Blimp 3

The newly redesigned Blimp Studio offers a tabbed interface to keep your analysis files organized.
Blimp Studio automatically downloads new updates as they become available, so your software will always be current.

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The newest version of Blimp will automatically download new updates as they become available, so your software will always be current.

NEW!Blimp 3.0 Now Available!

Blimp 3 for Mac OS and Windows is now available. Blimp 3 includes new computational engine for single- and multilevel path and latent variable models with missing data. The factored/sequential estimation approach allows for easy specification of complex latent variable models that are difficult or impossible to estimate in a joint modeling framework (e.g., latent factors interacting with manifest variables, latent variable by latent variable interactions, random effects as predictors or outcomes).

Many new features for missing data handling, including simple specification of selection and pattern mixture models for missing not at random processes. Blimp was developed with funding from Institute of Educational Sciences awards R305D150056 (Craig Enders, PI; Roy Levy, Co-PI) and R305D190002 (Craig Enders, PI; Brian Keller and Han Du, Co-PIs).  Algorithmic development by Craig Enders, Brian Keller, and Han Du. C++ programming by Brian Keller. Qt graphical user interface development by Brian Keller.

Blimp 3 Features

  • Multiple-equation models (e.g., path models) with up to three levels
  • Latent variables and latent variable regressions
  • Latent variables with random effects, interactions, and nonlinear effects
  • Selection and pattern mixtures models for missing not at random processes
  • Parameter constraints
  • Auxiliary parameters that are functions of estimated parameters
  • Latent variable imputation
  • Yeo-Johnson modeling for skewed continuous variables
  • Binary and multinomial logistic regression
  • Negative binomial regression for count outcomes
  • Estimation with sampling weights
  • Facilities for computing new variables with numerous built-in functions
  • Built-in functions embedded within regression equations
  • Facilities for introducing custom univariate prior distributions
  • New Blimp Studio graphical user interface
  • Redesigned output with numerous enhancements and additional printing options
  • Better optimization and many algorithmic improvements
  • Enhanced user guide with dozens of new examples and analysis scripts