SPSS Statistics Professional

Linear models

• SPSS Statistics Professional 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

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.
• It excludes specific categories, displays missing value cells and can add subtotals to tables.
• Tables can be previewed in real time and modified as they are created. They are exportable to Microsoft Word, Excel, PowerPoint or HTML for use in reports.

Data preparation

• SPSS Statistics Professional identifies suspicious or invalid cases, variables and data values.
• The software lets you view patterns of missing data and summarize variable distributions.
• Optimal Binning finds the best possible outcome for algorithms designed for nominal attributes.
• The Automated Data Preparation (ADP) tool detects and corrects quality errors and imputes missing values in one efficient step.
• Recommendations and visualizations help you determine which data to use.

Data validity and missing values

• SPSS Statistics Professional examines data from several different angles using one of six diagnostic reports, then estimates summary statistics and imputes missing values.
• It diagnoses serious missing data imputation problems.
• The software replaces missing values with estimates.
• It displays a snapshot for each type of missing value and any extreme values for each case.
• Hidden bias is removed by replacing missing values with estimates to include all groups—even those with poor responsiveness.

Decision trees

• SPSS Statistics Professional visually determines how your model flows so you can find specific subgroups and relationships.
• The software creates classification trees directly within IBM SPSS Statistics so you can use results to segment and group cases directly within the data.
• It includes four established tree-growing algorithms:
  • CHAID—A fast, statistical, multi-way tree algorithm that explores data quickly and efficiently, and builds segments and profiles with respect to the desired outcome.
  • Exhaustive CHAID—A modification of CHAID, which examines all possible splits for each predictor.
  • Classification and regression trees (C&RT)—A complete binary tree algorithm, which partitions data and produces accurate homogeneous subsets.
  • QUEST—A statistical algorithm that selects variables without bias and builds accurate binary trees quickly and efficiently.
• Selection or classification/prediction rules are generated in IBM SPSS Statistics syntax, SQL statements or simple text (through syntax).

Forecasting

• SPSS Statistics Professional enables you to deliver information in ways that your organization’s decision-makers can understand and use.
• It automatically determines the best-fitting ARIMA or exponential smoothing model to analyze your historic data.
• Hundreds of different time series can be modeled at once, rather than one variable at a time.
• Models are saved to a central file so that forecasts can be updated when data changes without having to re-set parameters or re-estimate models.
• Scripts can be written to update models with new data automatically.