TLR Guide
Stat342

Stat 305  Introduction to Biostatistical Methods for Health SciencesAt Simon Fraser University  Burnaby Campus SeptemberDecember (Fall) 2016 SFU Website Syllabus See Wk 11 notes for more details and some overriding information. Usual Office Hours: Monday, Wednesday, Thursday 34pm. In the statistics workshop. Assignments Assignment 1 Textbook pages for assignments Chapters 6 and 15 for Assignment 1 Filled Lecture Notes Week 1 , Syllabus and Policies Week 2 , Review: Probability and disease diagnostics, conditional probability, marginal, and Bayes rule Week 3, Part 1 , Defining a nominal variable, ChiSquared Tests (goodness of fit /1way, and independence / 2way), ROC curves Week 3, Part 2 , Odds and Odds Ratios Week 4 (Sept 26, 28), Worked examples, Uniform and Poisson distributions (briefly), Limitations of the chisquare test, expected cell size, and Fisherâ€™s exact test, Multiple 2x2 tables, Week 5 (Oct 3, 5), Simpsonâ€™s paradox, and the MantelHaenszel test. Using chisquared for Ordinal data. The Oridinal 'regression' coefficient. Reading discussion: The ASA discussion on pvalues. Review problems, and practice midterm. Week 6 (Oct 10, 12), No class on Thanksgiving, Oct 10. Midterm Oct 12 Week 7 (Oct 17, 19), Class on Oct 17 will be a video instead of live , Correlation vs association, Pearson's r (also called 'the correlation coefficient'), nonlinearity, Spearman rank correlation. Hypothesis testing for (Pearson) correlation, Correlation and regression. rsquared, (also called 'the coefficient of determination'), The bivariate normal assumption. Week 8 (Oct 24, 26), Examples using R: Basic functions, Regression, Diagnostic plots, specifically Residuals and Cook's Distance, Confidence bands, and Prediction bands. Week 9 (Oct 31, Nov 2), Multiple regression: specifically Colinearity, Perturbations, Variance Inflation Factors (VIFs), Polynomial terms and Interactions, Dummy Variables and Indicator variables Week 10 (Nov 7, 9), Akaike Information Criterion (AIC), the BIC, The Stepwise model selection method. Discussion of reading assignment on Causality, directed acyclic graphs (DAGs), and causality coeffients. Examples in Gerontology Week 11 (Nov 14, 16) , Review problems, and practice midterm. All of this will be assigned over the weekend and solved in class. Midterm 2 Nov 16 Week 12 (Nov 21, 23), How NOT to handle binary responses variables. Odds, Log Odds, and the Logit Function. Logistic Regression: examples, regression on two variables. Week 13 (Nov 28, 30), ShapiroWilks Test, Cross Validation and quantilequantile plots. Sampling basic, sampling weighting/bias, adaptive and snowball/Resp. Driven sampling. Case control studies. Funnel plots, if time permits. Week 14 (Dec 3, 5), Survival analysis including life tables. Censoring, KaplanMeier method, KaplanMeier plot. Cox proportion hazard test, logrank test. Last Day of Classes Dec 5 Week 15 (Dec 611), Finals review session or recorded session. Additional online support. Final exam Dec 12 Readings: Datasets: Secondary Resources:
