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1. Resources for learning Stata
2. Statistical graphics (mostly using Stata)
3. Tutorials on useful and advanced analysis techniques using Stata
4. Grant writing and developing grant proposals
5. Resources from the Equator Network for reporting research
6. Resources for Systematic Reviews and Evidence based-medicine
7. Sample size and power calculators
8. Other statistical resources
1. Resources for learning Stata
Over 300 short videos covering almost any aspect of using Stata you might want to learn more about (running specific statistical procedures or models, data management, etc) organised by topic.
A forum for Stata users to ask, and have questions answered by other Stata users or StataCorp Staff. All questions and answers are archived and searchable.
UCLA Statistical Methods and Data Analytics have extensive resources on learning Stata and other statistical programs. The Stata resources include Classes and seminars, learning modules, Data analysis and textbook examples, and the annotated output for frequently used statistical tests is very helpful.
Also useful is their webpage on Choosing the correct statistical test in SAS, Stata, SPSS and R
Past-proceedings of Stata Conferences in different Countries have useful presentations and downloads.
Stata offers free webinars on a variety of topics through the year. Recordings, slides, do-files and other resources for past webinars are available after you register.
The Stata Journal has articles about statistics, data analysis, new community contributed programs as well as tips and articles about using Stata effectively.
Richard Williams Stata highlights
Useful lecture notes and datasets on a range of topics from Professor Richard Williams, University of Notre Dame
Stata tutorial and other resources by Professor Germán Rodríguez (from Princeton)
This site has excellent links to lecture notes, Stata and R coding and datasets, for generalised linear models (GLM), Multilevel models, Survival analysis and Demography.
Getting started with Stata (Dr Oscar Torres-Reyna from Princeton University)
An older resource, but still relevant.
2. Statistical graphics (mostly using Stata)
Stata graph gallery. Excellent resource with pictures and code to reproduce graphs, by Survey Design and Analysis Services Pty Ltd, Australia.
Graph workflow: Crafting truthful data graphs, by Dr Demetris Christodoulou
A site dedicated to data visualisation with theory and explanations. Click on the graph to get the code to apply it to your own data.
Professor Ben Jann’s webpages which provide documentation, help files and examples for some his excellent Stata programs, a number of which are relevant to data visualisation, including coefplot, grstyle and palettes.
The Stata Guide by Dr Asjad Naqvi. Dr Naqvi is a data visualisation genius and has written many programs which can be installed and used within Stata. His github page has links to his presentations from Stata conferences, code and example graphs and other useful resources.
Stata Visual library – inspiration and code for data visualisation in Stata from the World Bank. See the Summary Statistics and Impact Evaluation menus.
The panel labelled Stata visual library is mislabelled but takes you to R code for data visualisation in economics, many of which have relevant to biomedical research.
These webpages also have links relevant to development research in practice, and impact evaluation developed by DIME, the World Bank’s Impact Evaluation Department.
3. Tutorials on useful and advanced analysis techniques using Stata
Survival analysis tutorials, by Paul Dickman (Karolinska Institute)
Tutorials on survival analysis, multistate models and joint models, by Michael Crowther (Red Door Analytics)
Tools and Tutorials by Tyler VanderWeele (Harvard T.H. Chan School of Public Health). Includes E-values for assessing unmeasured confounding, Interactions and Causal mediation
Decision curve analysis tutorials (Memorial Sloan Kettering Cancer Center)
Decision curve analysis evaluates models and diagnostic tests in terms of their clinical consequences. Documents and code (code in Stata, R, SAS and Python) are available.
4. Grant writing and developing grant proposals
Statistical aspects of grant proposals
A General Statistical Guide for Grant Applications, by Martin Bland et al, for St George’s Hospital Medical School, University of London
This checklist helps you to know which parts of the guide are relevant to your application.
Grant writing resources for US NIH grants
Write your application – NIH Grants and Funding
Sample grant applications from the NIAID. Examples of exceptional applications and summary statements for US National Institute of Allergy and Infectious Diseases research grant applications. There are also links to example forms and letters relevant to NIH grants.
Grant writing tutorials and tip sheets for NIH Research Grants
5. Resources from the Equator Network for reporting research
The equator network (Enhancing the QUAlity and Transparency Of health Research) website has links to over 550 reporting guidelines for many different study types, including RCTs, Observational studies, Diagnostic/Prognostic studies, Systematic reviews, Case reports, Economic evaluations, pre-clinical animal studies and more. Extension statements cover variations that are relevant to specific study types, interventions, and diseases.
Not sure where to start? Try with this searchable index.
Other useful tools from this website include How to write a great research paper using reporting guidelines, and Using reporting guidelines to help you peer review research
6. Resources for Systematic Reviews and Evidence based-medicine
The Cochrane Handbook for Systematic Reviews of Interventions
The Cochrane Handbook for Systematic Reviews of Diagnostic Test Accuracy
Cochrane Online learning resources relevant to systematic reviews and evidence-based medicine
The GRADE handbook describes the process of rating the quality of the best available evidence and developing health care recommendations following the approach proposed by the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) Working Group
Catalogue of Bias, Centre for Evidence-Based Medicine, Oxford University
Tutorial on meta-analysis Biases.
Mathur, M. and VanderWeele, T.J. (2022). Methods to address confounding and other biases in meta-analyses: review and recommendations. Annual Review of Public Health, 43:19-35.
7. Sample size and power calculators
Many sample size calculators are available in Stata. Using the menus navigate to: Statistics > Power, precision, and sample size. For video demonstrations on the multiple tools available, navigate here, and expand the menu ‘Power, precision and sample size’.
There are also many useful community contributed programs which can be installed into Stata including ART — ANALYSIS OF RESOURCES FOR TRIALS. Suite of commands for complex sample size calculations in randomized controlled trials with a survival or a binary outcome, by the MRC Clinical Trials Unit at University College London)
type net install art into the command window, and after installation type help art
Useful articles describing how to use these programs are available at https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7614770/, and https://onlinelibrary.wiley.com/doi/10.1002/sim.2517
PS: Power and Sample size calculation by William Dupont and Walton D Plummer.
Downloadable program (Windows)
Statistical considerations for clinical trials and scientific experiments (Prof David A. Schoenfeld, Massachusetts General Hospital Mallincrkrodt General Clinical Research Center).
n4studies (available for Android and iOS) and n4studies Plus (currently available only for iOS) are useful mobile apps developed by Thai biostatisticians.
8. Other statistical resources
Statistical graphics Course and relevant links from Vanderbilt Medical Centre Biostatistics Department
Course notes for Regression Modelling Strategies by Prof Frank Harrell Jr (Vanderbilt Medical Centre Biostatistics Department).
The Second edition of the e-textbook by the same author is downloadable from the MDCU Medical Library: Regression Modeling Strategies: With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis / by Frank E. Harrell , Jr.
Prof. Harrell’s Statistical problems to document and avoid: Author checklist is also useful.