9 citations · 11 across the 5 of their papers we have counts for
6 papers
Applied Statistics Requires Scientific Context
Ashley I Naimi
Statistical methods are indispensable to scientific inference. However, there exists a longstanding tension across a wide range of scientific disciplines about the role that ``cont…
Monte Carlo Integration in Simple and Complex Simulation Designs
Ashley I. Naimi, David Benkeser, Jacqueline E. Rudolph
Simulation studies are used to evaluate and compare the properties of statistical methods in controlled experimental settings. In most cases, performing a simulation study requires…
The Metropolis algorithm: A useful tool for epidemiologists
Alexander P Keil, Jessie K Edwards, Ashley I Naimi +1
The Metropolis algorithm is a Markov chain Monte Carlo (MCMC) algorithm used to simulate from parameter distributions of interest, such as generalized linear model parameters. The…
Efficient Generalization and Transportation
Zhenghao Zeng, Edward H. Kennedy, Lisa M. Bodnar +1
When estimating causal effects, it is important to assess external validity, i.e., determine how useful a given study is to inform a practical question for a specific target popula…
Incremental Intervention Effects in Studies with Dropout and Many Timepoints
Kwangho Kim, Edward H. Kennedy, Ashley I. Naimi
Modern longitudinal studies collect feature data at many timepoints, often of the same order of sample size. Such studies are typically affected by {dropout} and positivity violati…
Challenges in Obtaining Valid Causal Effect Estimates with Machine Learning Algorithms
Ashley I Naimi, Alan E Mishler, Edward H Kennedy
Unlike parametric regression, machine learning (ML) methods do not generally require precise knowledge of the true data generating mechanisms. As such, numerous authors have advoca…