Predictive Modeling
We help you develop analytical plans to answer your research questions. We use the latest techniques in data visualization, descriptive analytics, advanced analytics, and reporting. We have extensive experience conducting data mining, multivariate analyses, statistical, econometric, and predictive modeling. We use both supervised and unsupervised machine learning.
The most common techniques we use include:
General Linear Models and other regression models including MANOVA and ANCOVA models, as well as logistic, non-linear, and hierarchical regression models
Bayesian analytic approaches that consider prior probabilities, including Bayesians neural network models
CHAID and CART decision tree analyses
Cluster analysis using both frequentist (e.g., K-means cluster) and Bayesian models like Latent Class Analysis
Structural equation modeling
Survival analyses
We help you develop analytical plans to answer your research questions. We use the latest techniques in data visualization, descriptive analytics, advanced analytics, and reporting. We have extensive experience conducting data mining, multivariate analyses, statistical, econometric, and predictive modeling. We use both supervised and unsupervised machine learning.
The most common techniques we use include:
General Linear Models and other regression models including MANOVA and ANCOVA models, as well as logistic, non-linear, and hierarchical regression models
Bayesian analytic approaches that consider prior probabilities, including Bayesians neural network models
CHAID and CART decision tree analyses
Cluster analysis using both frequentist (e.g., K-means cluster) and Bayesian models like Latent Class Analysis
Structural equation modeling
Survival analyses
We help you develop analytical plans to answer your research questions. We use the latest techniques in data visualization, descriptive analytics, advanced analytics, and reporting. We have extensive experience conducting data mining, multivariate analyses, statistical, econometric, and predictive modeling. We use both supervised and unsupervised machine learning.
The most common techniques we use include:
General Linear Models and other regression models including MANOVA and ANCOVA models, as well as logistic, non-linear, and hierarchical regression models
Bayesian analytic approaches that consider prior probabilities, including Bayesians neural network models
CHAID and CART decision tree analyses
Cluster analysis using both frequentist (e.g., K-means cluster) and Bayesian models like Latent Class Analysis
Structural equation modeling
Survival analyses