What is he best known for?
The fields of study he is best known for:
- Statistics
- Internal medicine
- Normal distribution
His primary scientific interests are in Meta-analysis, Econometrics, Random effects model, Multivariate statistics and Statistics.
His Meta-analysis research includes themes of Systematic review and Data science.
His research on Econometrics often connects related topics like Bayesian probability.
The concepts of his Random effects model study are interwoven with issues in Inference, Medical statistics and Statistical inference.
His Multivariate statistics research is multidisciplinary, incorporating perspectives in Meta-regression and Multivariate analysis.
In the field of Statistics, his study on Confidence interval, Estimator and Statistic overlaps with subjects such as Restricted maximum likelihood and Power analysis.
His most cited work include:
- Consistency and inconsistency in network meta‐analysis: concepts and models for multi‐arm studies (665 citations)
- Consistency and inconsistency in network meta‐analysis: model estimation using multivariate meta‐regression (495 citations)
- Extending DerSimonian and Laird's methodology to perform multivariate random effects meta-analyses. (385 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Meta-analysis, Statistics, Econometrics, Random effects model and Confidence interval.
His biological study spans a wide range of topics, including Odds ratio, Statistical hypothesis testing, Endovascular aneurysm repair, Surgery and Systematic review.
His study in the field of Multivariate statistics, Regression analysis and Statistic is also linked to topics like Restricted maximum likelihood.
His Multivariate statistics research includes elements of Multivariate analysis and Consistency.
His study in Econometrics is interdisciplinary in nature, drawing from both Medical statistics, Publication bias, Bayesian probability and Coverage probability.
His Random effects model study also includes
- Estimator and related Moment,
- Data mining which connect with Markov chain Monte Carlo.
He most often published in these fields:
- Meta-analysis (56.00%)
- Statistics (40.00%)
- Econometrics (40.00%)
What were the highlights of his more recent work (between 2017-2021)?
- Meta-analysis (56.00%)
- Statistics (40.00%)
- Econometrics (40.00%)
In recent papers he was focusing on the following fields of study:
Dan Jackson mainly focuses on Meta-analysis, Statistics, Econometrics, Random effects model and Confidence interval.
The Meta-analysis study combines topics in areas such as Odds ratio, Contrast, Outcome, Bivariate analysis and Surrogate endpoint.
His study in the field of Multivariate statistics, Generalized linear mixed model and Method of moments also crosses realms of Restricted maximum likelihood and Context.
His Multivariate statistics study focuses on Univariate in particular.
His Econometrics research includes themes of Publication bias, Pairwise comparison, Bayesian probability, Normality and Data science.
His Random effects model study incorporates themes from Prediction interval, Systematic review, Linear model, Inference and Estimator.
Between 2017 and 2021, his most popular works were:
- A comparison of heterogeneity variance estimators in simulated random-effects meta-analyses (106 citations)
- A comparison of seven random-effects models for meta-analyses that estimate the summary odds ratio. (64 citations)
- When should meta-analysis avoid making hidden normality assumptions? (62 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Internal medicine
- Normal distribution
Dan Jackson mainly investigates Meta-analysis, Random effects model, Statistics, Econometrics and Confidence interval.
In his works, Dan Jackson performs multidisciplinary study on Meta-analysis and Statistical analyses.
As part of his studies on Random effects model, Dan Jackson frequently links adjacent subjects like Normality.
His study focuses on the intersection of Statistics and fields such as Inference with connections in the field of Estimator, Generalized linear mixed model and Statistical inference.
Dan Jackson has researched Econometrics in several fields, including Prior probability, Bayesian probability, Pairwise comparison and Sparse data sets.
Dan Jackson focuses mostly in the field of Confidence interval, narrowing it down to matters related to Systematic review and, in some cases, Endovascular aneurysm repair, Odds ratio, Point estimation and Outcome.
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