Biostatistic Resource Lists for CFAR Investigator

By Sources

Boston area course/seminar series

Harvard Chan SPH Biostatistics Lecture Courses

How to access

  • There are no free programs
  • According to school rules, unofficial auditing is NOT allowed
  • The audit has to be built into the course grading options
  • Cost per credit for the 2017-2018 academic year was $1,303.00. Harvard Affiliates do not receive a discount on tuition. (More about Non-degree programs for Harvard Affiliates)
  • There is a tuition assistance program (TAP). TAP recipients have to pay 10% of tuition. (More about TAP)

Selected course list (click each course for more details)

  • BST 201: Introduction to Statistical Methods
  • BST 210: Applied Regression Analysis
  • BST 212: Survey Research Methods in Community Health
  • BST 213: Applied Regression for Clinical Research
  • BST 222: Basics of Statistical Inference
  • BST 223: Applied Survival Analysis
  • BST 226: Applied Longitudinal Analysis
  • BST 227: Introduction to Statistical Genetics
  • BST 228: Applied Bayesian Analysis
  • BST 232: Methods I
  • BST 263: Applied Machine Learning
  • BST 267: Introduction to Social and Biological Networks

Harvard Catalyst Biostatistics Seminars

About this seminar series

  • This is a Biostatistics Continuing Education program by Harvard Catalyst.
  • The target audience is Harvard Catalyst statisticians and other quantitative researchers.
  • This is open/free to the CFAR investigators as well.
  • Although all seminars are not necessary related to the HIV/AIDS research, some talks might be relevant and useful for the CFAR investigators.
  • The past seminars can be seen from here

How Its Done Seminar

About this seminar series

  • This is a monthly seminar series by Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute.
  • The aim of this seminar series is to provide participants with useful examples and a framework on which to build their own projects.
  • This is open to the CFAR investigators as well
  • Seminar location is CLSB Building, 11FL, room 11081
  • Although all topics are not necessary related to the HIV/AIDS research, some talks might be relevant and useful for the CFAR investigators.
  • The past and upcoming talks can be seen from here
  • Some previous seminars that might have been relevant to the CFAR investigators are listed below.
    • How many mice? What on earth do I do with their data? (by Donna Neuberg)
    • Decision Curve Analysis (by Giovanni Parmigiani)
    • Next Generation Sequencing Pipelines (by Naim Rashid)
    • Propensity Score (by Cory Zigler)

Online books

Statistics at Square One (BMJ online)

About this source

  • This is an online book and free to access
  • This is an introductory level and no prior statistical or mathematical knowledge would be required.
  • Each section has an illustrating example and several exercises and the answers.
  • No computer package would be necessary to do the examples and exercises.
  • Topics to be covered (Chapter list)
    1. Data display and summary
    2. Mean and standard deviation
    3. Populations and samples
    4. Statements of probability and confidence intervals
    5. Differences between means: type I and type II errors and power
    6. Differences between percentages and paired alternatives
    7. The t tests
    8. The chi-squared tests
    9. Exact probability test
    10. Rank score tests
    11. Correlation and regression
    12. Survival analysis
    13. Study design and choosing a statistical test

Statistical Sleuth in R

About this source

  • This is an online textbook and free to access
  • This is an introductory level and no prior statistical or mathematical knowledge would be required.
  • The text is written in R Markdown. So, the R code and the result are displayed together, which would help readers to learn how to do it with R.
  • No prior knowledge about R would be necessary to read the contents.
  • Examples are not necessary related to clinical/laboratory research.
  • Topics to be covered (Chapter list)
    1. 2 group comparisons and resampling
    2. 2 group comparisons using t-tests
    3. a closer look at assumptions
    4. non-parametric 2 group comparisons
    5. more than 2 groups
    6. linear combinations and multiple comparisons
    7. linear regression
    8. even more linear regression
    9. multiple regression
    10. inference for multiple regression
    11. model checking and refinement
    12. variable selection
    13. two-way ANOVA

Online tutorials by software ventors

Video Tutorial on using Stata

About this source

  • StataCorp is continuously posting short video tutorials to illustrate how to implement various statistical analysis methods with Stata.
  • This is free and does not require a license of Stata to view the tutorials.
  • The length of each video is about a few minutes. Each video uses a data example, but the examples are not necessary related to medical research. The video content focuses on how to implement a particular statistical method by Stata; theories or details of the method is not covered in this tutorial.
  • This source would be useful for those who are using Stata or plan to use Stata.

Online data analysis examples

UCLA Data Analysis Examples (by UCLA Institute for Digital Research and Education Search)

About this source

  • This is free to access.
  • The website contains pages that illustrate the application of statistical analysis techniques using several statistical packages (i.e., Stata, SAS, SPSS, Mplus, and R). Each page has a sample data and analysis. An explanation of the output is also provided. References in each page would be also useful.
  • The pages are designed to introduce only the essence of the technique. No prior math/stat knowledge would be required. No equations in the pages.
  • The examples are not necessary related to medical research but often hypothetical examples just for illustrating purpose.
  • Topics to be covered on this page are:
    • Robust Regression
    • Logistic Regression
    • Exact Logistic Regression
    • Multinomial Logistic Regression
    • Ordinal Logistic Regression
    • Probit Regression
    • Poisson Regression
    • Negative Binomial Regression
    • Zero-inflated Poisson Regression
    • Zero-inflated Negative Binomial Regression
    • Zero-truncated Poisson
    • Zero-truncated Negative Binomial
    • Tobit Regression
    • Truncated Regression
    • Interval Regression
    • One-way MANOVA
    • Discriminant Function Analysis
    • Canonical Correlation Analysis
    • Multivariate Multiple Regression
    • Generalized Linear Mixed Models
    • Mixed Effects Logistic Regression
    • Latent Class Analysis
    • Power analysis: Single-sample t-test
    • Power analysis: Paired-sample t-test
    • Power analysis: Independent-sample t-test
    • Power analysis: Two Independent Proportions
    • Power analysis: One-way ANOVA
    • Power analysis: Multiple Regression
    • Power analysis: Accuracy in Parameter Estimation


BMJ Research Methods and Reporting section

About this source

  • BMJ has a specific section for articles that discuss research methods. This section includes research reporting guidelines as well.
  • The target audience of those articles is the readers of BMJ (mostly doctors). No prior math/stat knowledge is required to fully understand the materials.
  • The articles are accessible via Harvard library (or subscription)
  • Various topics are covered. The whole list can be seen from here.

The American Journal of Clinical Nutrition: Best (but oft-forgotten) practices series

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JAMA: Guide to Statistics and Methods series

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