Publications
69 results
69 results
Working Paper
Sophie Litschwartz and Luke Miratrix. “Characterizing Cross-Site Variation in Local Average Treatment Effects in Multisite RDD Contexts With an Application to Massachusetts High School Exit Exam”
Sophie Litschwartz and Luke Miratrix. “Characterizing Cross-Site Variation in Local Average Treatment Effects in Multisite RDD Contexts With an Application to Massachusetts High School Exit Exam”
2024
Joshua Gilbert, Luke Miratrix, Mridul Joshi, and Benjamin Domingue. 2024. “Disentangling Person-Dependent and Item-Dependent Causal Effects: Applications of Item Response Theory to the Estimation of Treatment Effect Heterogeneity”. Journal of Educational and Behavioral Statistics
Joshua Gilbert, Luke Miratrix, Mridul Joshi, and Benjamin Domingue. 2024. “Disentangling Person-Dependent and Item-Dependent Causal Effects: Applications of Item Response Theory to the Estimation of Treatment Effect Heterogeneity”. Journal of Educational and Behavioral Statistics
Christina Weiland, Rebecca Unterman, Susan Dynarski, Rachel Abenavoli, Howard Bloom, Breno Braga, Anne-Marie Faria, Erica Greenberg, Brian Jacob, Jane Arnold Lincove, and others. 2024. “Lottery-Based Evaluations of Early Education Programs: Opportunities and Challenges for Building the Next Generation of Evidence”. AERA Open, 10
Christina Weiland, Rebecca Unterman, Susan Dynarski, Rachel Abenavoli, Howard Bloom, Breno Braga, Anne-Marie Faria, Erica Greenberg, Brian Jacob, Jane Arnold Lincove, and others. 2024. “Lottery-Based Evaluations of Early Education Programs: Opportunities and Challenges for Building the Next Generation of Evidence”. AERA Open, 10
Kristen Hunter, Luke Miratrix, and Kristin Porter. 2024. “PUMP: Estimating Power, Minimum Detectable Effect Size, and Sample Size When Adjusting for Multiple Outcomes in Multi-Level Experiments”. Journal of Statistical Software, 108, Pp. 1–43
Kristen Hunter, Luke Miratrix, and Kristin Porter. 2024. “PUMP: Estimating Power, Minimum Detectable Effect Size, and Sample Size When Adjusting for Multiple Outcomes in Multi-Level Experiments”. Journal of Statistical Software, 108, Pp. 1–43
2023
Johann Gagnon-Bartsch, Adam Sales, Edward Wu, Anthony Botelho, John Erickson, Luke Miratrix, and Neil Heffernan. 2023. “Precise Unbiased Estimation in Randomized Experiments Using Auxiliary Observational Data”. Journal of Causal Inference, 11, 1, Pp. 20220011
Johann Gagnon-Bartsch, Adam Sales, Edward Wu, Anthony Botelho, John Erickson, Luke Miratrix, and Neil Heffernan. 2023. “Precise Unbiased Estimation in Randomized Experiments Using Auxiliary Observational Data”. Journal of Causal Inference, 11, 1, Pp. 20220011
Luke Keele, Eli Ben-Michael, Avi Feller, Rachel Kelz, and Luke Miratrix. 2023. “Hospital Quality Risk Standardization via Approximate Balancing Weights”. The Annals of Applied Statistics, 17, 2, Pp. 901–928
Luke Keele, Eli Ben-Michael, Avi Feller, Rachel Kelz, and Luke Miratrix. 2023. “Hospital Quality Risk Standardization via Approximate Balancing Weights”. The Annals of Applied Statistics, 17, 2, Pp. 901–928
Devin Caughey, Allan Dafoe, Xinran Li, and Luke Miratrix. 2023. “Randomisation Inference Beyond the Sharp Null: Bounded Null Hypotheses and Quantiles of Individual Treatment Effects”. Journal of the Royal Statistical Society Series B: Statistical Methodology, 85, 5, Pp. 1471–1491
Devin Caughey, Allan Dafoe, Xinran Li, and Luke Miratrix. 2023. “Randomisation Inference Beyond the Sharp Null: Bounded Null Hypotheses and Quantiles of Individual Treatment Effects”. Journal of the Royal Statistical Society Series B: Statistical Methodology, 85, 5, Pp. 1471–1491
Evan TR Rosenman and Luke Miratrix. 2023. “Designing Experiments Toward Shrinkage Estimation”. Electronic Journal of Statistics, 17, 2, Pp. 3406–3442
Evan TR Rosenman and Luke Miratrix. 2023. “Designing Experiments Toward Shrinkage Estimation”. Electronic Journal of Statistics, 17, 2, Pp. 3406–3442
Benjamin Lu, Eli Ben-Michael, Avi Feller, and Luke Miratrix. 2023. “Is It Who You Are or Where You Are? Accounting for Compositional Differences in Cross-Site Treatment Effect Variation”. Journal of Educational and Behavioral Statistics, 48, 4, Pp. 420–453
Benjamin Lu, Eli Ben-Michael, Avi Feller, and Luke Miratrix. 2023. “Is It Who You Are or Where You Are? Accounting for Compositional Differences in Cross-Site Treatment Effect Variation”. Journal of Educational and Behavioral Statistics, 48, 4, Pp. 420–453
Joshua Gilbert, James Kim, and Luke Miratrix. 2023. “Modeling Item-Level Heterogeneous Treatment Effects With the Explanatory Item Response Model: Leveraging Large-Scale Online Assessments to Pinpoint the Impact of Educational Interventions”. Journal of Educational and Behavioral Statistics, 48, 6, Pp. 889–913
Joshua Gilbert, James Kim, and Luke Miratrix. 2023. “Modeling Item-Level Heterogeneous Treatment Effects With the Explanatory Item Response Model: Leveraging Large-Scale Online Assessments to Pinpoint the Impact of Educational Interventions”. Journal of Educational and Behavioral Statistics, 48, 6, Pp. 889–913
Lisa Hsin, Luke Miratrix, Ha Yeon Kim, Maria LaRusso, and Catherine Snow. 2023. “Predictable Variation in the Implementation of a Curricular Intervention–-and Why It Matters”. The Elementary School Journal, 124, 1, Pp. 1–30
Lisa Hsin, Luke Miratrix, Ha Yeon Kim, Maria LaRusso, and Catherine Snow. 2023. “Predictable Variation in the Implementation of a Curricular Intervention–-and Why It Matters”. The Elementary School Journal, 124, 1, Pp. 1–30
Melody Huang, Naoki Egami, Erin Hartman, and Luke Miratrix. 2023. “Leveraging Population Outcomes to Improve the Generalization of Experimental Results: Application to the JTPA Study”. The Annals of Applied Statistics, 17, 3, Pp. 2139–2164
Melody Huang, Naoki Egami, Erin Hartman, and Luke Miratrix. 2023. “Leveraging Population Outcomes to Improve the Generalization of Experimental Results: Application to the JTPA Study”. The Annals of Applied Statistics, 17, 3, Pp. 2139–2164