Find below a number of lists of useful resources covering research methods (in general) and specific to Computational Social Sciences and Cyberpsychology; programming in R; data science; media effects and other related areas.
- Research Methods and Tools
- R Programming Resources
- Interesting Blog Posts
Research Methods and Tools
- The 20% Statistician - A blog on statistics, methods, and open science.
- Simply Statistics - a blog on data science, analysis, and statistics
- Bit by Bit : Social Research in the Digital Age - Matthew Salganik (Open Book)
- Data Visualisation: A practical introduction - Kieran Healy (Open Book)
- Fundamentals of Data Visualisation: A primer on making informative and compelling figures - Claus Wilke (Open Book)
- Lakens, D. (2013). Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs. Frontiers in psychology, 4.
- Lakens, D., Scheel, A.M., Isager, P.M. (2018) Equivalence Testing for Psychological Research: A Tutorial. Advances in Methods and Practices in Psychological Science, 1-11.
- Greenland, S., Senn, S. J., Rothman, K. J., Carlin, J. B., Poole, C., Goodman, S. N., & Altman, D. G. (2016). Statistical tests, p values, confidence intervals, and power: a guide to misinterpretations. European journal of epidemiology, 31, 337–350.
- De Groot, A. D. (1956/2014). The meaning of “significance” for different types of research. Translated and annotated by Eric-Jan Wagenmakers, Denny Borsboom, Josine Verhagen, Rogier Kievit, Marjan Bakker, Angelique Cramer, Dora Matzke, Don Mellenbergh, and Han L. J. van der Maas. Acta Psychologica, 148 , 188–194.
- Kass, R. E., Caffo, B. S., Davidian, M., Meng, X. L., Yu, B., & Reid, N. (2016). Ten Simple Rules for Effective Statistical Practice. PLOS Comput Biol, 12(6), e1004961.
- Gilmore, R. O., Kennedy, J. L., & Adolph, K. E. (2018). Practical solutions for sharing data and materials from psychological research. Advances in Methods and Practices in Psychological Science, 1(1), 121-130
- van’t Veer, A. E., & Giner-Sorolla, R. (2016). Pre-registration in social psychology—A discussion and suggested template. Journal of Experimental Social Psychology, 67, 2- 12.
- Brandt, M. J., IJzerman, H., Dijksterhuis, A., Farach, F. J., Geller, J., Giner-Sorolla, R., … & van’t Veer, A. (2014). The replication recipe: What makes for a convincing replication? Journal of Experimental Social Psychology, 50, 217–224.
Qualitative Methods and Reporting
- Guest, G., Namey, E., & McKenna, K. (2016). How Many Focus Groups Are Enough? Building an Evidence Base for Nonprobability Sample Sizes. Field Methods, 29(1).
- Twining, P., Heller, R. S., Nussbaum, M., & Tsai, C. C. (2017). Some guidance on conducting and reporting qualitative studies. Computers & Education, 106
Quantitative Methods and Reporting
- Lopez, X., Valenzuela, J., Nussbaum, M., Tsai, C-C (2015). Some recommendations for the reporting of quantitative studies, Computers & Education, 91
Literature Synthesis and Reporting
- Templier, M., & Paré, G. (2018). Transparency in literature reviews: an assessment of reporting practices across review types and genres in top IS journals. European Journal of Information Systems, 27(5).
General Research Methodology
- Wagenmakers, E.-J., Wetzels, R., Borsboom, D., J., H. L., & Kievit, R. A. (2012). An Agenda for Purely Confirmatory Research. Perspectives on Psychological Science, 7(6).
R Programming Resources
First port of call: How do I…
- Top 50 ggplot2 Visualizations - 50 ggplot2 examples with full code
The R Graph Gallery - A gallery of useful figures produced with R
- Hands on Programming with R - A good first resource for learning R fundamentals
- The Art of R Programming - It’s a good resource for systematically learning fundamentals such as types of objects, control statements, variable scope, classes and debugging in R.
- R Cookbook - A quick and simple introduction to conducting many common statistical tasks with R.
- Exploratory Data Analysis with R - Basic analytical skills for all sorts of data in R.
- R Programming for Data Science - More advanced data analysis that relies on R programming.
- Report Writing for Data Science in R - R-based methods for reproducible research and report generation.
- R for Data Science - Free book from RStudio developers with emphasis on data science workflow.
- OpenIntro Statistics - A free online open introduction to statistics book
- The tidyverse style guide - a great how to on the tidyverse
- Answering Questions with data: Introductory statistics - open statistics textbook
- Learning Statistics with R - open statistics textbook (with datasets)
- An introduction to data cleaning with R - great overview on the processes of cleaning datasets with R
Interesting Blog Posts
If the list becomes unwieldy I’ll consider adding sections.
- A visual introduction to machine learning
- It’s the Effect Size, Stupid: What effect size is and why it is important
- Have smartphones really destroyed a generation? We don’t know
- 5 years into academia – 45 things I’ve learned so far …
- SQL one of the most valuable skills
- Data science is different now
- Data Science Foundations: Know your data. Really, really, know it
- How the BBC Visual and Data Journalism team works with graphics in R
- Wikipedia Data Scraping with R: rvest in Action
- Open letter to journal editors: dynamite plots must die
- Reproducible Research in Computational Sciences
- What is statistical power? An illustration using simulated data
- The Two Friends Who Changed How We Think About How We Think