SMHS LinearModeling
Contents
Scientific Methods for Health Sciences - Linear Modeling
The following sub-sections represent a blend of model-based and model-free scientific inference, forecasting and validity.
Statistical Software
This section briefly describes the pros and cons of different statistical software platforms.
Quality Control
Discussion of data Quality Control (QC) and Quality Assurance (QA) which represent important components of data-driven modeling, analytics and visualization.
Multiple Linear Regression
Review and demonstration of computing and visualizing the regression-model coefficients (effect-sizes), (fixed-effect) linear model assumptions, examination of residual plots, and independence.
Linear mixed effects analyses
Scientific inference based on fixed and random effect models, assumptions, and mixed effects logistic regression.
Machine Learning Algorithms
Data modeling, training , testing, forecasting, prediction, and simulation.
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