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sirt (version 4.1-15)

data.befki: BEFKI Dataset (Schroeders, Schipolowski, & Wilhelm, 2015)

Description

The synthetic dataset is based on the standardization sample of the Berlin Test of Fluid and Crystallized Intelligence (BEFKI, Wilhelm, Schroeders, & Schipolowski, 2014). The underlying sample consists of N=11,756 students from all German federal states (except for the smallest one) and all school types of the general educational system attending Grades 5 to 12. A detailed description of the study, the sample, and the measure is given in Schroeders, Schipolowski, and Wilhelm (2015).

Usage

data(data.befki)
data(data.befki_resp)

Arguments

Format

  • The dataset data.befki contains 11756 students, nested within 581 classes.

    'data.frame': 11756 obs. of 12 variables:
    $ idclass: int 1276 1276 1276 1276 1276 1276 1276 1276 1276 1276 ...
    $ idstud : int 127601 127602 127603 127604 127605 127606 127607 127608 127609 127610 ...
    $ grade : int 5 5 5 5 5 5 5 5 5 5 ...
    $ gym : int 0 0 0 0 0 0 0 0 0 0 ...
    $ female : int 0 1 0 0 0 0 1 0 0 0 ...
    $ age : num 12.2 11.8 11.5 10.8 10.9 ...
    $ sci : num -3.14 -3.44 -2.62 -2.16 -1.01 -1.91 -1.01 -4.13 -2.16 -3.44 ...
    $ hum : num -1.71 -1.29 -2.29 -2.48 -0.65 -0.92 -1.71 -2.31 -1.99 -2.48 ...
    $ soc : num -2.87 -3.35 -3.81 -2.35 -1.32 -1.11 -1.68 -2.96 -2.69 -3.35 ...
    $ gfv : num -2.25 -2.19 -2.25 -1.17 -2.19 -3.05 -1.7 -2.19 -3.05 -1.7 ...
    $ gfn : num -2.2 -1.85 -1.85 -1.85 -1.85 -0.27 -1.37 -2.58 -1.85 -3.13 ...
    $ gff : num -0.91 -0.43 -1.17 -1.45 -0.61 -1.78 -1.17 -1.78 -1.78 -3.87 ...

  • The dataset data.befki_resp contains response indicators for observed data points in the dataset data.befki.

    num [1:11756, 1:12] 1 1 1 1 1 1 1 1 1 1 ...
    - attr(*, "dimnames")=List of 2
    ..$ : NULL
    ..$ : chr [1:12] "idclass" "idstud" "grade" "gym" ...

Details

The procedure for generating this dataset is based on a factorization of the joint distribution. All variables are simulated from unidimensional conditional parametric regression models including several interaction and quadratic terms. The multilevel structure is approximated by including cluster means as predictors in the regression models.

References

Schroeders, U., Schipolowski, S., & Wilhelm, O. (2015). Age-related changes in the mean and covariance structure of fluid and crystallized intelligence in childhood and adolescence. Intelligence, 48, 15-29. tools:::Rd_expr_doi("10.1016/j.intell.2014.10.006")

Wilhelm, O., Schroeders, U., & Schipolowski, S. (2014). Berliner Test zur Erfassung fluider und kristalliner Intelligenz fuer die 8. bis 10. Jahrgangsstufe [Berlin test of fluid and crystallized intelligence for grades 8-10]. Goettingen: Hogrefe.