More Accurately Analyze Complex Relationships Using Powerful Univariate and Multivariate Analysis

Make your analysis more accurate and reach more dependable conclusions with procedures designed to fit the inherent characteristics of data describing complex relationships. SPSS Advanced Models, an add-on module for SPSS Base, provides a powerful set of sophisticated univariate and multivariate analysis techniques for real-world problems, such as:

• Medical research: Analyze patient survival rates
• Manufacturing: Assess production processes
• Pharmaceutical: Report test results to the FDA
• Market research: Determine product interest levels

Access a Range of Powerful Models

In addition to the general linear models (GLM) and mixed models procedures, SPSS Advanced Models now offers the generalized linear models (GZLMs) and generalized estimating equations (GEEs) procedures.

• GZLMs include widely used statistical models, such as linear regression for normally distributed responses, logistic models for binary data, and loglinear models for count data. This procedure also offers many useful statistical models through its very general model formulation.
• GEEs extend generalized linear models to accommodate correlated longitudinal data and clustered data

SPSS Advanced Models continues to offer the following procedures:

• General linear models (GLM) procedure:
  Provides you with more flexibility to describe the relationship between a dependent variable and a set of independent variables
• Linear mixed models, also known as hierarchical linear models (HLM) procedure:
  Expands the general linear models used in the GLM procedure so that you can analyze data that exhibit correlation and non-constant variability. Create more accurate models when working with nested-structure data, and model the mean, variance, and covariance in your data