What’s new in IBM SPSS Statistics 29?
SURVREG AFT
SURVREG AFT matches accelerated failure time models with model effects proportional to survival time. See graph for sample output.

Linear Elastic Net Regression
Elastic Net can estimate linear regression models for dependent variables with one or multiple independent variables. See graph for sample output.

Linear Lasso Regression
Lasso estimates L1 loss-regularized regression models, and helps you display trace plots and select alpha hyperparameters. See graph for sample output.

Linear Ridge Regression
Ridge invokes the parametric survival model procedure with nonrecurrent lifetime data for more accurate failure time models. See graph for sample output.

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All SPSS features
Bootstrapping
Approximate the sampling distribution of an estimator by resampling the original dataset.
Missing values
Uncover missing data patterns, estimate summary statistics, and input missing values.
Data preparation
Streamline data preparation for more efficient analysis and more accurate conclusions.
Decision trees
Use decision trees and classification to identify relationships and predict outcomes.
Complex samples
Analyze statistical data and interpret survey results for complex samples.
IBM SPSS Statistics 29
Learn about the enhanced features and functionality of IBM® SPSS® Statistics 29