SPSS Statistics - Standard

Linear models

• Statistics Standard includes generalized linear mixed models (GLMM) for use with hierarchical data.
• This software has general linear models (GLM) and mixed models procedures.
• It includes 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. GENLIN also offers many useful statistical models through its very general model formulation.
• Generalized estimating equations (GEE) procedures extend generalized linear models to accommodate correlated longitudinal data and clustered data.

Nonlinear models

• Multinomial logistic regression (MLR) predicts categorical outcomes with more than two categories.
• Binary logistic regression classifies data into two groups.
• Nonlinear regression (NLR) and constrained nonlinear regression (CNLR) estimate parameters of nonlinear models.
• Probit analysis evaluates the value of stimuli using a logit or probit transformation of the proportion responding

Simulation capabilities

• Monte Carlo simulation techniques enable you to create simulated datasets based on existing data and/or known parameters when the existing data is inadequate.
• Non-numeric variables such as “male” and “female” can be simulated without recoding them as numeric variables.
• Existing predictive models and data can be used as the starting points for your simulation, including models exported from Automatic Linear Modeling (ALM) and IBM SPSS Modeler.
• Associations between categorical inputs are automatically determined and used when generating data for the inputs.
• Results are calculated over and over, using a different set of random values to produce distributions of possible outcome values and enabling users to select the best one.
• The advanced techniques within SPSS Statistics can be used to analyze simulation results and create charts and graphs to convey outcomes and recommended actions to decision-makers.

Customized tables

• Means or proportions are compared for demographic groups, customer segments, time periods or other categorical variables when including inferential statistics.
• The software creates summary statistics - from simple counts for categorical variables to measures of dispersion – and sorts categories by any summary statistic used.
• It includes three significance tests: Chi-square test of independence, comparison of column means (t test), or comparison of column proportions (z test).
• An interactive table builder provides drag and drop capabilities for creating pivot tables.
• Specific categories can be excluded, displays missing value cells and can add subtotals to tables.
• Tables can be previewed in real time and modified as they are created.
• Tables are exportable to Microsoft® Word, Excel®, PowerPoint® or HTML for use in reports.