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The example below shows how to run a three-level multilevel model in SPSS. For this example, we use the eg_hlm.sav data set and SPSS 16.0.1 (please note that this code should work in SPSS versions 11.5 and higher). In this data set, time (the variable year) is nested within students (the variable cid), and students are nested within schools (the variable school). In order to run this example, you may need to subset the data such that only some of the schools are used. (Please note that the schools are really numbered 1 through 60. Because this variable, called school, has value labels, you might see numbers like 2020, 2330, etc. in the school column. To turn off the value labels, click on the value labels button in the upper left of the Data View window in the Data Editor.)
Note that there are two random subcommands. Both are needed to run this type of three-level model. The first random subcommand provides the random intercepts for schools (the highest level), while the second random subcommand provides the random intercepts for students (the second level). These subcommands must be listed in this order (e.g., from highest to lowest level).
For more information, and for more examples, please see the SPSS Command
Syntax Reference for the mixed command. Model 6: Multilevel
Analysis has an example with a four-level model.
temporary. select if school < 15. mixed math with year /fixed = year /print = solution /random = intercept | subject(school) /random = intercept | subject(school*cid).
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