Some excellent research is done in all subject areas. This list is based on my perception of the proportion of publications in the indicated area that are rigorously scientific, reproducible, and useful.
Subject Areas With Least Reliable/Reproducible/Useful Research
- any area where there is no pre-specified statistical analysis plan and the analysis can change on the fly when initial results are disappointing
- behavioral psychology
- studies of corporations to find characteristics of "winners"; regression to the mean kicks in making predictions useless for changing your company
- animal experiments on fewer than 30 animals
- discovery genetics not making use of biology while doing large-scale variant/gene screening
- nutritional epidemiology
- electronic health record research reaching clinical conclusions without understanding confounding by indication and other limitations of data
- pre-post studies with no randomization
- non-nutritional epidemiology not having a fully pre-specified statistical analysis plan [few epidemiology papers use state-of-the-art statistical methods and have a sensitivity analysis related to unmeasured confounders]
- prediction studies based on dirty and inadequate data
- personalized medicine
- observational treatment comparisons that do not qualify for the second list (below)
- small adaptive dose-finding cancer trials (3+3 etc.)
Subject Areas With Most Reliable/Reproducible/Useful Research
- randomized crossover studies
- multi-center randomized experiments
- single-center randomized experiments with non-overly-optimistic sample sizes
- adaptive randomized clinical trials with large sample sizes
- pharmaceutical industry research that is overseen by FDA
- cardiovascular research
- observational research [however only a very small minority of observational research projects have a prospective analysis plan and high enough data quality to qualify for this list]
Some Suggested Remedies
Medical journals are reluctant to (1) publish critical letters to the editor and (2) retract papers. This has to change.
In academia, too much credit is still given to the quantity of publications and not to their quality and reproducibility. This too must change. The pharmaceutical industry has FDA to validate their research. The NIH does not serve this role for academia.
Rochelle Tractenberg, Chair of the American Statistical Association Committee on Professional Ethics and a biostatistician at Georgetown University said in a 2017-02-22 interview with The Australian that many questionable studies would not have been published had formal statistical reviews been done. When she reviews a paper she starts with the premise that the statistical analysis was incorrectly executed. She stated that "Bad statistics is bad science."