Advanced Statistical Analysis
With a highly trained team of analysts we are able to employ advanced statistical techniques to help answer research questions. Common serviceses include
- Identifying latent groups.
- Finding the key drivers of an outcome variable (binary or continuous).
- Identifying statistical differences and effects sizes from experimental data.
- Finding optimal combinations of variables.
- Determining the best model fit.
Using a mix of our own software programs and commercial packages such as R, SPSS, and Minitab, we are able to provide methods including:
- ANOVA and general linear modeling
- Factor analysis
- Cluster analysis
- Reliability analysis
- Rasch modeling
- Logistic regression
- Multiple linear regression analysis
- Latent class analysis (LCA)
- Structural equation modeling (SEM)
The MeasuringU team can assist with analysis, formal write-ups (e.g. APA style), and explanations of the methods, assumptions, and guidance on interpretations and next steps.