# Biostatistics

## Biostatistics Lecture Series Videos

Past Biostatistics lectures are available for viewing on the BiostatisticsMCW YouTube page. Currently there are over 20 educational videos ranging from basic statistical topics to more advanced topics, such as Survival Analysis.

#### Video Topics & Abstract Brochure:

Contains the entire listing of Biostatistics lecture videos and abstracts.

Below you can find the full listing of video topics, abstracts, direct video links to YouTube, and each lecture's accompanying powerpoint.

 Analyzing Discrete Data: Describing discrete (categorical) data; graphical display; measure of association for binary outcomes; risk difference, relative risk, odds ratios; tests of association; Chi-square tests; Fisher’s exact test; introduction to logistic regression model ANOVA: Comparing More Than Two Treatments: Techniques for comparing the mean responses of two or more treatment groups (one way ANOVA); comparison of two factors (two way ANOVA); multiple comparisons Basic Concepts of Bayesian Statistics: What is Bayesian statistics; interpretation and assignment of probability; calibration of probability; conditional probability; Bayes Theorem; prior, posterior and predictive distributions; inference and prediction conditioned on full information; when Bayesian methods are particularly useful; individualized medicine; hierarchical and complex stochastic modeling; pooling of information; substantial extra-data information; adaptive clinical trials. Biostatistics Questions & Database Basics: Resources available in the Biostatistics Consulting Service; basic questions when planning a study; basic concepts of how to create a research database; types of data; spreadsheet vs. database Choosing Statistical Software: Introduction to some of the most commonly used statistical packages; comparison of the capabilities, availability, cost, and ease of use of the packages Common Errors in Linear Regression: Linear regression components, use graphs to check linear regression assumptions, linearity, constant variance, normality, outliers, multicollinearity, remedies Concepts on the Way from Data to Decisions: Hypothesis formulation; study-to-study variation; tests of hypothesis; type I and II errors; confidence intervals; planning a study Designing Clinical Trials: Dose-finding phase I designs; phase II designs; determination of sample size; the use of two stage designs Getting Help for Your Biostatistics Questions & Database Basics: Resources available in the Biostatistics Consulting Service; basic questions when planning a study; basic concepts of how to create a research database; types of data; spreadsheet vs. database Introduction to Survival Analysis: Censoring and truncation; Kaplan-Meier estimators; log rank tests; competing risks; cumulative incidence functions Introduction to Survival Analysis (11.8.13): Survival analysis; time-to-event data; event of interest in studies (e.g. death, recurrence of disease, development of complications after treatment); methods for partial data; regression methods; methods used to analyze competing risks data Logistical Regression: Simple logistic regression models for binary data; interpretation of regression coefficients in simple logistic regression; multiple logistic regression models; estimation and inference for logistic regression models; odds ratios; models for association; models for prediction/classification Longitudinal Analysis: Longitudinal studies; design for longitudinal studies; analysis for longitudinal studies; correlation between measurements; statistical methods to address correlation; missing data mechanism Matched Studies in Medical Research: The use of retrospective and prospective matching; Methods for comparison of treatment in matched studies with binary or continuous outcome; paired vs. unpaired t-tests; McNemar’s test Multiple Comparisons: Problem of multiple testing; familywise error rates; false discovery rates; multiple testing strategies; subgroup analysis; interim analysis Paired Data Analysis: Paired t-test; Sign Test; Wilcoxon Sign rank test; McNemar’s test Propensity Scores: Definition of propensity score; the background and motivation of developing propensity score method; propensity score estimation method; propensity score matching; estimating treatment effect using propensity including matched pair analysis and regression adjustment and stratification Reading Medical Literature: The main parts of a statistical paper; review of basic statistical concepts; reading the statistical methods and results section Methods for Equivalence and Non‐Inferiority Testing: Equivalence tests: tests designed to show two treatments have the same mean outcome; non-inferiority tests: tests to show a new treatment performs no worse than an existing test; confidence interval based tests Simple Statistics & Graphics in Excel: Data entry; descriptive statistics (mean, median, etc.); statistical inference (t-test, ANOVA, regression); how to create and enhance graphs (line, pie, bar) in Excel Simple Statistics in Excel: Entering and managing data in Excel; descriptive statistics; statistical inference in Excel including t-test, simple regression models; data analysis add-in Statistical Consideration in Grant Writing: Specific aims and hypotheses; specifying the study population; selecting a study design; defining outcome measures; sample size calculations; data analysis plan Statistical Graphics in Excel: Types of graphs in Excel: pie charts, bar charts, histograms, line graphs, scatter diagrams; properties of a good graph; modifying default graphs Statistics, Probability & Diagnostic Medicine: Sensitivity; specificity, positive and negative predictive value; the likelihood ratio;  the ROC curve Simple Linear Regression: Simple linear regression; fitting a line to data; interpretation and prediction; confidence intervals and hypothesis testing; measuring the strength of association; model checking; binary predictions Uses and Abuses of Non‐parametric Statistics: The sign and sign rank test for paired data; the Mann-Whitney Wilcoxon test for unpaired data Web-Based Sample Size Calculation: Statistical hypotheses, significance level and statistical power; free online website for sample size and power calculations Writing a Protocol: Protocol rational for prospective and retrospective studies; elements of a protocol