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

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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 Figure 9.4 Extract from SPSS Control Code for Creating a Student Background SPSS Data Set *NOTE: Assignment of variable names. data list file = bsg1.dat / VERSION 1 - 2 . .{INSERT VARIABLE NAME FORMAT AND LOCATION HERE} . *NOTE: Assignment of variable labels. variable labels VERSION "*FILE VERSION*" . .{INSERT VARIABLE LABELS HERE} . VALUE LABELS IDPOP 1 "population 1" 2 "population 2" 3 "population 3" / . .{INSERT VARIABLE LABELS HERE} . *RECODE of sysmis-values. RECODE IDSTRAT (999 = sysmis). . .{INSERT RECODES OF MISSING VALUES HERE} . *RECODE of other missing-values. MISSING value IDSTRAT (998 ). . .{DEFINE MISSING VALUES HERE} . SAVE OUTFILE = bsg.sys. T I M S S D A T A B A S E U S E R G U I D E 9 - 7
C H A P T E R 9 P E R F O R M I N G A N A L Y S E S 9.3 Computing JRR Replicate Weights and Sampling Variance Using SPSS and SAS In this section example SAS and SPSS code that may be used to compute the JRR standard errors for means and percentages is described. This code is provided in the form of SAS and SPSS macros. These macros compute the percentage of students within a subgroup defined by a set of classification variables, the JRR standard error of this percentage, the mean for the group on a variable of choice, and the JRR standard error of that mean. Each of these macros operate as follows: 1. Computes a set of 75 replicate weights for the record using the procedure described in the previous chapter. 2. Aggregates or summarizes the file computing the sum of the weights for each category, the sum of the weights overall, and the sum of a weighted analysis variable. 3. Computes the percent of people within each group, their mean on the analysis variable, and their corresponding standard errors. In SPSS the resulting working file contains the corresponding statistics. In SAS the file FINAL contains the corresponding statistics. When using each of these macros, the user needs to specify a set of classification variables, one analysis variable, the number of replicate weights to be generated, the variable that contains the sampling information such as JKZONE and JKINDIC, and the sampling weight that is to be used for the analysis. When using the SAS macro the user will also need to specify the data file that contains the data that is to be processed. In SPSS the macro uses the current working file, which is the file that was last read. 9.3.1 SAS Macro for Computing Mean and Percents with Corresponding Standard Errors (JACK.SAS) The CD containing the TIMSS International Database contains a SAS macro program called JACK.SAS. This macro can be used to compute weighted percents and means within categories defined by variables specified by the user, and the JRR standard error estimate for these statistics. The control code for the macro JACK.SAS is presented in Figure 9.5. 9 - 8 T I M S S D A T A B A S E U S E R G U I D E
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International Association for the E
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Contents Chapter 1: Overview of TIM
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C O N T E N T S 7.3 Codebook Files
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C O N T E N T S Table 7.7 Classific
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Chapter 1 Overview of TIMSS and the
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I N T R O D U C T I O N C H A P T E
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Chapter 2 TIMSS Instruments and Boo
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I N S T R U M E N T S C H A P T E R
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Chapter 3 Sampling and Sampling Wei
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S A M P L I N G C H A P T E R 3 Tab
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S A M P L I N G C H A P T E R 3 3.5
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S A M P L I N G C H A P T E R 3 Tab
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C H A P T E R 4 D A T A C O L L E C
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C H A P T E R 5 S C A L I N G 5.2 T
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C H A P T E R 5 S C A L I N G 5.6 L
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C H A P T E R 6 A C H I E V E M E N
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