FRSC: Freitag and Schlicht (2009)

Description

The FRSC data frame has 16 rows and 8 variables

Usage

data(FRSC)

Arguments

Format

A data frame with 16 observations on the following 8 variables.

integrated_comp_schools: a numeric vector. Condition, percentage of Pupils Enrolled in Integrated Comprehensive Schools,
coop_comp_schools: a numeric vector. Condition, percentage of Pupils Enrolled in Cooperative Comprehensive Schools.
full_day_schools: a numeric vector. Condition, percentage of Pupils Enrolled in All-Day Schools
child_care: a numeric vector. Condition, ratio of Number of Child Care Facilities to Total Population between 0 and 6 Years (percent).
pre_schools: a numeric vector. Condition, ratio of pupils Enrolled in Pre-School to Total 6-Year-Old Population (per cent)
early_tracking: a numeric vector. Condition, onset of Tracking, Legal Regulation.
outcome: a numeric vector. Outcome, high Degree of Social Inequality Cases in Education.
indep_hauptschule: a numeric vector. Condition, autonomy of the Hauptschule.

Details

Data are used by Freitag and Schlicht (2009) to analyze social inequality in education. The data are raw scores.

References

Freitag, M, and Schlicht, R. (2009) "Educational Federalism in Germany: Foundations of Social Inequalities in Education", Governance 22(1), pp. 47-72.

Schneider, C. Q., Wagemann, C. (2012) Set-Theoretic Methods for the Social Sciences, Cambridge University Press: Cambridge.

Schneider, C. Q., Wagemann, C., Quaranta, M. (2012) How To... Use Software for Set-Theoretic Analysis. Online Appendix to "Set-Theoretic Methods for the Social Sciences". Available at www.cambridge.org/schneider-wagemann