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Nicole E. Pashley
Nicole E. Pashley
Assistant Professor of Statistics, Rutgers University
Verified email at stat.rutgers.edu - Homepage
Title
Cited by
Cited by
Year
Insights on variance estimation for blocked and matched pairs designs
NE Pashley, LW Miratrix
Journal of Educational and Behavioral Statistics 46 (3), 271-296, 2021
432021
Design-based ratio estimators and central limit theorems for clustered, blocked RCTs
PZ Schochet, NE Pashley, LW Miratrix, T Kautz
Journal of the American Statistical Association 117 (540), 2135-2146, 2022
192022
Block what you can, except when you shouldn’t
NE Pashley, LW Miratrix
Journal of Educational and Behavioral Statistics 47 (1), 69-100, 2022
112022
Estimating heterogeneous causal effects of high-dimensional treatments: Application to conjoint analysis
M Goplerud, K Imai, NE Pashley
arXiv preprint arXiv:2201.01357, 2022
102022
Causal inference for multiple treatments using fractional factorial designs
NE Pashley, MAC Bind
Canadian Journal of Statistics 51 (2), 444-468, 2023
92023
Note on the delta method for finite population inference with applications to causal inference
NE Pashley
Statistics & Probability Letters 188, 109540, 2022
72022
Noncompliance and Instrumental Variables for 2K Factorial Experiments
M Blackwell, NE Pashley
Journal of the American Statistical Association 118 (542), 1102-1114, 2023
62023
Conditional as-if analyses in randomized experiments
NE Pashley, GW Basse, LW Miratrix
Journal of Causal Inference 9 (1), 264-284, 2021
62021
Batch adaptive designs to improve efficiency in social science experiments
M Blackwell, NE Pashley, D Valentino
Working paper, Harvard University, 2022. URL https://www. mattblackwell. org …, 2022
52022
Comparative efficacy of superheated dry steam application and insecticide spray against common bed bugs under simulated field conditions
RS Ramos, R Cooper, T Dasgupta, NE Pashley, C Wang
Journal of economic entomology 116 (1), 12-18, 2023
42023
Design-Based Ratio Estimators and Central Limit Theorems for Clustered, Blocked RCTs May 2020
PZ Schochet, NE Pashley, LW Miratrix, T Kautz
arXiv preprint arXiv:2002.01146, 2020
12020
Optimal allocation of sample size for randomization-based inference from 2K factorial designs
A Ravichandran, NE Pashley, B Libgober, T Dasgupta
Journal of Causal Inference 12 (1), 20230046, 2024
2024
Improving instrumental variable estimators with post-stratification
NE Pashley, L Keele, LW Miratrix
arXiv preprint arXiv:2303.10016, 2023
2023
Package ‘factiv’
M Blackwell, N Pashley, MM Blackwell
2022
Causal inference from treatment-control studies having an additional factor with unknown assignment mechanism
NE Pashley, KB Hunter, K McKeough, DB Rubin, T Dasgupta
arXiv preprint arXiv:2202.03533, 2022
2022
Supplemental Materials for “Noncompliance and instrumental variables for 2 factorial experiments”
M Blackwell, NE Pashley
2021
Estimating Heterogeneous Causal Effects of High-Dimensional Treatments Using Interpretable Machine Learning: Application to Conjoint Analysis
M Goplerud, K Imai, NE Pashley
2021
Conditional as-if analyses in randomized experiments
LW Miratrix, GW Basse, NE Pashley
2021
Advancing Design and Inference in a Causal Framework
NE Pashley
Harvard University, 2020
2020
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