ArticleAmerican journal of epidemiology2022
Using Numerical Methods to Design Simulations: Revisiting the Balancing Intercept.
Article in American journal of epidemiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed.
- REFINE2: a simplified simulation tool to help epidemiologists evaluate the suitability and sensitivity of effect estimation within user-specified data.American journal of epidemiology · 2026Article
- A Two-Stage Method for Extending Inferences From a Collection of Trials.Statistics in medicine · 2025Article
- Accounting for nonmonotone missing data using inverse probability weighting.Statistics in medicine · 2023Observational
- Efficient and robust methods for causally interpretable meta-analysis: Transporting inferences from multiple randomized trials to a target population.Biometrics · 2023Article
- RE: "USING NUMERICAL METHODS TO DESIGN SIMULATIONS: REVISITING THE BALANCING INTERCEPT".American journal of epidemiology · 2022Article
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3 authors.
Funding
Abstract
In this paper, we consider methods for generating draws of a binary random variable whose expectation conditional on covariates follows a logistic regression model with known covariate coefficients. We examine approximations for finding a "balancing intercept," that is, a value for the intercept of the logistic model that leads to a desired marginal expectation for the binary random variable. We show that a recently proposed analytical approximation can produce inaccurate results, especially when targeting more extreme marginal expectations or when the linear predictor of the regression model has high variance. We then formulate the balancing intercept as a solution to an integral equation, implement a numerical approximation for solving the equation based on Monte Carlo methods, and show that the approximation works well in practice. Our approach to the basic problem of the balancing intercept provides an example of a broadly applicable strategy for formulating and solving problems that arise in the design of simulation studies used to evaluate or teach epidemiologic methods.
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