Jennifer Hill
#27,666
Most Influential Person Now
American statistician
Jennifer Hill's AcademicInfluence.com Rankings
Jennifer Hillmathematics Degrees
Mathematics
#2870
World Rank
#4344
Historical Rank
Statistics
#128
World Rank
#169
Historical Rank
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Mathematics
Jennifer Hill's Degrees
- PhD Statistics Stanford University
- Masters Statistics Stanford University
Why Is Jennifer Hill Influential?
(Suggest an Edit or Addition)According to Wikipedia, Jennifer Lynn Hill is an American statistician specializing in causal inference with applications to social statistics. She is a professor of applied statistics at New York University in the Steinhardt School of Culture, Education, and Human Development.
Jennifer Hill's Published Works
Number of citations in a given year to any of this author's works
Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author
Published Works
- Why We (Usually) Don't Have to Worry About Multiple Comparisons (2009) (1034)
- Bayesian Nonparametric Modeling for Causal Inference (2011) (940)
- Multiple Imputation with Diagnostics (mi) in R: Opening Windows into the Black Box (2011) (610)
- Principal Stratification Approach to Broken Randomized Experiments (2003) (239)
- Automated versus Do-It-Yourself Methods for Causal Inference: Lessons Learned from a Data Analysis Competition (2017) (185)
- Interval estimation for treatment effects using propensity score matching (2006) (148)
- Regression and Other Stories (2020) (146)
- Discussion of research using propensity‐score matching: Comments on ‘A critical appraisal of propensity‐score matching in the medical literature between 1996 and 2003’ by Peter Austin, Statistics in Medicine (2008) (141)
- Latino workers in the contemporary South (2001) (102)
- ON THE STATIONARY DISTRIBUTION OF ITERATIVE IMPUTATIONS (2010) (99)
- Endangered childhoods: how consumerism is impacting child and youth identity (2011) (86)
- Reducing Bias in Treatment Effect Estimation in Observational Studies Suffering from Missing Data (2004) (85)
- Assessing lack of common support in causal inference using bayesian nonparametrics: Implications for evaluating the effect of breastfeeding on children's cognitive outcomes (2013) (76)
- Bayesian Additive Regression Trees: A Review and Look Forward (2020) (75)
- Multiple Imputation for Continuous and Categorical Data: Comparing Joint Multivariate Normal and Conditional Approaches (2014) (73)
- A flexible, interpretable framework for assessing sensitivity to unmeasured confounding (2016) (71)
- Assessing Sensitivity to Unmeasured Confounding Using a Simulated Potential Confounder (2016) (70)
- Data Analysis Using Regression and Multilevel/Hierarchical Models: Missing-data imputation (2006) (64)
- An Extension and Test of Converse’s “Black-and-White” Model of Response Stability (2001) (56)
- Challenges With Propensity Score Strategies in a High-Dimensional Setting and a Potential Alternative (2011) (54)
- A Broader Template for Analyzing Broken Randomized Experiments (1998) (54)
- Bias Amplification and Bias Unmasking (2016) (48)
- Classification by Opinion-Changing Behavior: A Mixture Model Approach (2001) (44)
- Applied regression and multilevel/hierarchical models (2006) (32)
- Data Analysis Using Regression and Multilevel/Hierarchical Models: Multilevel structures (2006) (28)
- School Choice in NY City: A Bayesian Analysis of an Imperfect Randomized Experiment (2001) (27)
- Marriage: Cause or Mere Indicator of Future Earnings Growth? (2009) (26)
- Data Analysis Using Regression and Multilevel/Hierarchical Models: Multilevel linear models: the basics (2006) (24)
- Comment: The Essential Role of Pair Matching (2009) (15)
- Data Analysis Using Regression and Multilevel/Hierarchical Models: Sample size and power calculations (2006) (11)
- Matched Sampling for Causal Effects: The Design of the New York School Choice Scholarships Program Evaluation (2006) (10)
- Multilevel models and causal inference (2013) (10)
- Data Analysis Using Regression and Multilevel/Hierarchical Models: Single-level regression (2006) (10)
- Data Analysis Using Regression and Multilevel/Hierarchical Models: Causal inference using regression on the treatment variable (2006) (8)
- Data Analysis Using Regression and Multilevel/Hierarchical Models: Logistic regression (2006) (7)
- The Ambiguous Effects of Undergraduate Debt: Extending the Human Capital Model of Graduate School Enrollment (2008) (6)
- Data Analysis Using Regression and Multilevel/Hierarchical Models: Simulation for checking statistical procedures and model fits (2006) (6)
- Causal Inference: Overview (2015) (6)
- A Causal Framework for Observational Studies of Discrimination (2020) (6)
- Data Analysis Using Regression and Multilevel/Hierarchical Models: Multilevel modeling in Bugs and R: the basics (2006) (5)
- Data Analysis Using Regression and Multilevel/Hierarchical Models: Linear regression: before and after fitting the model (2006) (5)
- Data Analysis Using Regression and Multilevel/Hierarchical Models: Analysis of variance (2006) (4)
- Synchronicity and grief: The phenomenology of meaningful coincidence as it arises during bereavement (2011) (4)
- Data Analysis Using Regression and Multilevel/Hierarchical Models: Multilevel linear models: varying slopes, non-nested models, and other complexities (2006) (4)
- Causal inference using more advanced models (2006) (4)
- Principal Strati cation Approach to Broken Randomized Experiments: A Case Study of School Choice Vouchers in New York City (2003) (3)
- Data Analysis Using Regression and Multilevel/Hierarchical Models: Simulation of probability models and statistical inferences (2006) (3)
- Data Analysis Using Regression and Multilevel/Hierarchical Models: Multilevel generalized linear models (2006) (3)
- Data Analysis Using Regression and Multilevel/Hierarchical Models: Fitting multilevel models (2006) (3)
- Data Analysis Using Regression and Multilevel/Hierarchical Models: Model checking and comparison (2006) (3)
- Data Analysis Using Regression and Multilevel/Hierarchical Models: Six quick tips to improve your regression modeling (2006) (3)
- The Goossens: A Musical Century Carole Rosen [Book Review] (1995) (2)
- Data Analysis Using Regression and Multilevel/Hierarchical Models: Likelihood and Bayesian inference and computation (2006) (2)
- Data Analysis Using Regression and Multilevel/Hierarchical Models: Generalized linear models (2006) (2)
- Data Analysis Using Regression and Multilevel/Hierarchical Models: Causal inference using multilevel models (2006) (2)
- Accommodating Missing Data in Mixture Models for Classification by Opinion-Changing Behavior (2001) (2)
- Additional topics in causal inference (2020) (2)
- Deconstructing Claims of Post-Treatment Bias in Observational Studies of Discrimination (2020) (2)
- Potential for Bias Inflation with Grouped Data: A Comparison of Estimators and a Sensitivity Analysis Strategy. (2018) (2)
- Crossing a Divide? Maud Fritz-Stubbs as Amateur then Professional Musician in Late Nineteenth Century Sydney (2000) (2)
- Seeing like students: what Nairobi youth think about politics, the state and the future (2020) (2)
- DRAFT Bayesian Nonparametric Modeling for Causal Inference (2007) (1)
- DECONSTRUCTING THE CHILDREN'S CULTURE INDUSTRY: A RETROSPECTIVE ANALYSIS FROM YOUNG PEOPLE (2013) (1)
- Data Analysis Using Regression and Multilevel/Hierarchical Models: Fitting multilevel linear and generalized linear models in Bugs and R (2006) (1)
- Rejoinder: Response to Discussions and a Look Ahead (2019) (1)
- Stan and BART for Causal Inference: Estimating Heterogeneous Treatment Effects Using the Power of Stan and the Flexibility of Machine Learning (2022) (1)
- Data Analysis Using Regression and Multilevel/Hierarchical Models: Understanding and summarizing the fitted models (2006) (1)
- Data Analysis Using Regression and Multilevel/Hierarchical Models: Statistical graphics for research and presentation (2006) (1)
- Causal Inference using Bayesian Additive Regression Trees [R package bartCause version 1.0-4] (2020) (1)
- The Myths of Synthetic Control: Recommendations for Practice (2022) (0)
- Bayesian Exploration into Competing Models for Opinion-Changing Behavior (2001) (0)
- List of Examples (2006) (0)
- From data collection to model understanding to model checking (2006) (0)
- Data Analysis Using Regression and Multilevel/Hierarchical Models: Linear regression: the basics (2006) (0)
- Discussion of Paul Rosenbaum's “Covariance Adjustment in Randomized Experiments and Observational Studies" (2002) (0)
- Hanging out in the concrete jungle: Exploring the culture of youth homelessness in Melbourne (2014) (0)
- ‘A Source of Enjoyment': The Social Dimension of the Melbourne Liedertafels in the Late Nineteenth Century (2005) (0)
- Nihilism and Dystopian Morality in the Marquis de Sade’s Justine (2015) (0)
- From drawing room to diva: the Australian popular song 'I Was Dreaming' by Augustus W. Juncker (1999) (0)
- The Critical Editing of Music: History, Method and Practice [Book Review] (1997) (0)
- ‘Deeply helpful training’: Percy Grainger’s First Piano Teachers in Late Nineteenth-century Melbourne (2015) (0)
- The Spiritual Anatomy of Emotion: How Feelings Link the Brain, the Body, and the Sixth Sense (2012) (0)
- Data Analysis Using Regression and Multilevel/Hierarchical Models: Debugging and speeding convergence (2006) (0)
- “Lessons we are still learning”, a commentary on Cochran’s 1972 paper “Observational Studies" (2015) (0)
- Data Analysis Using Regression and Multilevel/Hierarchical Models: Concepts and methods from basic probability and statistics (2006) (0)
- Press 978-1107-02398-7 — Regression and Other Stories (0)
- Data Analysis Using Regression and Multilevel/Hierarchical Models: Working with regression inferences (2006) (0)
- Linear regression with a single predictor (2020) (0)
- Data Analysis Using Regression and Multilevel/Hierarchical Models: Multilevel logistic regression (2006) (0)
- Observational studies with all confounders assumed to be measured (2020) (0)
- Causal inference and randomized experiments (2020) (0)
- Award given by the Vernon Prize Committee for volume 28 of JPAM (2010) (0)
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What Schools Are Affiliated With Jennifer Hill?
Jennifer Hill is affiliated with the following schools:
