ReviewPopulation studies2016
Bayesian demography 250 years after Bayes.
Review in Population studies, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed.
- Musculoskeletal surgeons use mixed reasoning rather than pure Bayesian strategies in clinical practice.PloS one · 2026Article
- Exploring the Various Sources of Mortality Estimation in Ghana: A Scoping Review of Data Sources, Challenges, and Opportunities.Healthcare (Basel, Switzerland) · 2025Review
- Multiregional Population Forecasting: A Unifying Probabilistic Approach for Modelling the Components of Change.European journal of population = Revue europeenne de demographie · 2025Article
- Article
- Exploiting the Bayesian approach to derive counts of married women of reproductive age across Cameroon for healthcare planning, 2000-2030.Scientific reports · 2022Article
- Bayesian variable selection using Knockoffs with applications to genomics.Computational statistics · 2022Article
- Challenges of Modeling Outcomes for Surgical Infections: A Word of Caution.Surgical infections · 2021Article
- Guest Editorial: Spatial demography in regional science.Journal of geographical systems · 2021Article
- Article
- Bayesian estimation of pharmacokinetic parameters: an important component to include in the teaching of clinical pharmacokinetics and therapeutic drug monitoring.Research in pharmaceutical sciences · 2020Review
- Jointly Estimating Subnational Mortality for Multiple Populations.Demographic researchArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Bayesian statistics offers an alternative to classical (frequentist) statistics. It is distinguished by its use of probability distributions to describe uncertain quantities, which leads to elegant solutions to many difficult statistical problems. Although Bayesian demography, like Bayesian statistics more generally, is around 250 years old, only recently has it begun to flourish. The aim of this paper is to review the achievements of Bayesian demography, address some misconceptions, and make the case for wider use of Bayesian methods in population studies. We focus on three applications: demographic forecasts, limited data, and highly structured or complex models. The key advantages of Bayesian methods are the ability to integrate information from multiple sources and to describe uncertainty coherently. Bayesian methods also allow for including additional (prior) information next to the data sample. As such, Bayesian approaches are complementary to many traditional methods, which can be productively re-expressed in Bayesian terms.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.