Applying the Mathematical MASS Model with R

سرفصل های دوره

This course focuses on capabilities, models, and datasets available within the MASS package in R. Along the way, you will gain knowledge of estimating survival probabilities and working with hazard rates in multi-state model.

1. Course Overview

1. Course Overview

2. Performing Qualitative and Quantitative Analysis Using MASS Datasets

01. Version Check

02. Prerequisites and Course Outline

03. Introducing the MASS Package

04. Qualitative and Quantitative Data

05. Hypothesis Testing Using t-tests

06. Hypothesis Testing Using ANOVA

07. Demo - Integrating with the MASS Package

08. Demo - Quantitative and Qualitative Analysis of Bi

09. Demo - Running t-tests on Birthweight Data

10. Demo - Quantitative and Qualitative Analysis of Ca

11. Demo - Executing ANOVA Analysis on Cars Data

12. Demo - Paired Sample t-test on Anorexia Data

3. Performing Predictive Analytics Using MASS Models

1. Principal Component Analysis - Intuition

2. Linear Discriminant Analysis and Quadratic Discriminant Analysis

3. Fitting Robust Linear Models

4. Demo - Linear Discriminant Analysis (LDA) and Visualization

5. Demo - LDA Using All Column Values

6. Demo - Quadratic Discriminant Analysis

7. Demo - Fitting a Robust Linear Model

8. Demo - Robust Regression Using the Boston Housing Dataset

4. Implementing Multi-state Models in R

01. Multi-state Models

02. Survival Models

03. Types of State Models

04. Understanding Weibull Distributions to Model State Transitions

05. Examples of Multi-state Models

06. The Kaplan-Meier Estimator and the Log Rank Test

07. Demo - Understanding the Multi-state Model Data

08. Demo - Modeling Transition Probabilities and Simulating Outcomes

09. Demo - Visualizing and Interpreting State Occupancy Probabilities

10. Demo - Modeling Survival Analysis

11. Demo - Log Rank Tests and the Proportional Hazards Model

12. Summary and Further Study

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تولید کننده: PluralSight