What is he best known for?
The fields of study he is best known for:
- Statistics
- Internal medicine
- Cancer
His scientific interests lie mostly in Econometrics, Relative survival, Statistics, Survival analysis and Proportional hazards model.
His Econometrics research integrates issues from Sample size determination, Markov chain Monte Carlo, Event and Meta-analysis, Random effects model.
Paul C. Lambert interconnects Life expectancy, Leukemia and Cancer survival in the investigation of issues within Relative survival.
His Statistics study frequently draws connections to other fields, such as Meta-regression.
Paul C. Lambert combines subjects such as Parametric statistics and Parametric model with his study of Survival analysis.
In his study, Disease is inextricably linked to Cancer, which falls within the broad field of Proportional hazards model.
His most cited work include:
- What to add to nothing? Use and avoidance of continuity corrections in meta‐analysis of sparse data (1041 citations)
- Meta-analysis of individual participant data: rationale, conduct, and reporting (901 citations)
- Pharmacological and lifestyle interventions to prevent or delay type 2 diabetes in people with impaired glucose tolerance: systematic review and meta-analysis (893 citations)
What are the main themes of his work throughout his whole career to date?
Paul C. Lambert spends much of his time researching Relative survival, Statistics, Survival analysis, Parametric statistics and Econometrics.
His biological study deals with issues like Colorectal cancer, which deal with fields such as Socioeconomic status.
His work carried out in the field of Survival analysis brings together such families of science as Population based, Gerontology, Component and Hazard ratio.
His work in Parametric statistics covers topics such as Proportional hazards model which are related to areas like Mathematical optimization.
The various areas that Paul C. Lambert examines in his Econometrics study include Event, Randomized controlled trial, Meta-analysis, Random effects model and Competing risks.
His studies in Cancer integrate themes in fields like Life expectancy and Incidence.
He most often published in these fields:
- Relative survival (60.38%)
- Statistics (42.81%)
- Survival analysis (43.45%)
What were the highlights of his more recent work (between 2019-2021)?
- Relative survival (60.38%)
- Statistics (42.81%)
- Cancer (34.19%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Relative survival, Statistics, Cancer, Survival analysis and Parametric statistics.
His studies deal with areas such as Event, Mortality rate, Age adjustment and Regression as well as Relative survival.
As part of his studies on Statistics, Paul C. Lambert often connects relevant areas like Prognostic model.
The concepts of his Survival analysis study are interwoven with issues in Sample size determination, Cohort study and Cohort.
His study focuses on the intersection of Parametric statistics and fields such as Hazard with connections in the field of Baseline, Calibration, Meta-analysis and Individual participant data.
He works mostly in the field of Cancer registry, limiting it down to topics relating to Surgery and, in certain cases, Disease, as a part of the same area of interest.
Between 2019 and 2021, his most popular works were:
- Temporal recalibration for improving prognostic model development and risk predictions in settings where survival is improving over time. (7 citations)
- Temporal recalibration for improving prognostic model development and risk predictions in settings where survival is improving over time. (7 citations)
- Marginal measures and causal effects using the relative survival framework. (4 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Internal medicine
- Cancer
Paul C. Lambert mainly investigates Cancer, Relative survival, Cancer survival, Net Survival and Completeness.
His Colorectal cancer study in the realm of Cancer interacts with subjects such as Causal effect.
His biological study spans a wide range of topics, including Stage, Patient survival and Population level.
To a larger extent, Paul C. Lambert studies Internal medicine with the aim of understanding Cancer survival.
His Net Survival study necessitates a more in-depth grasp of Cancer registry.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
