CHEM97Na {micemd} | R Documentation |
An incomplete two-level dataset which consists of A/AS-level examination data from England
Description
This dataset is an extract of the CHEM97 dataset (Fielding, A. et al, 2003) dealing with point scores of 31,022 pupils grouped in 2,280 schools. CHEM97Na reports point score for Schools with more than 70 pupils only, i.e. 1681 pupils grouped in 18 schools. Systematically missing values and sporadically missing values have been added according to a missing completely at random (MCAR) mechanism (Little R.J.A. and Rubin D.B., 2002). Systematically missing values are values that are missing for all pupils of a same school, while sporadically missing values are values which are missing for an individual only (Resche-Rigon, et al 2013).
Usage
data("CHEM97Na")
Format
A data frame with 1681 observations on the following 5 variables.
School
a numeric indexing the School
Sex
a factor with levels
M
F
Age
a numeric indicating the age in months
GSCE
a numeric vector indicating the point score at the General Certificate of Secondary Education
Score
a numeric vector indicating the point score on A-level Chemistry in 1997
Details
For more details, see Fielding, A. et al (2003).
Source
Fielding, A., Yang, M., and Goldstein, H.(2003). Multilevel ordinal models for examination grades. Statistical Modelling, 3 (2): 127-153.
Available at http://www.bristol.ac.uk/cmm/learning/mmsoftware/data-rev.html#chem97
References
Fielding, A., Yang, M., and Goldstein, H. (2003). Multilevel ordinal models for examination grades. Statistical Modelling, 3 (2): 127-153. doi:10.1191/1471082X03st052oa
Resche-Rigon, M., White, I. R., Bartlett, J., Peters, S., Thompson, S., and on behalf of the PROG-IMT Study Group (2013). Multiple imputation for handling systematically missing confounders in meta-analysis of individual participant data. Statistics in Medicine, 32(28):4890-4905. doi:10.1002/sim.5894
Little R.J.A., Rubin D.B. (2002) Statistical Analysis with Missing Data. Wiley series in probability and statistics, New-York
See Also
Examples
data(CHEM97Na)
#summary
summary(CHEM97Na)
#summary per School
by(CHEM97Na,CHEM97Na$School,summary)