Pages that link to "Item:Q4559704"
From MaRDI portal
The following pages link to Estimation and Inference of Heterogeneous Treatment Effects using Random Forests (Q4559704):
Displaying 50 items.
- Inference on heterogeneous treatment effects in high‐dimensional dynamic panels under weak dependence (Q6067223) (← links)
- Discussion of the Paper “Prediction, Estimation, and Attribution” by B. Efron (Q6068036) (← links)
- Causal interaction trees: Finding subgroups with heterogeneous treatment effects in observational data (Q6079481) (← links)
- Global sensitivity analysis of randomized trials with nonmonotone missing binary outcomes: Application to studies of substance use disorders (Q6079486) (← links)
- Pool adjacent violators algorithm–assisted learning with application on estimating optimal individualized treatment regimes (Q6079628) (← links)
- Testing for Heterogeneity in the Utility of a Surrogate Marker (Q6079768) (← links)
- HETEROGENEOUS TREATMENT EFFECTS OF NUDGE AND REBATE: CAUSAL MACHINE LEARNING IN A FIELD EXPERIMENT ON ELECTRICITY CONSERVATION (Q6088651) (← links)
- Stable Discovery of Interpretable Subgroups via Calibration in Causal Studies (Q6089483) (← links)
- Efficient screening of predictive biomarkers for individual treatment selection (Q6094206) (← links)
- Consistent and unbiased variable selection under indepedent features using random forest permutation importance (Q6103229) (← links)
- Is there a role for statistics in artificial intelligence? (Q6103792) (← links)
- Random Forests for Spatially Dependent Data (Q6107238) (← links)
- What's trending in difference-in-differences? A synthesis of the recent econometrics literature (Q6108351) (← links)
- A multiagent reinforcement learning framework for off-policy evaluation in two-sided markets (Q6138596) (← links)
- A reluctant additive model framework for interpretable nonlinear individualized treatment rules (Q6138648) (← links)
- Designing experiments toward shrinkage estimation (Q6144430) (← links)
- Gradient boosting for extreme quantile regression (Q6144813) (← links)
- Federated causal inference in heterogeneous observational data (Q6149278) (← links)
- Estimation and inference for policy relevant treatment effects (Q6163243) (← links)
- Forward-selected panel data approach for program evaluation (Q6163247) (← links)
- Estimating heterogeneous treatment effects versus building individualized treatment rules: connection and disconnection (Q6170514) (← links)
- Neighborhood-based cross fitting approach to treatment effects with high-dimensional data (Q6170545) (← links)
- Analysing a built-in advantage in asymmetric darts contests using causal machine learning (Q6170912) (← links)
- Treatment effects estimation with missing not at random data without outcome modeling (Q6172250) (← links)
- Dimension-agnostic inference using cross U-statistics (Q6178581) (← links)
- The Effect of Job Loss and Unemployment Insurance on Crime in Brazil (Q6181684) (← links)
- Subgroup analysis using Bernoulli‐gated hierarchical mixtures of experts models (Q6189827) (← links)
- Designing optimal, data-driven policies from multisite randomized trials (Q6198860) (← links)
- Using Wasserstein generative adversarial networks for the design of Monte Carlo simulations (Q6199647) (← links)
- Instrumental variable estimation with first-stage heterogeneity (Q6199657) (← links)
- Exploring uplift modeling with high class imbalance (Q6487755) (← links)
- Asymptotics of K-fold cross validation (Q6535409) (← links)
- Causality in econometrics: choice vs chance (Q6536492) (← links)
- A new paradigm for high-dimensional data: distance-based semiparametric feature aggregation framework via between-subject attributes (Q6536927) (← links)
- Parametric identification of the joint distribution of the potential outcomes (Q6541539) (← links)
- Forecasting hurricane-related power outages via locally optimized random forests (Q6541753) (← links)
- Causal effect random forest of interaction trees for learning individualized treatment regimes with multiple treatments in observational studies (Q6543882) (← links)
- On variance estimation of random forests with Infinite-order U-statistics (Q6546441) (← links)
- Improving uplift model evaluation on randomized controlled trial data (Q6555155) (← links)
- Generalizing treatment effects with incomplete covariates: identifying assumptions and multiple imputation algorithms (Q6563657) (← links)
- Heterogeneous treatment effect-based random forest: HTERF (Q6573307) (← links)
- Combining observational and experimental datasets using shrinkage estimators (Q6589235) (← links)
- Improved inference for doubly robust estimators of heterogeneous treatment effects (Q6589258) (← links)
- Reflections on the concept of optimality of single decision point treatment regimes (Q6595094) (← links)
- Some children left behind: variation in the effects of an educational intervention (Q6600018) (← links)
- Subgroup analysis and adaptive experiments crave for debiasing (Q6602034) (← links)
- Learning optimal biomarker-guided treatment policy for chronic disorders (Q6615930) (← links)
- A pilot design for observational studies: using abundant data thoughtfully (Q6617428) (← links)
- Ranking of average treatment effects with generalized random forests for time-to-event outcomes (Q6617512) (← links)
- Forecasting Inflation in a Data-Rich Environment: The Benefits of Machine Learning Methods (Q6617739) (← links)
