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Mplus Statistical Software: An application with multiple data-modeling techniques

The Mplus statistical software can be utilized to conduct statistical analysis of diverse data type. The data can be variate, multi-variate, longitudinal, category ordered and category unordered among other data types.

In addition, to the accommodation of different data types, Mplus enables the data scientist to conduct research by application of latent and observed factors. The latent factor in a data-set is not measurable, whereas, the observed factor is measurable and therefore it can be viewed for comparison with the latent factor.

Further, the application of Mplus to the available data allows the researcher to use more than one latent factor and integrate it with other latent factors. Integration of latent factor with measurable or observable factors is also possible. It is this facility of multi-level and longitudinal integration of data that makes Mplus very unique.

The data modeling techniques that can be applied to a given data by using Mplus are as follows

  • Missing data modeling
  • Monte Carlo Simulation technique
  • Regression Analysis
  • Path Analysis
  • Exploratory Factor Analysis
  • Confirmatory Factor Analysis
  • Structural Equation Modeling
  • Growth Modeling
  • Discrete-time Survey Analysis
  • Continuous-time survival analysis

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