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From the final estimates of the fixed effects, we see that all the predictors made a significant
contribution to the explanation of the variation in the outcome variable MATHACH. The school
sector had a positive influence on the intercept, but a negative influence on the slope of SES. As
Catholic schools were coded 1, this implies that the intercept for students in Catholic schools was,
on average, 1.226 units higher than for students in public schools. The SES slope for Catholic
schools was 1.641 units lower than for public schools. The largest contribution to the intercept,
however, is from the mean social class variable (MEANSES). The higher the mean SES of the group,
the higher the intercept for a particular school.
For the HS&B example, the level-1 units are students and the level-2 units are schools. The
two files are linked by a common level-2 unit ID, school id in our example, which must appear
on every level-1 record. In constructing the MDM file, the HLM program will compute summary
statistics based on the level-1 unit data and store these statistics together with level-2 data.
四路交叉分类和嵌套混合
对学生在学校内随时间推移,教师的重复措施,或在中嵌套项目反应,根据原籍国和目的地进行交叉分类。
对同时居住在某一特定地区并参加某一学校的人的重复措施。
To supply HLM with appropriate information for the data, the command, and the MDM files:
1. Select SPSS/Windows from the Input File Type pull-down menu.
2. Specify the structure of data. The three choices are cross-sectional, longitudinal,
and measures within groups. The data in HSB1.SAV are cross-sectional.
3. Click Browse in the Level-1 Specification section to open an Open Data File
dialog box.
4. Open a level-1 SPSS system file in the HLM folder (HSB1.SAV in our example). The
Choose Variables button will be activated.
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