STAT 437
Statistical Methods for Life History Analysis
Administrative Information
Assignments and Solutions
Helper Code and Supplementary Notes
Lecture Videos, Slides, Notes, and Code
- (Lecture 001) Welcome to STAT 437
- (Lecture 002) What are longitudinal data?
- (Lecture 003) Exploring Longitudinal Data (Application)
- (Lecture 004) Notation for Longitudinal Data (Theory)
- (Lecture 005) What is Linear Regression (Review; Theory)
- (Lecture 006) Continuous Longitudinal Data: Why Can’t we Just Use Regression? (Linear Marginal Models)
- (Lecture 007) Linear Marginal Models: Likelihood, Inference, and Asymptotics (Theory)
- (Lecture 008) Linear Marginal Models: Implementation in R (Application)
- (Lecture 009) What are generalized linear models? (Review; Theory)
- (Lecture 010) Marginal Models: Accommodating non-continuous outcomes
- (Lecture 011) M-Estimation: A Practicing Statistician’s Best Friend (Conceptual, Theory, and Application)
- (Lecture 012) Generalized Estimating Equations: Estimating parameters from Marginal Models
- (Lecture 013) Generalized Estimating Equations: Examples of GEEs (Theory)
- (Lecture 014) Generalized Estimating Equations: Details of Asymptotic Inference (Theory)
- (Lecture 015) Generalized Estimating Equations: COVID-19 Example
- (Lecture 016) Generalized Estimating Equations: Epilepsy Trial Example
- (Lecture 017) From the Population to the Individual: Mixed Effects Models
- (Lecture 018) Linear Mixed Effects Models
- (Lecture 019) Linear Mixed Effects Models (Theory)
- (Lecture 020) Variance Testing Considerations: Constrained LRT
- (Lecture 021) Linear Mixed Effects Models (Application)
- (Lecture 022) Transition Models for Longitudinal Data
- (Lecture 023) Transition Models (Theory)
- (Lecture 024) Transition Models (Application)
- (Lecture 025) Handling Missing Data in Longitudinal Models
- (Lecture 026) Handling Missing Data in Longitudinal Models - MCAR, NMAR, and Likelihood Techniques
- (Lecture 027) Handling Missing Data in Longitudinal Models - Imputation and Weighting
- (Lecture 028) Recap of Longitudinal Methods
- (Lecture 029) Introduction to Time-to-Event Data
- (Lecture 030) Quantities of Interest for Survival Analysis
- (Lecture 031) Discrete Time to Event Data
- (Lecture 032) Discrete Time to Event Data (Theory)
- (Lecture 033) Discrete Time to Event Data Exploration (Application)
- (Lecture 034) Logistic Regression and Proportional Odds Models
- (Lecture 035) Logistic Regression and Proportional Odds Models (Application)
- (Lecture 036) Introduction to Continuous Time Survival Analysis
- (Lecture 037) Continuous Time Survival Analysis, Likelihood Construction (Theory)
- (Lecture 038) Location Scale Family Distributions, with log-linear Regression (Theory)
- (Lecture 039) Continuous Time Regression Models using Survreg (Application)
- (Lecture 040) Accelerated Failure Time Models
- (Lecture 041) Accelerated Failure Time Models (Theory)
- (Lecture 042) Accelerated Failure Time Models (Application)
- (Lecture 043) Proportional Hazards Models
- (Lecture 044) Proportional Hazards Models (Theory)
- (Lecture 045) Proportional Hazards Models (Application)
Data Files
To save these data files, right-click and save as. The data are presented for educational purposes only. Sources for the data are available in the data_import_helper.R script, and data should be used only to follow along with the relevant lectures. Any use of this data beyond these purposes needs to be cleared with the data owners.
| File Name | Modified |
|---|---|
| DogOwners.csv | 7/4/23 |
| Korea Income and Welfare.csv | 7/4/23 |
| TLC.csv | 7/4/23 |
| TLC_mar.csv | 7/4/23 |
| air_pollution.csv | 7/4/23 |
| air_pollution_NMAR.csv | 7/4/23 |
| aml.csv | 7/4/23 |
| customer_churn.csv | 7/4/23 |
| dental.csv | 7/4/23 |
| gold_medal_instagram.csv | 7/4/23 |
| job_code_table.csv | 7/4/23 |
| mort.csv | 7/4/23 |
| oasis_longitudinal.csv | 7/4/23 |
| ontario_by_phu.csv | 7/4/23 |
| pasta_sales.csv | 7/4/23 |
| schoolgirls.csv | 7/4/23 |
| seizures_full.csv | 7/4/23 |
| seizures_mcar.csv | 7/4/23 |
| stroke.csv | 7/4/23 |
| teachers.csv | 7/4/23 |
| wallstreet_sentiment.csv | 7/4/23 |
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