Epidemiology is a broad and fast emerging field, and proper use and understanding of its methods is a key element to conducting high-quality research. Regular review of existing tools in designing and conducting epidemiological studies will be of use to students and experienced researchers and will assist clinicians in conducting clinic-based research. In addition, such reviews provide a reference for reviewers and readers who are less familiar with the methods but want to assess the research quality.
To provide readers with an up-to-date overview of research methods in epidemiology. Papers can cover advanced topics or explain what to look for in research papers applying a specific design or using specific methods.
This Research Topic seeks papers that describe how to conduct epidemiological research in the clinical and population setting, as well as papers that describe reasoning and application of new epidemiological methods, using existing (open access) data, including annotated analysis scripts. Papers can be hands-on or review the current state of knowledge.
Topics can include but are not limited to:
Conducting hospital-based case-control studies
Conducting case-crossover studies
Variable selection for multivariable regression models
Distinguish aims in prediction and causal inference
Collider stratification bias (Table 2 fallacy)
How to set up directed acyclic graphs
Building prediction models
Statistical methods in meta-analyses or meta-research
Propensity score analyses
Data collection methods
How to deal with missing data
Use and misuse of statistical significance testing
How to impute, is multiple imputation always necessary or sufficient?
Competing risk, does ignoring (always) lead to bias?
Network meta-analysis, how to do it, what are the pitfalls?
How to assess the added value of predictors in time-to-event prediction models?
How to assess predictive performance in time-to-event models anyway?
What to do in diagnostic test accuracy research when there is no reference standard?
Adaptive randomized controlled trials
Priority setting in epidemiologic research
Starting and maintaining large cohort studies
Preventing data-fishing in large cohort studies
Setting up and conducting register studies
Data sharing in clinical trials - Open Science
Epidemiology is a broad and fast emerging field, and proper use and understanding of its methods is a key element to conducting high-quality research. Regular review of existing tools in designing and conducting epidemiological studies will be of use to students and experienced researchers and will assist clinicians in conducting clinic-based research. In addition, such reviews provide a reference for reviewers and readers who are less familiar with the methods but want to assess the research quality.
To provide readers with an up-to-date overview of research methods in epidemiology. Papers can cover advanced topics or explain what to look for in research papers applying a specific design or using specific methods.
This Research Topic seeks papers that describe how to conduct epidemiological research in the clinical and population setting, as well as papers that describe reasoning and application of new epidemiological methods, using existing (open access) data, including annotated analysis scripts. Papers can be hands-on or review the current state of knowledge.
Topics can include but are not limited to:
Conducting hospital-based case-control studies
Conducting case-crossover studies
Variable selection for multivariable regression models
Distinguish aims in prediction and causal inference
Collider stratification bias (Table 2 fallacy)
How to set up directed acyclic graphs
Building prediction models
Statistical methods in meta-analyses or meta-research
Propensity score analyses
Data collection methods
How to deal with missing data
Use and misuse of statistical significance testing
How to impute, is multiple imputation always necessary or sufficient?
Competing risk, does ignoring (always) lead to bias?
Network meta-analysis, how to do it, what are the pitfalls?
How to assess the added value of predictors in time-to-event prediction models?
How to assess predictive performance in time-to-event models anyway?
What to do in diagnostic test accuracy research when there is no reference standard?
Adaptive randomized controlled trials
Priority setting in epidemiologic research
Starting and maintaining large cohort studies
Preventing data-fishing in large cohort studies
Setting up and conducting register studies
Data sharing in clinical trials - Open Science