8 citations · 22 across the 7 of their papers we have counts for
7 papers
Estimating population average treatment effects from experiments with noncompliance
Kellie Ottoboni, Jason Poulos
Randomized control trials (RCTs) are the gold standard for estimating causal effects, but often use samples that are non-representative of the actual population of interest. We pro…
Bernoulli Ballot Polling: A Manifest Improvement for Risk-Limiting Audits
Kellie Ottoboni, Matthew Bernhard, J. Alex Halderman +2
We present a method and software for ballot-polling risk-limiting audits (RLAs) based on Bernoulli sampling: ballots are included in the sample with probability , independently.…
Random Sampling: Practice Makes Imperfect
Philip B. Stark, Kellie Ottoboni
The pseudo-random number generators (PRNGs), sampling algorithms, and algorithms for generating random integers in some common statistical packages and programming languages are un…
Risk-Limiting Audits by Stratified Union-Intersection Tests of Elections (SUITE)
Kellie Ottoboni, Philip B. Stark, Mark Lindeman +1
Risk-limiting audits (RLAs) offer a statistical guarantee: if a full manual tally of the paper ballots would show that the reported election outcome is wrong, an RLA has a known mi…
Random problems with R
Kellie Ottoboni, Philip B. Stark
R (Version 3.5.1 patched) has an issue with its random sampling functionality. R generates random integers between and by multiplying random floats by , taking the floor…
Next Steps for the Colorado Risk-Limiting Audit (CORLA) Program
Mark Lindeman, Neal McBurnett, Kellie Ottoboni +1
Colorado conducted risk-limiting tabulation audits (RLAs) across the state in 2017, including both ballot-level comparison audits and ballot-polling audits. Those audits only cover…
An Empirical Comparison of Parametric and Permutation Tests for Regression Analysis of Randomized Experiments
Kellie Ottoboni, Fraser Lewis, Luigi Salmaso
Hypothesis tests based on linear models are widely accepted by organizations that regulate clinical trials. These tests are derived using strong assumptions about the data-generati…