HLM 8 for Windows 多層次模式分析軟體

HLM 8 for Windows是一套群昱公司代理的多層次模式分析軟體,HLM提供的模型包括2-level models、3-level models、Hierarchical Generalized Linear Models (HGLM)和Hierarchical Multivariate Linear Models (HMLM)等。HLM所發展的階層模型(Hierarchical Linear and Nonlinear Modeling)軟體,包含線性和非線性部分,HLM可以讀取大部份統計軟體的檔案如 SPSS, SAS, SYSTAT及STATA等等。HLM常用於社會科學和行為科學,因為它常有巢狀結構(Nested Structure)的資料,因此需用次模型(Sub-Model)或階層模型(Hierarchical Model),HLM就是設計來專門解決此類問題的。

In social research
and other fields, research data often have a hierarchical
structure. That is, the individual subjects of study may be
classified or arranged in groups which themselves have qualities
that influence the study. In this case, the individuals can
be seen as level-1 units of study, and the groups into which
they are arranged are level-2 units. This may be extended
further, with level-2 units organized into yet another set
of units at a third level and with level-3 units organized
into another set of units at a fourth level. Examples of this
abound in areas such as education (students at level 1, teachers
at level 2, schools at level 3, and school districts at level
4) and sociology (individuals at level 1, neighborhoods at
level 2). It is clear that the analysis of such data requires
specialized software. Hierarchical linear and nonlinear models
(also called multilevel models) have been developed to allow
for the study of relationships at any level in a single analysis,
while not ignoring the variability associated with each level
of the hierarchy.

The HLM program can

fit models to outcome variables that generate a linear model

with explanatory variables that account for variations at

each level, utilizing variables specified at each level. HLM

not only estimates model coefficients at each level, but it

also predicts the random effects associated with each sampling

unit at every level. While commonly used in education research

due to the prevalence of hierarchical structures in data from

this field, it is suitable for use with data from any research

field that have a hierarchical structure. This includes longitudinal

analysis, in which an individual’s repeated measurements can

be nested within the individuals being studied. In addition,

although the examples above implies that members of this hierarchy

at any of the levels are nested exclusively within a member

at a higher level, HLM can also provide for a situation where

membership is not necessarily “nested”, but “crossed”, as

is the case when a student may have been a member of various

classrooms during the duration of a study period.

The HLM program allows

for continuous, count, ordinal, and nominal outcome variables

and assumes a functional relationship between the expectation

of the outcome and a linear combination of a set of explanatory

variables. This relationship is defined by a suitable link

function, for example, the identity link (continuous outcomes)

or logit link (binary outcomes).

N  News
about HLM

  • HLM 7 is Compatible with Windows 10. It has been tested on Windows 10 and no
    problems were reported.


  • HLM 7 is Compatible with Windows 8. It has been tested on Windows 8
    and no
    problems were reported.


  • HLM 7 is Compatible with Windows 7. It has successfully passed Microsoft
    designed tests for compatibility and reliability on Windows 7. It can be used
    on both the 32-bit and 64-bit editions. Compatible with Windows 7 products
    install without worry and run reliably with Windows 7.