IBM SPSS Advanced Statistics

Use powerful techniques to analyze complex data

With IBM SPSS Advanced Statistics software, you can:

  • Move beyond basic analysis
  • Build flexible models using a wealth of model-building options
  • Achieve more accurate predictive models using a wide range of modeling techniques

Comprehensive tools for today’s analyst

IBM SPSS Advanced Statistics software addresses the wide range of statistical needs of today’s analyst. With its wealth of features and capabilities, you may never be limited to basic analytical techniques again.


GLM multivariate: Gain more flexibility to describe the relationship between a dependent variable and a set of independent variables.

Linear mixed models (Mixed): Use the Mixed procedure to model means, variances and covariances when working with nested-structure data or repeated measures data, including when there are different numbers of repeated measurements, different intervals for different cases or both.

Survival analysis: Analyze event history and duration data to better understand events. IBM SPSS Advanced Statistics software includes state-of-the-art survival procedures such as Kaplan-Meier and Cox Regression.

VARCOMP: Choose from a number of methods to estimate the variance component for each random effect in a mixed model.

Log-linear analysis: Fit log-linear and logit models to count data so you can more easily model and predict your outcomes.

GLMM: GLMM: Allows more accurate models when predicting nonlinear outcomes (for example, what product a customer is likely to buy) by taking into account hierarchical data structures (customer nested with an organization)

Interactive and improved visualizations enable a more intuitive explanation of model predictors and outcomes.

System Screen

1.GLM Multivariate main dialog box

2.Contrasts dialog box

3.Options dialog box

4.Between-subjects SSCP matrix

5.The spread-versus-level plot

IBM SPSS Statistics Modules