Evidence-based suggestions for a statistics roadmap
Some interesting links to get an overview of the most used statistical methods and tools:
- https://quantifyinghealth.com/popular-statistical-tests-and-models/
- https://quantifyinghealth.com/statistical-software-popularity-in-research/
- https://quantifyinghealth.com/programming-languages-popularity-in-research/
- https://www.kdnuggets.com/polls/
- https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4105959 (Free To Use Statistical Software: Comparing Statistical Analyses 58 Pages Posted: 23 May 2022)
- https://psyarxiv.com/9pnkw/ (Free and (Mostly) Open Source Data Analysis Software for Academic Research 2021)
"I analyzed the methods sections of 43,110 randomly chosen research papers, uploaded to PubMed Central between the years 2016 and 2021, in order to check the popularity of 125 statistical methods in medical research.
The most popular statistical tests in research articles are:
- Student’s t-test: Used to compare the mean of a population to a theoretical value, or compare means between 2 populations.
- Chi-square test: Used to compare 2 proportions.
- Mann-Whitney U test: Used to compare medians between 2 populations.
- One-way ANOVA and Kruskal-Wallis test: Used to compare means between more than 2 populations.
- Kaplan-Meier estimator: Used to estimate the survival function when analyzing time-to-event data.
- Log-rank test: Used to compare survival times between 2 groups.
The most popular statistical models in research articles are:
- Logistic regression: Used to study the relationship between 1 or more predictor variables and 1 binary outcome variable.
- Linear regression: Used to study the relationship between 1 or more predictor variables and 1 continuous outcome variable.
- Cox regression: Used to study the relationship between 1 or more predictor variables and the survival time of patients. "
Popularity of 125 Statistical Tests and Models 2016-2021: Popularity_of_125_Statistical_Tests_and_Models_0A2016-2021.ods
Source: https://www.kdnuggets.com/2019/04/top-data-science-machine-learning-methods-2018-2019.html
Source: https://www.kdnuggets.com/2017/12/top-data-science-machine-learning-methods.html/2
The "Stats with R" course by Manny Gimond roughly corresponds with the above priorities: https://mgimond.github.io/Stats-in-R/index.html
- T and Z tests (https://mgimond.github.io/Stats-in-R/z_t_tests.html)
- F-test (https://mgimond.github.io/Stats-in-R/F_test.html)
- Confidence intervals (https://mgimond.github.io/Stats-in-R/CI.html)
- Chi-Square tests (https://mgimond.github.io/Stats-in-R/ChiSquare_test.html)
- Linear regression (https://mgimond.github.io/Stats-in-R/regression.html)
- Logistic regression (https://mgimond.github.io/Stats-in-R/Logistic.html)
- ANOVA (https://mgimond.github.io/Stats-in-R/ANOVA.html)
QtiPlot already supports most of the top tests: https://qtiplot.com/statistics.html.