Easily manage the creation of structural equation models

Statistics Amos allows you toto specify,to estimate,evaluateAndpresentmodels to illustrate hypothesized relationships between variables. The module allows you to develop models more accurately than standard multivariate statistics techniques. Users can choose GUI (Graphical User Interface) or non-graphical program interface.

Statistics Amos allows you todevelop aptitude and behavioral modelsreflecting complex relationships.

The software:

• Provides proceduresSEM(Structural Equation Modeling)—easy to use and allows you to easily compare, confirm, and refine your models.

• Use analyticsBayesian—to improve model parameter estimates.

• Offers different data attribution methods—to create different datasets.

Provides SEM

• Quickly develop graphic templates using drag-and-drop drawing and editing tools.

• Create models that realistically reflect complex relationships.

• Use any numeric value, observed or latent, to predict any other numeric value.

• Use non-graphical scripting capabilities to handle complex models faster and to create similar models.

• Take advantage of multivariate analysis to extend standard methods, including regression, factor analysis, correlation, and analysis of variance.

Use Bayesian analysis

• Improve estimates by specifying a proactive distribution of information.

• Take advantage of the faster and automatically editable Markov Chain Monte Carlo (MCMC) computational method.

• Make estimates with sorted censored and categorical data.

• Specify user-defined values to predict using a simplified technique.

• Build models based on non-numeric data, without assigning numeric classifications to the data.

• Use censored data without employing extraordinary predictive procedures.

It offers different methods of data attribution

• Use regression attribution to create a single complete dataset.

• Use stochastic regression attribution or Bayesian attribution to create multiple attribution datasets.

• You can also attribute missing values or latent variable scores.

Data sheetStatistics Amos