Incorrect standard errors and tests of significance for regression coefficients would be given using MR when HLM should be used.ĩ Example from Tate Example of a policy analysis related to ongoing school reform efforts in a hypothetical state. Therefore the assumptions of constant variance and independence of errors in multiple regression are violated. If classroom used then we have a loss of power Students within any one classroom, b/c they were taught together tend to be similar in their performance As a result, they provide less information than if the same number of students had been taught separately by different teachers Problem is if student is used as the unit of analysis then we have problems with error. Students from Classroom A tend to be more alike with each other than they would be with students from Classroom B. For example, the effect of student study time may be related to teacher emphasis on homework.
Should the student be the unit of analysis or the classroom mean, school mean, etc.? HLM simultaneously accounts for several levels of data E.g., if we have a multiple regression model do we try to predict the student’s level of achievement or the classroom’s?Ħ HLM uses We can simultaneously study the effects of group level variables and individual level variables with HLM There may be interactions across levels as well that only HLM can account for. For example, when we have students who are nested in classrooms, classrooms nested within schools, etc… E.g., if we randomly sampled three classrooms of students from 10 different schools and then collected data from all these students.Ĭlients in groups for group therapy Employees in organizations School administrators in school districts Voters in voting precincts Homeowners in neighborhoodsĥ Unit of Analysis Researchers have difficulty deciding the appropriate unit of analysis with educational data. Both are frequently used with educational data and are rapidly gaining in popularity.ģ When should HLM be used? HLM is appropriate for use when we have nested data structures which occurs frequently with educational data. Multilevel models or Hierarchical Linear Models and Structural Equation Models are both considered extensions of regression analyses.
2 Hierarchical Linear Modeling (HLM) Structural Equation Modeling (SEM)
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