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HLM Examples
To fit models in HLM, 8 statistical applications are used: HLM2, which fits 2-level linear and nonlinear (HGLM) models; HLM3, which fits 3-level linear/nonlinear models; HLM4, which fits 4-level linear/nonlinear models; HMLM, which fits hierarchical multivariate 2-level linear models; HMLM2, which fits hierarchical multivariate 3-level models; HCM2, which fits 2-level crossed-and-nested models, ; HCM3, which fits 3-level crossed-and-nested models; and HLMHCM, which fits linear models with crossed-and-nested random effects. For specific examples for the different modules, please see below.
![HLM百科](//l.b2b168.com/2020/06/18/17/202006181725027765464.jpg)
The first task in using HLM2 is to construct the Multivariate Data Matrix (MDM) from raw data
or from a statistical package. We generally work with two raw data files: a level-1 file and a
level-2 file. Both files must be sorted by the level-2 ID (It is possible, however, to build the
MDM file from a single data file, though this option is not suggested when the level-1 file is
very large. The level-1 file must again be sorted by level-2 ID.
![HLM百科](//l.b2b168.com/2019/07/19/15/20190719151114584044.jpg)
HLM新版本在建模多层次和纵向数据方面提供了**的灵活性。HLM功能的亮点包括三个新的进程,处理二进制、计数、序数和多项式(名义)的响应变量,以及连续响应变量的一般理论层次线性模型。
![HLM百科](//l.b2b168.com/2020/06/18/15/202006181534441272554.jpg)
Should the user prefer the model displayed without subscripts or the mixed model display at the
modeling window, the Preferences option from the File menu may be used to open the
Preferences dialog box as shown below.
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