User Guide for the TIMSS International Database.pdf - TIMSS and ...

P E R F O R M I N G A N A L Y S E S C H A P T E R 9
CVAR
DVAR
This lists the variables that are to be used to classify the students in the data file. This can
be a single variable, or a list of variables. The maximum number of variables will depend
mostly on the computer resources available to the user at the time. It is recommended to
always include the variable that identifies the country. At least one variable has to be
specified, usually IDCNTRY.
This is the variable for which means are to be computed. Only one variable has to be
listed here. If the user wants to find out, for example, the results in mathematics and
science, then the macro needs to be invoked separately to generate each table. Although
in most cases the continuous variable of interest will be an achievement variable, this can
actually be any other continuous variable in the data file.
FNAME
The name of the data set that contains the variables necessary for the analysis. The name
of this file has to be in either the single or multilevel SAS format. The multilevel SAS file
format contains the library as well as the data set. It is important to emphasize that this
data set must include only those cases that are of interest in the analysis. If the user wants
to have specific cases excluded from the analysis, as for example, students with missing
variables or select students from a specific grade, this should be done prior to invoking
the macro.
The simplest and most straightforward way is to invoke the macro using the conventional SAS
notation for invoking macros followed by the list of arguments for the analysis enclosed in
parenthesis, separated by commas, and in the same order as they are listed above. For
example, if the macro is invoked as:
%jack(TOTWGT ,JKZONE,JKINDIC,75,IDCNTRY IDGRADER ITSEX, BIMATSCR, BSGALL1);
it will compute the mean mathematics achievement, and its corresponding standard error, for
boys and girls, by grade, within each country, using the variable TOTWGT as the sampling
weight. It will also compute the percent of boys and girls by grade within the country, and its
corresponding standard error. The data will be read from the data set BSGALL1, and the
standard error of the statistics will be computed based on 75 replicate weights.
The file that contains these results is called FINAL and can be found in the WORK library.
The variables that are contained in this file are:
Classification Variables
Each of the classification variables are kept in the resulting file. In the above example
there would be three variables in the WORK.FINAL data set. These would be IDCNTRY,
IDGRADER, and ITSEX. There is one unique occurrence for each combination of the
categories for these variables.
T I M S S D A T A B A S E U S E R G U I D E 9 - 1 3