Aggregating predictions from experts: a scoping review of statistical methods, experiments, and applications

Download Paper Abstract Forecasts support decision making in a variety of applications. Statistical models can produce accurate forecasts given abundant training data, but when data is sparse or rapidly changing, statistical models may not be able to make accurate predictions. Expert judgmental forecasts—models that combine expert-generated predictions into a single forecast—can make predictions when training data is limited by relying on human intuition. Researchers have proposed a wide array of algorithms to combine expert predictions into a single forecast, but there is no consensus on an optimal aggregation model....

June 2020 · Thomas McAndrew, Nutcha Wattanachit, Casey Gibson, Nicholas G. Reich

An expert judgment model to predict early stages of the COVID-19 outbreak in the United States

Compared to fixed effect models, random effects suffer lower bias and trade inflated type I errors for improved power. Contrasting hazard rates between trials prevent accurate estimates from both fixed and random effects models.

January 2019 · tom mcandrew

Crossing points in survival analysis sensitively depend on system conditions

Crossing survival curves complicate how we interpret results from a clinical trial’s primary endpoint. We find the function to determine a crossing point’s location depends exponentially on individual survival curves. This exponential relationship between survival curves and the crossing point transforms small survival curve errors into large crossing point errors. In most cases, crossing points are sensitive to individual survival errors and may make accurately locating a crossing point unsuccessful. We argue more complicated analyses for mitigating crossing points should be reserved only after first exploring a crossing point’s variability, or hypothesis tests account for crossing point variability....

January 2018 · tom mcandrew

Reply & Supply: Efficient crowdsourcing when workers do more than answer questions

By modeling question sets as networks of interrelated questions, we introduce algorithms to help curtail the growth bias by efficiently distributing workers between exploring new questions and addressing current questions.

August 2017 · Thomas C McAndrew, Elizaveta A Guseva, James P Bagrow

What we write about when we write about causality: Features of causal statements across large-scale social discourse

We find that causal statements have a number of significant lexical and grammatical differences compared to non-causal language

August 2016 · Thomas C McAndrew, Joshua C Bongard, Christopher M Danforth, Peter Sheridan Dodds, Paul DH Hines, James P Bagrow

Robustness of spatial micronetworks

Accounting for spatial effects in both construction and robustness is important for designing efficient microgrids and other network infrastructure.

April 2015 · Thomas C McAndrew, Christopher M Danforth, James P Bagrow

A phase II study of the PARP inhibitor ABT-888 plus temozolomide in patients with heavily pretreated, metastatic colorectal cancer.

January 2011 · tom mcandrew

Cardio papers

January 2019 · tom mcandrew

Cyber physical systems

January 2016 · tom mcandrew

Obstetrics, Gynecology, Maternal and Child health papers

January 2015 · tom mcandrew