Medical statistics and Data Science: Epidemiology

Quantitative Bais Aanlysis in Epidemiology

We are still working on it.
     

News:

A new book “An introduction to Directed Acyclic Graph (DAG) for health researchers” has been published in Amazon in the 21st December 2024

An introduction to Directed Acyclic Graph (DAG) for health researchers

The book description:

"Directed acyclic graph (DAG) is increasingly used in modern epidemiology, especially guide researchers to implementing causal inference in observational studies. Casual DAG visually presents causal knowledge and assumptions between variables. Once one can manage the rules, it can facilitate many tasks, such as using DAG makes it easier to understand many concepts for example direct and indirect causal effects, mediation analysis, collider stratification bias, selection bias, and information bias, etc. It also makes easier to recognize and avoid mistakes in analytic decisions such as using the backdoor criterion to select variables to be adjusted."

"More advanced texts on DAGs are readily available in textbooks and in scientific papers, but a simple and comprehensive introduction to DAG is lacking."

"The book thoroughly introduces DAG in a plain language from the scratch, step by step with more simple and accessible language explaining the concepts, terminologies, rules, and potential applications. The book will pave the way for researchers using DAG."

Contents

Background

underdevelopment

Install Stata commands

  • biasepi
    • Second verion of Stata-package biasepi is ready. It includs three Stata commands (biascon, biasmis, and biasselect) to perform simple bias analysis, multidimensional bias analysis, multiple bias modelinging in epidemiological data. Combining the existing Stata commands, the package is capable to perform probabilitic bias analysis. Type and run "ssc describe biasepi" in the Stata command window. You should be able to view and download the commands.

      Be aware: you may have to remove the older version, if so, the following may help.

      • PC: Go to C driver → ado → plus → b, remove biasepi, biasselect, biascon, biasmis
      • Mac: Go to Folder → Library → Application support → Stata → Plus → b, remove biasepi, biasselect, biascon, biasmis

  • episens
    • In the Stata command window, type "search episens", you should be able find the information on command "episens" by Nicola Orsini et al.4

Selection bias

  • Single bias analysis
  • Multiple bias analysis
  • Probalistic bias analysis

Unmeasured and Unknown Confounders

  • Single bias analysis
  • Multiple bias analysis
  • Probalistic bias analysis

Misclassification

  • Single bias analysis
  • Multiple bias analysis
  • Probalistic bias analysis

References

  1. Lash TL, Fox MP, MacLehose RF, Maldonado G, McCandless LC, Greenland S. Good practices for quantitative bias analysis. Int J Epidemiol. 2014 Link
  2. Fox MP, Lash TL. On the Need for Quantitative Bias Analysis in the Peer-Review Process. Am J Epidemiol. 2017 Link
  3. Lash TL, Fox MP, and Fink AK. Applying Quantitative Bias Analysis to Epidemiologic Data Link
  4. Orsini N, Bellocco R, Bottai M, Wolk A, and Greenland S. A tool for deterministic and probabilistic sensitivity analysis of epidemiologic studies Link