-0)

data.bs: Datasets from Borg and Staufenbiel (2007)

Description

Datasets of the book of Borg and Staufenbiel (2007) Lehrbuch Theorien and Methoden der Skalierung.

Usage

data(data.bs07a)

Format

• 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

References

Borg, I., & Staufenbiel, T. (2007). Lehrbuch Theorie und Methoden der Skalierung. Bern: Hogrefe.

Examples

## 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)