94 citations · 158 across the 24 of their papers we have counts for
27 papers
The role of discretization scales in causal inference with continuous-time treatment
Jinghao Sun, Forrest W. Crawford
There are well-established methods for identifying the causal effect of a time-varying treatment applied at discrete time points. However, in the real world, many treatments are co…
Causal identification for continuous-time stochastic processes
Jinghao Sun, Forrest W. Crawford
Many real-world processes are trajectories that may be regarded as continuous-time "functional data". Examples include patients' biomarker concentrations, environmental pollutant l…
A sample size heuristic for network scale-up studies
Nathaniel Josephs, Dennis M. Feehan, Forrest W. Crawford
The network scale-up method (NSUM) is a survey-based method for estimating the number of individuals in a hidden or hard-to-reach subgroup of a general population. In NSUM surveys,…
Causal identification of infectious disease intervention effects in a clustered population
Xiaoxuan Cai, Eben Kenah, Forrest W. Crawford
Causal identification of treatment effects for infectious disease outcomes in interconnected populations is challenging because infection outcomes may be transmissible to others, a…
Dependence-robust confidence intervals for capture-recapture surveys
Jinghao Sun, Luk Van Baelen, Els Plettinckx +1
Capture-recapture (CRC) surveys are used to estimate the size of a population whose members cannot be enumerated directly. CRC surveys have been used to estimate the number of Covi…
Identification of causal intervention effects under contagion
Xiaoxuan Cai, Wen Wei Loh, Forrest W. Crawford
Defining and identifying causal intervention effects for transmissible infectious disease outcomes is challenging because a treatment -- such as a vaccine -- given to one individua…
Efficient and minimal length parametric conformal prediction regions
Daniel J. Eck, Forrest W. Crawford
Conformal prediction methods construct prediction regions for iid data that are valid in finite samples. We provide two parametric conformal prediction regions that are applicable…
Interpretation of the individual effect under treatment spillover
Forrest W. Crawford, Olga Morozova, Ashley L. Buchanan +1
Some interventions may include important spillover or dissemination effects between study participants. For example, vaccines, cash transfers, and education programs may exert a ca…
Randomization for the susceptibility effect of an infectious disease intervention
Daniel J. Eck, Olga Morozova, Forrest W. Crawford
Randomized trials of infectious disease interventions, such as vaccines, often focus on groups of connected or potentially interacting individuals. When the pathogen of interest is…
Risk ratios for contagious outcomes
Olga Morozova, Ted Cohen, Forrest W. Crawford
The risk ratio is a popular tool for summarizing the relationship between a binary covariate and outcome, even when outcomes may be dependent. Investigations of infectious disease…
Estimating the Size of a Large Network and its Communities from a Random Sample
Lin Chen, Amin Karbasi, Forrest W. Crawford
Most real-world networks are too large to be measured or studied directly and there is substantial interest in estimating global network properties from smaller sub-samples. One of…
Direct likelihood-based inference for discretely observed stochastic compartmental models of infectious disease
Lam Si Tung Ho, Forrest W. Crawford, Marc A. Suchard
Stochastic compartmental models are important tools for understanding the course of infectious diseases epidemics in populations and in prospective evaluation of intervention polic…
Submodular Variational Inference for Network Reconstruction
Lin Chen, Forrest W Crawford, Amin Karbasi
In real-world and online social networks, individuals receive and transmit information in real time. Cascading information transmissions (e.g. phone calls, text messages, social me…
Birth/birth-death processes and their computable transition probabilities with biological applications
Lam Si Tung Ho, Jason Xu, Forrest W. Crawford +2
Birth-death processes track the size of a univariate population, but many biological systems involve interaction between populations, necessitating models for two or more populatio…
Confidence intervals for means under constrained dependence
Peter M. Aronow, Forrest W. Crawford, José R. Zubizarreta
We develop a general framework for conducting inference on the mean of dependent random variables given constraints on their dependency graph. We establish the consistency of an or…
Seeing the Unseen Network: Inferring Hidden Social Ties from Respondent-Driven Sampling
Lin Chen, Forrest W. Crawford, Amin Karbasi
Learning about the social structure of hidden and hard-to-reach populations --- such as drug users and sex workers --- is a major goal of epidemiological and public health research…
Identification of homophily and preferential recruitment in respondent-driven sampling
Forrest W. Crawford, Peter M. Aronow, Li Zeng +1
Respondent-driven sampling (RDS) is a link-tracing procedure for surveying hidden or hard-to-reach populations in which subjects recruit other subjects via their social network. Th…
Hidden population size estimation from respondent-driven sampling: a network approach
Forrest W. Crawford, Jiacheng Wu, Robert Heimer
Estimating the size of stigmatized, hidden, or hard-to-reach populations is a major problem in epidemiology, demography, and public health research. Capture-recapture and multiplie…
Nonparametric Identification for Respondent-Driven Sampling
Peter M. Aronow, Forrest W. Crawford
Respondent-driven sampling is a survey method for hidden or hard-to-reach populations in which sampled individuals recruit others in the study population via their social links. Th…
The graphical structure of respondent-driven sampling
Forrest W. Crawford
Respondent-driven sampling (RDS) is a chain-referral method for sampling members of a hidden or hard-to-reach population such as sex workers, homeless people, or drug users via the…
Sex, lies and self-reported counts: Bayesian mixture models for heaping in longitudinal count data via birth-death processes
Forrest W. Crawford, Robert E. Weiss, Marc A. Suchard
Surveys often ask respondents to report nonnegative counts, but respondents may misremember or round to a nearby multiple of 5 or 10. This phenomenon is called heaping, and the err…
On the distribution of interspecies correlation for Markov models of character evolution on Yule trees
Willem H. Mulder, Forrest W. Crawford
Efforts to reconstruct phylogenetic trees and understand evolutionary processes depend fundamentally on stochastic models of speciation and mutation. The simplest continuous-time m…
Combining List Experiment and Direct Question Estimates of Sensitive Behavior Prevalence
Peter M. Aronow, Alexander Coppock, Forrest W. Crawford +1
Survey respondents may give untruthful answers to sensitive questions when asked directly. In recent years, researchers have turned to the list experiment (also known as the item c…
Markov counting models for correlated binary responses
Forrest W. Crawford, Daniel Zelterman
We propose a class of continuous-time Markov counting processes for analyzing correlated binary data and establish a correspondence between these models and sums of exchangeable Be…