IBM SPSS Advanced Statistics
IBM® SPSS® Advanced Statistics provides the following capabilities:
- General linear models (GLM) and mixed models procedures.
- Generalized linear models (GENLIN) including widely used statistical models, such as linear regression for normally distributed responses,
logistic models for binary data and loglinear models for count data.
- Linear mixed models, also known as hierarchical linear models (HLM), which expands the general linear models used in the GLM
procedure so that you can analyze data that exhibit correlation and non-constant variability.
- Generalized estimating equations (GEE) proceduresthat extend generalized linear models to accommodate correlated longitudinal data and clustered data.
- Generalized linear mixed models (GLMM) for use with hierarchical data and a wide range of outcomes, including ordinal values.
- Survival analysis procedures for examining lifetime or duration data.
SPSS Advanced Statistics Screenshots
Linear Mixed Models estimated means
GLMM provides estimated marginal means to explain the impact of the predictor.
Generalized Linear Mixed Models model summary
A GLMM model summary shows how well the model fits the data.