SPSS Statistics features

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For understanding licensing options: Subscription vs Perpetual, Base packs & addons

SPSS Statistics modules vs packages mapping

Depending on the license / subscription type opted, different combinations of modules (modules = set of features) are available in different packages. The mapping is as follows:

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SPSS Statistics features list

The exhaustive list of features as of July 2022, grouped into modules is as follows:

Data access and management

  • Compare two data files for compatibility
  • Data prep features: Define Variable Properties tool; Copy Data Properties tool, Visual Bander, Identify Duplicate Cases; Date/Time wizard
  • Data Restructure wizard: Single record to multiple records, Multiple records to single record
  • Direct Excel data access
  • Easier importing from Excel and CSV
  • Export data to SAS and current versions of Excel
  • Export/insert to Database wizard
  • Import data from IBM Cognos® Business Intelligence
  • Import/export to/from Dimensions
  • Import Stata files (until V14)
  • Long variable names
  • Longer value labels
  • Multiple datasets can be run in one SPSS session
  • ODBC Capture—DataDirect drivers
  • OLE DB data access
  • Password protection
  • SAS 7/8/9 data files including compressed files)
  • Text wizard
  • Unicode support
  • Very long text strings

Data preparation

  • Automated data preparation—enhanced modelviewer for automated data preparation
  • Validate data—streamline the process of validatingdata before analyzing it
  • Anomaly detection—identify unusual cases in amultivariate setting
  • Optimal binning

Graphs

  • Auto and cross correlation graphs
  • Basic graphs
  • Mapping (geospatial analysis)
  • Chart gallery
  • Chart options
  • Chart Builder UI for commonly used charts
  • Charts for multiple response variables
  • Graphics Production Language for custom charts
  • Interactive graphs-scriptable
  • Overlay and dual Y charts
  • Panelled charts
  • ROC analysis
  • Time series charts
  • Relationship map

Output

  • Case summaries
  • Style output
  • Conditional formatting
  • Codebook
  • Export charts as Microsoft Graphic Object
  • Export model as XML to Smart Score
  • Export to PDF
  • Export to Word/Excel/PowerPoint
  • HTML output

Help features

  • Application examples
  • Index
  • Tutorial
  • Extensions
  • Search

Data editor enhancements

  • Custom attributes for user-defined metadata
  • Spell checker
  • Splitter controls
  • Variable sets for wide data
  • Variable icons
  • Optimal binning
  • Improved performance for large pivot tables
  • OLAP cubes/pivot tables
  • Output management system
  • Output scripting
  • Reports summaries in rows and columns
  • Search and replace
  • Smart devices (tablets and phones)
  • Table to graph conversion
  • Web reports

Extended programmability

  • Custom UI builder enhancements (work seamlessly with Python and R and can be used in IBM SPSS Modeler)
  • New Extensions hub
  • Custom dialog builder for Extensions
  • Flow control or syntax jobs
  • Partial least squares regression
  • Python, .NET and Java for front-end scripting
  • SPSS equivalent of the SAS DATA STEP
  • Support for R algorithms and graphics
  • User-defined procedures

Statistics

  • ANOVA (in syntax only)
  • Automatic linear models
  • Cluster
  • Correlate—bivariate, partial, distances
  • Crosstabs–Define variable sets
  • Descriptive ratio statistics (PVA)
  • Descriptive
  • Discriminant analysis
  • Enhanced model viewer on two-step cluster and new nonparametric
  • Explore
  • Factor analysis
  • Frequencies
  • Geo-spatial analytics (STP and GSAR) (NEW!)
  • Improved performance for frequencies, crosstabs, descriptive
  • Power Analysis–(Statistics Base Server)
  • Matrix operations
  • Means
  • Monte Carlo simulation
  • Nearest neighbour analysis
  • New nonparametric tests
  • One way ANOVA
  • Ordinal regression (PLUM)
  • Ordinary least squares regression
  • Power Analysis
  • PP plots
  • QQ plots
  • Ratio
  • Reliability and ALSCAL multidimensional scaling
  • ROC curve
  • Compare ROC curves
  • Rule checking on secondary SPC charts
  • Summarize data
  • T tests: paired samples, independent samples, one-samples
  • Two-step cluster: categorical and continuous data/large data sets
  • Weighted Cohen’s kappa
  • Meta-analysis

Multithreaded algorithms

  • SORT

Bootstrapping

  • Sampling and pooling
  • Descriptive procedures that can be bootstrapped:
  • Correlations/nonparametric correlations
  • Crosstabs
  • Descriptives
  • Examine
  • Frequencies
  • Means
  • Partial correlations
  • T tests

Custom tables

  • 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

Regression

  • Binary logistic regression
  • Logit response models
  • Multinomial logistic regression
  • Nonlinear regression
  • Probit response analysis
  • Two stage least squares
  • Weighted least squares
  • Quantile regression

Advanced statistics

  • Cox regression
  • General linear modelling (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
  • Kaplan Meier
  • Linear mixed-level models (aka hierarchical linear models)
  • Survival
  • Variance component estimation

Complex samples (CS)

  • CS Cox regression (also multithreaded)
  • CS descriptives
  • CS general linear models
  • CS logistic regression
  • CS ordinal regression
  • CS selection
  • CS tabulate
  • Sampling wizard/Analysis Plan wizard

Exact tests

  • Cochran’s Q test
  • Contingency coefficient
  • Cramer’s V
  • Fisher’s exact test
  • Somers’ D—symmetric and asymmetric
  • Friedman test
  • Gamma
  • Goodman and Kruskal tau
  • Jonckheere-Terpstra test
  • Kappa
  • Kendall’s coefficient of concordance
  • Kendall’s tau-b and tau-c
  • Kruskal-Wallis test
  • Likelihood ratio test
  • Linear-by-linear association test
  • Mann-Whitney U or Wilcoxon rank-sum W test
  • Marginal homogeneity test
  • McNemar test
  • Median test
  • Pearson Chi-square test
  • Pearson’s R
  • Phi
  • Sign test
  • Spearman correlation
  • Uncertainty coefficient—symmetric or asymmetric
  • Wald-Wolfowitz runs test
  • Wilcoxon signed-rank test

Categories

  • Correspondence analysis (ANACOR)
  • Principal components analysis for categorical data (CATPCA; replaces PRINCALS)
  • Ridge regression, lasso, elastic net (CATREG)
  • CORRESPONDENCE
  • Nonlinear canonical correlation (OVERALS)
  • Multidimensional scaling for individual differences scaling with constraints (PROXSCAL)
  • Preference scaling (PREFSCAL; multidimensional unfolding)
  • Multiple correspondence analysis

Missing values

  • Data patterns table
  • Imputation with means estimation or regression
  • Listwise and pairwise statistics
  • Missing patterns table
  • Multiple imputation of missing data
  • Pooling

Conjoint

  • Estimate utilities (CONJOINT)
  • For conjoint analysis (ORTHOPLAN)
  • PLANCARDS

Decision trees

  • C&RT
  • CHAID
  • Exhaustive CHAID
  • QUEST

Forecasting

  • Auto regressive integrated moving average
  • Autoregression
  • Expert modeler exponential smoothing methods
  • Forecast multiple series (outcomes) at once
  • Temporal causal modelling
  • Seasonal decomposition
  • Spectral analysis

Neural networks

  • Multilayer perception
  • Radial basis function

Direct marketing

  • Cluster analysis
  • Contact profiling
  • Control package test
  • Propensity to purchase
  • RFM analysis: recency, frequency, monetary
  • Zip code response

 

AMOS (Structural Equation Modelling )

  • Bayesian estimation
  • Confirmatory factor analysis
  • Enter the model into a spreadsheet-like table (no programming)
  • Estimation of categorical and censored data
  • Latent class analysis
  • Non-graphical method of modeling
  • Structural equation modeling/path analysis
  • Specify path diagram using syntax