The following pages link to Super Learner (Q5443060):
Displaying 50 items.
- Population intervention causal effects based on stochastic interventions (Q115158) (← links)
- Subsemble: an ensemble method for combining subset-specific algorithm fits (Q116028) (← links)
- Sparse classification with paired covariates (Q127641) (← links)
- COBRA: a combined regression strategy (Q268720) (← links)
- Discussion of ``Identification, estimation and approximation of risk under interventions that depend on the natural value of treatment using observational data'', by Jessica Young, Miguel Hernán, and James Robins (Q306795) (← links)
- An asymptotically optimal kernel combined classifier (Q334008) (← links)
- A fusion of least squares and empirical likelihood for regression models with a missing binary covariate (Q341405) (← links)
- Finding quantitative trait loci genes with collaborative targeted maximum likelihood learning (Q544627) (← links)
- Classification in postural style (Q714355) (← links)
- Estimator selection and combination in scalar-on-function regression (Q1615246) (← links)
- The finite sample performance of semi- and non-parametric estimators for treatment effects and policy evaluation (Q1658377) (← links)
- Estimation of a non-parametric variable importance measure of a continuous exposure (Q1950850) (← links)
- Estimating effects with rare outcomes and high dimensional covariates: knowledge is power (Q2001880) (← links)
- Evaluating the impact of a HIV low-risk express care task-shifting program: a case study of the targeted learning roadmap (Q2001893) (← links)
- Predicting overall vaccine efficacy in a new setting by re-calibrating baseline covariate and intermediate response endpoint effect modifiers of type-specific vaccine efficacy (Q2001894) (← links)
- Continuous-time targeted minimum loss-based estimation of intervention-specific mean outcomes (Q2105179) (← links)
- Robust machine learning for treatment effects in multilevel observational studies under cluster-level unmeasured confounding (Q2141660) (← links)
- Estimation of the marginal effect of antidepressants on body mass index under confounding and endogenous covariate-driven monitoring times (Q2170439) (← links)
- A causal exposure response function with local adjustment for confounding: estimating health effects of exposure to low levels of ambient fine particulate matter (Q2194470) (← links)
- A unified study of nonparametric inference for monotone functions (Q2196204) (← links)
- When and when not to use optimal model averaging (Q2208423) (← links)
- Comment: Outcome-wide individualized treatment strategies (Q2218079) (← links)
- Rejoinder: A nonparametric superefficient estimator of the average treatment effect (Q2218089) (← links)
- A multi-loss super regression learner (MSRL) with application to survival prediction using proteomics (Q2259821) (← links)
- Improved precision in the analysis of randomized trials with survival outcomes, without assuming proportional hazards (Q2274689) (← links)
- Robust and flexible estimation of stochastic mediation effects: a proposed method and example in a randomized trial setting (Q2324996) (← links)
- Comment on ``Automated versus do-it-yourself methods for causal inference: lessons learned from a data analysis competition'' (Q2325614) (← links)
- Improving multilabel classification via heterogeneous ensemble methods (Q2326859) (← links)
- Efficient estimation of quantiles in missing data models (Q2409634) (← links)
- Flexible HAR model for realized volatility (Q2697034) (← links)
- A broad symmetry criterion for nonparametric validity of parametrically based tests in randomized trials (Q2893986) (← links)
- Global sensitivity analysis for repeated measures studies with informative drop-out: A semi-parametric approach (Q3119826) (← links)
- An Omnibus Non-Parametric Test of Equality in Distribution for Unknown Functions (Q3120101) (← links)
- Tuning parameters in random forests (Q4606433) (← links)
- Impact of subsampling and tree depth on random forests (Q4615432) (← links)
- Confidence sets with expected sizes for Multiclass Classification (Q4637018) (← links)
- Comment (Q4916483) (← links)
- An Application of Targeted Maximum Likelihood Estimation to the Meta‐Analysis of Safety Data (Q4919598) (← links)
- Propensity score prediction for electronic healthcare databases using super learner and high-dimensional propensity score methods (Q5034151) (← links)
- The relative performance of ensemble methods with deep convolutional neural networks for image classification (Q5036355) (← links)
- (Q5053280) (← links)
- Comparing different propensity score estimation methods for estimating the marginal causal effect through standardization to propensity scores (Q5084764) (← links)
- Confounding adjustment methods for multi-level treatment comparisons under lack of positivity and unknown model specification (Q5093035) (← links)
- Comparing and Weighting Imperfect Models Using D-Probabilities (Q5120673) (← links)
- Aggregating classifiers via Rademacher–Walsh polynomials (Q5220783) (← links)
- Discussion of PENCOMP (Q5229884) (← links)
- Nonparametric Causal Effects Based on Incremental Propensity Score Interventions (Q5231493) (← links)
- Estimation of the optimal regime in treatment of prostate cancer recurrence from observational data using flexible weighting models (Q5283324) (← links)
- Super Learning: An Application to the Prediction of HIV-1 Drug Resistance (Q5443030) (← links)
- Stochastic Tree Search for Estimating Optimal Dynamic Treatment Regimes (Q5857116) (← links)
