AY2023

Biostatistics Practicum 2 (advanced programming using Stata and R)

(Adjunct lecturer at Graduate School of Public Health, St. Luke's International University)

Course Information

Course number: 5002040

Meeting time: 18:00-20:15 every Thursday

Room: None - online

Office hours: by email appointment

Teaching assistant: Khin Maung Soe July

Zoom link and password: will be provided via the manaba system

Syllabus: can be downloaded here.

Course Materials

Class 1 (Sep 8):  Review of Biostatistics I: with Stata

Class 2 (Sep 15):  Review of Biostatistics I: with Stata (cont.)

Class 3 (Sep 22): Analysis of Variance (ANOVA) in Stata

Class 4 (Sep 29): Introduction to R software

Class 5 (Oct 6): Introduction to R software (cont.)

Class 6 (Oct 13): Analysis of Variance (ANOVA) in R      Assignment 1: ANOVA exercise (R or Stata at students’ choice)

Class 7 (Oct 20): Simple and Multiple Linear Regression Models: assumptions, model fit in Stata

Class 8 (Oct 27): Simple and Multiple Linear Regression Models: model fit, confounding, mediation and interaction in R         Assignment 2: Linear regression (R or Stata at students’ choice)

Class 9 (Nov 10):  Logistic Regression Models: Single and multiple predictor models; assumptions, model fits and interpreting the parameters’ estimates in Stata

Class 10 (Nov 17): Logistic Regression Models: Single and multiple predictor models; assumptions, model fits and interpreting the parameters’ estimates in R

Class 11 (Nov 24): Loglinear Regression Models (Poisson Model) in Stata

Class 12 (Dec 1): Loglinear Regression Models (Poisson Model) in R                                                                                                                            Assignment 3: Logistic regression and Poisson model (R or Stata at students’ choice)

Class 13 (Dec 8):  Survival analysis in R: Survival time, censoring, survival functions, Kaplan-Meier estimate and Log-rank Test

Class 14 (Dec 15):  Survival analysis in R: Hazard functions, Cox’s proportional hazards model, interpretation of the model parameters Assignment 4: Survival analysis (R or Stata at students’ choice)

Class 15 (Dec 22):  Survival analysis in Stata

Economic Statistics (Statistics and programming using R)

(Adjunct lecturer at Faculty of Liberal Arts, Sophia University)

Course Information

Course number: IBE340

Meeting time: 10:55-12:35 every Monday and Thursday

Room: 2-310

Office hours: by email appointment

Teaching assistant: None

Syllabus: can be downloaded here

Course Materials

Class 1:  Introduction

Class 2:  Review of Probability and Statistics

Class 3: Review of Probability and Statistics (cont.)

Class 4: Review of Probability and Statistics (cont.)

Class 5: Simple regression

Class 6: Simple regression (cont.)

Class 7: Simple regression (cont.)

Class 8: Multiple Regression: Estimation

Class 9:  Multiple Regression: Estimation (cont)

Class 10: Multiple Regression: Estimation (cont.)

Class 11: Multiple Regression: Inference

Class 12: Multiple Regression: Inference (cont.)

Class 13: Multiple Regression: Inference (cont.)

Class 14: Catch-up & Review

Class 15: Mid-term Exam

Class 16: Multiple Regression: Specification

Class 17: Multiple Regression: Specification (cont.)

Class 18: Multiple Regression: Specification (cont.)

Class 19: Multiple Regression: Assessing Empirical Studies

Class 20: Multiple Regression: Assessing Empirical Studies (cont.)

Class 21: Panel Data

Class 22: Panel Data (cont.)

Class 23: Instrument Variable Regression

Class 24: Instrument Variable Regression (cont.)

Class 25: Presentation

Class 26: Presentation (cont.)

Class 27: Catch-up & Review

Class 28: Final Exam