# 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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