Deconfounding#
Here are the main deconfounding techniques used in research and analysis:
Statistical Methods#
Randomization: Randomly assign subjects to treatment groups to ensure equal distribution of known and unknown confounding variables[2][5].
Restriction: Limit study participants to those with similar values of potential confounding variables, eliminating variation in confounders[2][5].
Matching: Pair subjects in treatment groups with counterparts in comparison groups who share the same confounding variable values[2][5].
Statistical Control: Include potential confounders as variables in regression analysis[2].
Advanced Techniques#
Stratification: Distribute confounders evenly within separate strata or groups for analysis[8].
Multivariate Modeling: Use statistical models to handle multiple covariates and confounders simultaneously[9].
Standardization: Use a standard reference population to negate the effects of confounding factors like age and sex[10].
Modern Approaches#
Latent Variable Inference: Use recurrent neural networks (RNNs) to infer unobserved confounders from historical data[16].
Variational Autoencoder Deconfounding: Remove latent features correlated with confounders using specialized neural network architectures[7].
Propensity Score Methods: Estimate the probability of receiving treatment based on subject characteristics using logistic regression models[15].
Citations: [1] https://www.medrxiv.org/content/10.1101/2024.09.20.24314055v1 [2] https://www.scribbr.co.uk/faqs/how-do-i-prevent-confounding-variables-from-interfering-with-my-research/ [3] https://academic.oup.com/bib/article-abstract/25/6/bbae512/7824239 [4] https://www.tandfonline.com/doi/full/10.1080/01621459.2023.2240461 [5] https://www.scribbr.co.uk/research-methods/confounding-variable/ [6] https://openreview.net/forum?id=ryxDjjCqtQ [7] https://academic.oup.com/bib/article/25/6/bbae512/7824239 [8] https://www.statsdirect.com/help/basics/confounding.htm [9] https://pmc.ncbi.nlm.nih.gov/articles/PMC4017459/ [10] https://www.healthknowledge.org.uk/public-health-textbook/research-methods/1a-epidemiology/biases [11] https://www.turing.ac.uk/sites/default/files/2020-07/time_series_deconfounder.pdf [12] https://www.nngroup.com/articles/confounding-variables-quantitative-ux/ [13] https://www.turing.ac.uk/news/publications/time-series-deconfounder-estimating-treatment-effects-over-time-presence-hidden [14] https://pubmed.ncbi.nlm.nih.gov/24834204/ [15] https://handbook-5-1.cochrane.org/chapter_13/13_6_2_1_controlling_for_confounding.htm [16] https://arxiv.org/html/2410.20423v1 [17] https://proceedings.mlr.press/v236/hatt24a.html