Design of observational studies
From MaRDI portal
Publication:5902290
DOI10.1007/978-1-4419-1213-8zbMath1308.62005OpenAlexW253646976MaRDI QIDQ5902290
Publication date: 27 November 2009
Published in: Springer Series in Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/978-1-4419-1213-8
Introductory exposition (textbooks, tutorial papers, etc.) pertaining to statistics (62-01) Applications of statistics (62Pxx) Design of statistical experiments (62Kxx)
Related Items (91)
Biased Encouragements and Heterogeneous Effects in an Instrumental Variable Study of Emergency General Surgical Outcomes ⋮ Extrapolating Treatment Effects in Multi-Cutoff Regression Discontinuity Designs ⋮ The Landscape of Causal Inference: Perspective From Citation Network Analysis ⋮ False discovery rate control for effect modification in observational studies ⋮ Generalized quantile treatment effect: a flexible Bayesian approach using quantile ratio smoothing ⋮ Optimal multilevel matching using network flows: an application to a summer reading intervention ⋮ Greedy outcome weighted tree learning of optimal personalized treatment rules ⋮ Using statistical methods to model the fine-tuning of molecular machines and systems ⋮ Subgroup causal effect identification and estimation via matching tree ⋮ Full matching approach to instrumental variables estimation with application to the effect of malaria on stunting ⋮ The Case-Control Approach Can be More Powerful for Matched Pair Observational Studies When the Outcome is Rare ⋮ Generalized Optimal Matching Methods for Causal Inference ⋮ How strong is strong enough? Strengthening instruments through matching and weak instrument tests ⋮ Comparing Covariate Prioritization via Matching to Machine Learning Methods for Causal Inference Using Five Empirical Applications ⋮ Evidence factors from multiple, possibly invalid, instrumental variables ⋮ Optimal Matching with Minimal Deviation from Fine Balance in a Study of Obesity and Surgical Outcomes ⋮ Building Representative Matched Samples With Multi-Valued Treatments in Large Observational Studies ⋮ Detecting heterogeneous treatment effects with instrumental variables and application to the Oregon Health Insurance Experiment ⋮ Sharpening the Rosenbaum Sensitivity Bounds to Address Concerns About Interactions Between Observed and Unobserved Covariates ⋮ Some models and methods for the analysis of observational data ⋮ Evaluating and improving a matched comparison of antidepressants and bone density ⋮ Bridging preference‐based instrumental variable studies and cluster‐randomized encouragement experiments: Study design, noncompliance, and average cluster effect ratio ⋮ How Well Can Fine Balance Work for Covariate Balancing ⋮ Instrumented Difference-in-Differences ⋮ Large Sample Properties of Matching for Balance ⋮ Testing Biased Randomization Assumptions and Quantifying Imperfect Matching and Residual Confounding in Matched Observational Studies ⋮ Can \(p\)-values be meaningfully interpreted without random sampling? ⋮ Is there a role for statistics in artificial intelligence? ⋮ The risk of maternal complications after Cesarean delivery: near-far matching for instrumental variables study designs with large observational datasets ⋮ Causal inference in data analysis with applications to fairness and explanations ⋮ Using predictability to improve matching of urban locations in Philadelphia ⋮ Designing experiments toward shrinkage estimation ⋮ A guide to regression discontinuity designs in medical applications ⋮ Social distancing and COVID-19: randomization inference for a structured dose-response relationship ⋮ Statistical matching and subclassification with a continuous dose: characterization, algorithm, and application to a health outcomes study ⋮ To Adjust or not to Adjust? Estimating the Average Treatment Effect in Randomized Experiments with Missing Covariates ⋮ Fundamentals of Causal Inference: With R Fundamentals of Causal Inference: With R , Babette A. Brumback, Boca Raton, FL: Chapman & Hall/CRC Press, 2022, xii + 236 pp., $74.95(H), ISBN 978-0-367-70505-3. ⋮ Construction of alternative hypotheses for randomization tests with ordinal outcomes ⋮ Regression analysis of unmeasured confounding ⋮ Rejective Sampling, Rerandomization, and Regression Adjustment in Survey Experiments ⋮ An exact adaptive test with superior design sensitivity in an observational study of treatments for ovarian cancer ⋮ Matching methods for causal inference: a review and a look forward ⋮ Sharp Sensitivity Analysis for Inverse Propensity Weighting via Quantile Balancing ⋮ Instrumental variable estimation with a stochastic monotonicity assumption ⋮ Stronger instruments via integer programming in an observational study of late preterm birth outcomes ⋮ Agnostic notes on regression adjustments to experimental data: reexamining Freedman's critique ⋮ Matching methods for observational studies derived from large administrative databases ⋮ Rank tests in unmatched clustered randomized trials applied to a study of teacher training ⋮ Split-door criterion: identification of causal effects through auxiliary outcomes ⋮ Matching for balance, pairing for heterogeneity in an observational study of the effectiveness of for-profit and not-for-profit high schools in Chile ⋮ When is a sensitivity parameter exactly that? ⋮ Covariate-adjusted Fisher randomization tests for the average treatment effect ⋮ Using Mixed Integer Programming for Matching in an Observational Study of Kidney Failure After Surgery ⋮ On the value of subscription models for online grocery retail ⋮ Case Definition and Design Sensitivity ⋮ Contrasting Evidence Within and Between Institutions That Provide Treatment in an Observational Study of Alternate Forms of Anesthesia ⋮ Effect Modification and Design Sensitivity in Observational Studies ⋮ Impact of Multiple Matched Controls on Design Sensitivity in Observational Studies ⋮ Predicting overall vaccine efficacy in a new setting by re-calibrating baseline covariate and intermediate response endpoint effect modifiers of type-specific vaccine efficacy ⋮ Matching on‐the‐fly: Sequential allocation with higher power and efficiency ⋮ Isolation in the construction of natural experiments ⋮ An alternative sensitivity approach for longitudinal analysis with dropout ⋮ Learning causal effect using machine learning with application to China's typhoon ⋮ The classification permutation test: a flexible approach to testing for covariate imbalance in observational studies ⋮ Using Approximation Algorithms to Build Evidence Factors and Related Designs for Observational Studies ⋮ Causal inference: a missing data perspective ⋮ Uncertainty intervals for regression parameters with non-ignorable missingness in the outcome ⋮ Wavelet-domain regression and predictive inference in psychiatric neuroimaging ⋮ Clustered Treatment Assignments and Sensitivity to Unmeasured Biases in Observational Studies ⋮ Weighted M-statistics With Superior Design Sensitivity in Matched Observational Studies With Multiple Controls ⋮ Using the potential outcome framework to estimate optimal sample size for cluster randomized trials: a simulation-based algorithm ⋮ DOS ⋮ On Sensitivity Value of Pair-Matched Observational Studies ⋮ A New u-Statistic with Superior Design Sensitivity in Matched Observational Studies ⋮ Extended sensitivity analysis for heterogeneous unmeasured confounding with an application to sibling studies of returns to education ⋮ Polymatching algorithm in observational studies with multiple treatment groups ⋮ An instrumental variables design for the effect of emergency general surgery ⋮ Causal inference for the effect of mobility on Covid-19 deaths ⋮ Testing for differential abundance in compositional counts data, with application to microbiome studies ⋮ Dimensions, power and factors in an observational study of behavioral problems after physical abuse of children ⋮ Optimal Tradeoffs in Matched Designs Comparing US-Trained and Internationally Trained Surgeons ⋮ Sensitivity analysis for unobserved confounding in causal mediation analysis allowing for effect modification, censoring and truncation ⋮ Discovering Heterogeneous Exposure Effects Using Randomization Inference in Air Pollution Studies ⋮ Do School Districts Affect NYC House Prices? Identifying Border Differences Using a Bayesian Nonparametric Approach to Geographic Regression Discontinuity Designs ⋮ Identification and Estimation of Treatment and Interference Effects in Observational Studies on Networks ⋮ Triplet Matching for Estimating Causal Effects With Three Treatment Arms: A Comparative Study of Mortality by Trauma Center Level ⋮ Bounds on the conditional and average treatment effect with unobserved confounding factors ⋮ Randomization Inference for Outcomes with Clumping at Zero ⋮ Rerandomization with diminishing covariate imbalance and diverging number of covariates ⋮ Instrumental variables: an econometrician's perspective ⋮ Using the Exterior Match to Compare Two Entwined Matched Control Groups
Uses Software
This page was built for publication: Design of observational studies