Anthony Costello on Twitter. (n.d.). Twitter. Retrieved 1 March 2021, from https://twitter.com/globalhlthtwit/status/1323747414923202562

(7) ReconfigBehSci on Twitter: “@ToddHorowitz3 probably- and I think there are many interesting questions around why he is there and whether he should be there. But to answer those properly, looking at the performance of the model seems important and interesting to me- that is all I am saying” / Twitter. (n.d.). Retrieved March 6, 2021, from https://twitter.com/SciBeh/status/1324389147050569734

ReconfigBehSci. (2020, November 5). A prediction to keep an eye on.. [Tweet]. @SciBeh. https://twitter.com/SciBeh/status/1324347728172847107

ReconfigBehSci. (2020, November 5). @ToddHorowitz3 2/2 so I would prefer to treat this as an opportunity for empirical observation and learning. Evaluation should focus on trying to assess actual contribution, not a priori judgments. [Tweet]. @SciBeh. https://twitter.com/SciBeh/status/1324367278352355330

‘Expert Reaction to Non-Peer Reviewed Modelling Presented on a Dashboard Suggesting That “a Herd Immunity Threshold (of 73.4%) Will Be Reached This Week on 9 April 2021” | Science Media Centre’. Accessed 12 April 2021. https://www.sciencemediacentre.org/expert-reaction-to-non-peer-reviewed-modelling-presented-on-a-dashboard-suggesting-that-a-herd-immunity-threshold-of-73-4-will-be-reached-this-week-on-9-april-2021/.

The impact of reopening schools on SARS-CoV-2 transmission in England. (n.d.). LSHTM. Retrieved 10 March 2021, from https://www.lshtm.ac.uk/newsevents/news/2021/impact-reopening-schools-sars-cov-2-transmission-england

ReconfigBehSci. (2021, March 5). RT @theAliceRoberts: A new study predicts the effect of fully reopening schools—Pushing R up from 0.8 to between 1.1-1.5. R is very abst… [Tweet]. @SciBeh. https://twitter.com/SciBeh/status/1369569328920727553

Confounding vs. Effect modification – The Stats Geek. (n.d.). Retrieved February 27, 2021, from https://thestatsgeek.com/2021/01/13/confounding-vs-effect-modification/

unnest_wider( data, col, names_sep = NULL, simplify = TRUE, names_repair = "check_unique", ptype = list(), transform = list() )

unnest_wider( data, col, names_sep = NULL, simplify = TRUE, names_repair = "check_unique", ptype = list(), transform = list() )

unnest_wider( data, col, names_sep = NULL, simplify = TRUE, names_repair = "check_unique", ptype = list(), transform = list() )

unnest_longer( data, col, values_to = NULL, indices_to = NULL, indices_include = NULL, names_repair = "check_unique", simplify = TRUE, ptype = list(), transform = list() )

unnest_longer( data, col, values_to = NULL, indices_to = NULL, indices_include = NULL, names_repair = "check_unique", simplify = TRUE, ptype = list(), transform = list() )

unnest_longer( data, col, values_to = NULL, indices_to = NULL, indices_include = NULL, names_repair = "check_unique", simplify = TRUE, ptype = list(), transform = list() )

unnest_wider( data, col, names_sep = NULL, simplify = TRUE, names_repair = "check_unique", ptype = list(), transform = list() )

unnest_wider( data, col, names_sep = NULL, simplify = TRUE, names_repair = "check_unique", ptype = list(), transform = list() )

hoist( .data, .col, ..., .remove = TRUE, .simplify = TRUE, .ptype = list(), .transform = list() )

"%>%" shortcut Ctrl + Shift + M

Medios de comunicación #NuevaMarquetalia

Tibbles: https://blog.rstudio.com/2016/03/24/tibble-1-0-0/#:~:text=There%20are%20two%20main%20differences,to%20work%20with%20large%20data.

Define variables, such as colors (e.g. $primary: #337ab7) in Sass (styles.scss) then compile to css for web.

R library "bootstraplib" built on foundation of "sass".

Use "run_with_themer()" to get a live preview GUI for customizing bootstrap theme.

Also, use "shinyOptions(plot.autocolors=TRUE)" at top of app to get plot outputs that respect Dark Mode.

CURSO R

plot() and lines() seem to plot regression lines

• Can they be added to a ggplot?
• Can they be used to print R2 on the plot?

Does it seem like Hadley still stands by this statement after tidy evaluation from this article <Do you need tidyeval>

Title

Gallagher, J. (2020, October 9). Covid cases increase rapidly as next steps planned. BBC News. https://www.bbc.com/news/health-54477618

Comparison of dashboard tech stack as of 10/2020:

aaronpeikert. (2020). Aaronpeikert/reproducible-research [TeX]. https://github.com/aaronpeikert/reproducible-research (Original work published 2019)

Viechtbauer, W. (2020). Wviechtb/forest_emojis [R]. https://github.com/wviechtb/forest_emojis (Original work published 2020)

Kretzschmar, M. E., Rozhnova, G., Bootsma, M. C. J., Boven, M. van, Wijgert, J. H. H. M. van de, & Bonten, M. J. M. (2020). Impact of delays on effectiveness of contact tracing strategies for COVID-19: A modelling study. The Lancet Public Health, 5(8), e452–e459. https://doi.org/10.1016/S2468-2667(20)30157-2

Adam, D. (2020). A guide to R — the pandemic’s misunderstood metric. Nature. https://doi.org/10.1038/d41586-020-02009-w

Starnini, M., Aleta, A., Tizzoni, M., & Moreno, Y. (2020). Impact of the accuracy of case-based surveillance data on the estimation of time-varying reproduction numbers. MedRxiv, 2020.06.26.20140871. https://doi.org/10.1101/2020.06.26.20140871

Wilson, C. (n.d.). First coronavirus R numbers for regions within England released. New Scientist. Retrieved June 15, 2020, from https://www.newscientist.com/article/2246029-first-coronavirus-r-numbers-for-regions-within-england-released/

Farboodi, M., Jarosch, G., & Shimer, R. (2020). Internal and External Effects of Social Distancing in a Pandemic (Working Paper No. 27059; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27059

Working with Census microdata. (n.d.). Retrieved July 31, 2020, from https://walker-data.com/tidycensus/articles/pums-data.html

Holcombe, A. O., Kovacs, M., Aust, F., & Aczel, B. (2020). Tenzing: Documenting contributorship using CRediT [Preprint]. MetaArXiv. https://doi.org/10.31222/osf.io/b6ywe

Spiegelhalter, D. (2020, July 5). Risks, R numbers and raw data: How to interpret coronavirus statistics. The Observer. https://www.theguardian.com/world/2020/jul/05/risks-r-numbers-and-raw-data-how-to-interpret-coronavirus-statistics

Liverpool, C. W., Jessica Hamzelou, Adam Vaughan, Conrad Quilty-Harper and Layal. (n.d.). Covid-19 news: Almost 20,000 care home deaths in England and Wales. New Scientist. Retrieved July 6, 2020, from https://www.newscientist.com/article/2237475-covid-19-news-almost-20000-care-home-deaths-in-england-and-wales/

Introducing JASP 0.13. (2020, July 2). JASP - Free and User-Friendly Statistical Software. https://jasp-stats.org/?p=6483

Du, H., Jiang, G., & Ke, Z. (2020). A Bootstrap Based Between-Study Heterogeneity Test in Meta-Analysis [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/de4g9

Matthias #WashYourHands Egger on Twitter: “The effective reproduction number Re is now above 1 in #Switzerland: 1.28 (95% 1.06-1.53). We urgently need an in-depth understanding of transmission dynamics, the effectiveness of contact tracing etc. And #MaskUp https://t.co/24E5o4jYiS” / Twitter. (n.d.). Twitter. Retrieved June 30, 2020, from https://twitter.com/eggersnsf/status/1276882802173247490

Mathur, M. B., & VanderWeele, T. J. (2020). New statistical metrics for multisite replication projects. Journal of the Royal Statistical Society: Series A (Statistics in Society), 183(3), 1145–1166. https://doi.org/10.1111/rssa.12572

Vaughan, A. (n.d.). R number. New Scientist. Retrieved June 29, 2020, from https://www.newscientist.com/term/r-number/

See r/yiffinhell on Reddit.

Privacy Preserving Data Analysis of Personal Data (May 27, 2020). (n.d.). Retrieved June 25, 2020, from https://www.youtube.com/watch?time_continue=11&v=wRI84xP0cVw&feature=emb_logo

Maier, M., Bartoš, F., & Wagenmakers, E.-J. (2020). Robust Bayesian Meta-Analysis: Addressing Publication Bias with Model-Averaging [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/u4cns

Coronavirus: R number jumps to 1.79 in Germany after abattoir outbreak. (n.d.). Sky News. Retrieved June 22, 2020, from https://news.sky.com/story/coronavirus-r-number-jumps-to-1-79-in-germany-after-abattoir-outbreak-12011468

Rocker

Different results between SAS, R, Stata, SPSS

License of libraries in R

• In general bioscience and academia, S ---> R has built over years its position of one of the industry standards
• In clinical research, however, SAS reigns par excellence
• Pharmaceutical companies, CROs and even FDA do use R “internally”.But they resist (or hesitate) to use it in submissions (to FDA)
• Clinical Programmer or Biostatistician ≝ SAS Programmer. Period

Differences between R and SAS:

• origin of dates
• default contrasts
• used sum of squares
• calculation of quantiles
• generation of random numbers
• implementation of advanced model
• representation of floating point numbers

Revolution R

Hironori Funabiki on Twitter

Willem, L., Hoang, T. V., Funk, S., Coletti, P., Beutels, P., & Hens, N. (2020). SOCRATES: An online tool leveraging a social contact data sharing initiative to assess mitigation strategies for COVID-19 [Preprint]. Epidemiology. https://doi.org/10.1101/2020.03.03.20030627

Dablander, F. (2020, June 11). Interactive exploration of COVID-19 exit strategies. R-Bloggers. https://www.r-bloggers.com/interactive-exploration-of-covid-19-exit-strategies/

Ggplot2 extensions. (n.d.). Retrieved June 14, 2020, from https://exts.ggplot2.tidyverse.org/

Views, R. (2020, May 20). An R View into Epidemiology. /2020/05/20/some-r-resources-for-epidemiology/

Bail, C. A. (2016). Combining natural language processing and network analysis to examine how advocacy organizations stimulate conversation on social media. Proceedings of the National Academy of Sciences, 113(42), 11823–11828. https://doi.org/10.1073/pnas.1607151113

Rosenbusch, H., Hilbert, L. P., Evans, A. M., & Zeelenberg, M. (2020). StatBreak: Identifying “Lucky” Data Points Through Genetic Algorithms. Advances in Methods and Practices in Psychological Science, 2515245920917950. https://doi.org/10.1177/2515245920917950

Peikert, A., & Brandmaier, A. M. (2019). A Reproducible Data Analysis Workflow with R Markdown, Git, Make, and Docker. https://doi.org/10.31234/osf.io/8xzqy

Samuel, J.; Ali, G.G.M.N.; Rahman, M.M.; Esawi, E.; Samuel, Y. COVID-19 Public Sentiment Insights and Machine Learning for Tweets Classification. Preprints 2020, 2020050015 (doi: 10.20944/preprints202005.0015.v1)

Davis, N. (2020, May 4). Rival Sage group says Covid-19 policy must be clarified. The Guardian. https://www.theguardian.com/world/2020/may/04/rival-sage-group-covid-19-policy-clarified-david-king

Puleo, M., & Staff Writer (2020 March 18). New study says “high temperature and high relative humidity significantly reduce” spread of COVID-19. https://www.accuweather.com/en/health-wellness/new-study-says-high-temperature-and-high-relative-humidity-significantly-reduce-spread-of-covid-19/703418

Liu, Y., Eggo, R. M., & Kucharski, A. J. (2020). Secondary attack rate and superspreading events for SARS-CoV-2. The Lancet, 395(10227), e47. https://doi.org/10.1016/S0140-6736(20)30462-1

Endo, A., Centre for the Mathematical Modelling of Infectious Diseases COVID-19 Working Group, Abbott, S., Kucharski, A. J., & Funk, S. (2020). Estimating the overdispersion in COVID-19 transmission using outbreak sizes outside China. Wellcome Open Research, 5, 67. https://doi.org/10.12688/wellcomeopenres.15842.1

Carl T. Bergstrom on Twitter

R today - UK

The Santa Fe Institute - SFI Transmission PDF

Bi, Q., Wu, Y., Mei, S., Ye, C., Zou, X., Zhang, Z., Liu, X., Wei, L., Truelove, S. A., Zhang, T., Gao, W., Cheng, C., Tang, X., Wu, X., Wu, Y., Sun, B., Huang, S., Sun, Y., Zhang, J., … Feng, T. (2020). Epidemiology and transmission of COVID-19 in 391 cases and 1286 of their close contacts in Shenzhen, China: A retrospective cohort study. The Lancet Infectious Diseases, S1473309920302875. https://doi.org/10.1016/S1473-3099(20)30287-5

You can create estimation plots with:

• this website
• R package
• Python package
• MATLAB package

McElreath, R. Statistical Rethinking: A Bayesian Course Using R and Stan Github.com. https://github.com/rmcelreath/statrethinking_winter2019

Entire course with materials online.

R 4.0.0 now available, and a look back at R’s history. (n.d.). Revolutions. Retrieved April 30, 2020, from https://blog.revolutionanalytics.com/2020/04/r-400-is-released.html

James, E. Tutorial Home. Github.io. https://emljames.github.io/GorillaR/

Multilevel correlations: A new method for common problems. (2020 April 13). R-bloggers. https://www.r-bloggers.com/multilevel-correlations-a-new-method-for-common-problems/

Petermr/openVirus. (n.d.). GitHub. Retrieved April 8, 2020, from https://github.com/petermr/openVirus

Pharma industry is one of the most rewarding industries, especially now

Clinical Research is highly conservative, making SAS macros applicable for decades. Unfortunately, that's not the same case with R

The normal distribution in r

Generating random data in r

R provides a wide range of functions for obtaining summary statistics. One method of obtaining descriptive statistics is to use the sapply( ) function with a specified summary statistic.

The same basic structure for all Shiny apps:

1. ui object.
2. server function.
3. call to the shinyApp function.

---> examples <---

UI example of a Shiny app (check the code below)

Server example of a Shiny app (check the code below):

• random distribution is plotted as a histogram with the requested number of bins
• code that generates the plot is wrapped in a call to renderPlot

Using Python scripts inside R Shiny (in 6 steps):

1. In ui.R create textOutput: textOutput("textOutput") (after plotoutput()).
2. In server.R create handler: output$textOutput <- renderText({ }].
3. Create python_ref.py and insert this code:
4. Import reticulate library: library(reticulate).
5. source_python() function will make Python available in R:
6. Make sure you've these files in your directory:

• app.R
• python_ref.py and that you've imported the reticulate package to R Environment and sourced the script inside your R code.

Hit run.

Shiny > Dash:

• Dash isn't yet as stabilised
• Shiny has much more layout options, whereas in Dash you need to utilise HTML and CSS
• developing new components in Dash needs ReactJS knowledge (not so easy)

Typical tools used for working with Shiny

why does he use 'within' rather than mutate?

What is valence in music according to Spotify?