BERD House an online biostatistics resource managed by the Biostatistics, Epidemiology and Research Design (BERD) core of the ICTR Melissa J. Fazzari, Ph.D., M.S.BERD Director ICTR Biostatistics Core Biostatistics virtual walk-in clinic: Meet with a biostatistician without an appointment and obtain quick advice on your project. Every Tuesday virtual walk-in support between 3 - 5 pm via the following zoom link: https://einsteinmed.zoom.us/j/96403655408 Melissa J. Fazzari, Ph.D., M.S.BERD Director ICTR Biostatistics Core Statistics, Machine Learning, and Data Science Training: Getting Started Biostatistics Support and Guidelines Who can I meet with to discuss my project? The Division of Biostatistics offers biostatistics consulting and collaboration to enhance the quality and rigor of scientific research conducted by investigators at Einstein and Montefiore. Longer-term collaborations: Appointments with biostatistics faculty are available by appointment only. How do I get my data set ready for analysis? Best Practices Statistical Methods Common Statistical Tests How to Construct a Demographics Table An Introduction to Statistical Power An introduction to Logistic Regression Parametric vs non-parametric tests Standard Deviation vs Standard Error Box and Whisker Plots QQ Plots What is the Area under the ROC curve? Machine Learning Machine Learning: The basics Intro to Random Forest Gradient Boosting Tutorial An introduction to Penalized Regression Data Science 101 Coming Soon OMICS Data Analysis Coming Soon Study Design and Statistical Power An Introduction to Statistical Power Journal Club Coming Soon Announcements and Upcoming workshops Coming Soon Software and other Resources: R Software and Sample Codes How to download R Basic Syntax in R Programming R for Beginners Intro to R for Medical Data R Learning Resources Creating figures in R Video Tutorials Courses Continuous outcomes Testing for differences between 2 groups Testing for differences in more than 2 groups Categorical/binary outcomes Testing for association between two categorical variables Estimating a logistic regression model R Workshops: Course Material Introduction to R and Tidyverse workshop S1. Cheat sheet for dplyr S1. Intro to RStudio,Tidyverse and dplyr S1. Presentation on RStudio and dplyr part 1 S1. R code for Intro to dplyr S2. Presentation on dplyr part 2 S2. R code for dplyr part 2 S3. Presentation on dplyr part 3 S3. R code with solution S3. R code S4. Presentation on ggplot and knitr S4. R code for ggplot and knitr (HTML) S4. R code for ggplot and knitr (R markdown) Other Software Packages SPSS: Request via IT portal SAS: Email request Graphpad Prism: Request via IT portal Einstein software list Additional Resources UCLA IDRE VASSAR Stats Columbia Univ. Population Health Methods
