| Modeling and detecting change in temporal networks via the degree corrected stochastic block model JD Wilson, NT Stevens, WH Woodall Quality and Reliability Engineering International 35 (5), 1363-1378, 2019 | 102 | 2019 |
| Modeling and detecting change in temporal networks via the degree corrected stochastic block model JD Wilson, NT Stevens, WH Woodall Quality and Reliability Engineering International 35 (5), 1363-1378, 2019 | 102 | 2019 |
| Assessing agreement between two measurement systems: An alternative to the limits of agreement approach NT Stevens, SH Steiner, RJ MacKay Statistical methods in medical research 26 (6), 2487-2504, 2017 | 56 | 2017 |
| Statistical methods for network surveillance DR Jeske, NT Stevens, AG Tartakovsky, JD Wilson Applied Stochastic Models in Business and Industry 34 (4), 425-445, 2018 | 44 | 2018 |
| Using multiple agreement methods for continuous repeated measures data: a tutorial for practitioners RA Parker, C Scott, V Inácio, NT Stevens BMC Medical Research Methodology 20, 1-14, 2020 | 38 | 2020 |
| The effect of temporal aggregation level in social network monitoring MJ Zhao, AR Driscoll, S Sengupta, NT Stevens, RD Fricker Jr, ... PloS one 13 (12), e0209075, 2018 | 26 | 2018 |
| Comparing heteroscedastic measurement systems with the probability of agreement NT Stevens, SH Steiner, RJ MacKay Statistical Methods in Medical Research 27 (11), 3420-3435, 2018 | 22 | 2018 |
| Monitoring dynamic networks: A simulation‐based strategy for comparing monitoring methods and a comparative study L Yu, IM Zwetsloot, NT Stevens, JD Wilson, KL Tsui Quality and Reliability Engineering International 38 (3), 1226-1250, 2022 | 21 | 2022 |
| Design and analysis of confirmation experiments NT Stevens, CM Anderson-Cook Journal of Quality Technology 51 (2), 109-124, 2019 | 21 | 2019 |
| Comparing the reliability of related populations with the probability of agreement NT Stevens, CM Anderson-Cook Technometrics 59 (3), 371-380, 2017 | 21 | 2017 |
| Statistical challenges in online controlled experiments: A review of a/b testing methodology N Larsen, J Stallrich, S Sengupta, A Deng, R Kohavi, NT Stevens The American Statistician, 1-15, 2023 | 17 | 2023 |
| Quantifying similarity in reliability surfaces using the probability of agreement NT Stevens, CM Anderson-Cook Quality Engineering 29 (3), 395-408, 2017 | 17 | 2017 |
| Bayesian probability of agreement for comparing the similarity of response surfaces NT Stevens, SE Rigdon, CM Anderson-Cook Journal of Quality Technology 52 (1), 67-80, 2020 | 16 | 2020 |
| Augmented measurement system assessment NT Stevens, R Browne, SH Steiner, RJ MacKay Journal of Quality Technology 42 (4), 388-399, 2010 | 15 | 2010 |
| Comparing Kaplan‐Meier curves with the probability of agreement NT Stevens, L Lu Statistics in Medicine 39 (30), 4621-4635, 2020 | 14 | 2020 |
| Bayesian probability of predictive agreement for comparing the outcome of two separate regressions NT Stevens, SE Rigdon, CM Anderson‐Cook Quality and Reliability Engineering International 34 (6), 968-978, 2018 | 13 | 2018 |
| Estimating the effects of non-pharmaceutical interventions and population mobility on daily COVID-19 cases: evidence from Ontario NT Stevens, A Sen, F Kiwon, PP Morita, SH Steiner, Q Zhang Canadian Public Policy 48 (1), 144-161, 2022 | 12 | 2022 |
| Statistical network surveillance DR Jeske, NT Stevens, JD Wilson, AG Tartakovsky Wiley StatsRef: Statistics Reference Online, 1-12, 2014 | 12 | 2014 |
| Gauge R&R studies that incorporate baseline information NT Stevens, SH Steiner, RP Browne, RJ MacKay IIE Transactions 45 (11), 1166-1175, 2013 | 12 | 2013 |
| Hurdle blockmodels for sparse network modeling N Motalebi, NT Stevens, SH Steiner The American Statistician 75 (4), 383-393, 2021 | 9 | 2021 |
