IBM® SPSS® Statistics Standard Edition includes all the Base Edition capabilities plus features that support advanced modeling options, regression analysis and custom tables.
Take advantage of various regression procedures including logistic regression, quantile regression and more. Use advanced statistics procedures such as GLM multivariate, variance components analysis, life tables and Bayesian statistics. Summarize your data and display analyses in production-ready tables with the Custom Tables module.
Boost your analytics with these features
Predict categorical outcomes and apply various nonlinear regression procedures.
Use the Bayesian inference method of statistical inference to update the probability for a hypothesis as more information becomes available.
Multivariate general linear modeling (GLM)
Use GLM multivariate modeling to model the value of multiple dependent variables based on their relationships to categorical and scale predictors. GLM repeated measures allows repeated measurements of multiple dependent variables.
Summarize SPSS Statistics data, and display your analyses as presentation-quality, production-ready tables. Use analytics capabilities and advanced features to build tables to interpret and learn from data.
Generalized linear models and generalized estimating equations
Expand the general linear model with the generalized linear models procedure so that the dependent variable is linearly related to the factors and covariates through a specified link function. Use the generalized estimating equations procedure to analyze repeated measurements or other correlated observations.
Use life tables to examine the distribution of time-to-event variables, including by levels of a factor variable; Kaplan-Meier survival analysis for examining the distribution of time-to-event variables, including by levels of a factor variable or producing separate analyses by levels of a stratification variable; and Cox regression for modeling the time to a specified event, based upon the values of given covariates.
Standard Edition features
- Binary logistic regression
- Logit response models
- Multinomial logistic regression
- Nonlinear regression
- Probit response analysis, two-stage least squares, weighted least squares, quantile regression
- Cox regression
- General linear modeling (GLM), general factorial, multivariate (MANOVA), repeated measures, variance components
- Generalized linear models and generalized estimating equations, gamma regression, Poisson regression, negative binomial
- GENLOG for loglinear and logit
- Generalized linear mixed models (GLMM) (ordinal targets included)
- Bayesian statistics
- Hierarchical loglinear models
- Linear mixed-level models (aka hierarchical linear models)
- Variance component estimation
- 35 descriptive statistics
- Drag-and-drop interface
- Inferential statistics
- Nested tables
- Place totals in any row, column, or layer
- Post computed categories
- Effective base for weighted sample results
- Put multiple variables into the same table
- Significance tests on multiple response variables
- Significance test in custom tables main table
- Significance values for column means and column proportion tests
- Specialized multiple response set tables
- False discovery correction method for multiple comparisons
- Syntax converter
- Table preview