AIMC Topic: Propensity Score

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Using classification tree analysis to generate propensity score weights.

Journal of evaluation in clinical practice Mar 28, 2017
RATIONALE, AIMS AND OBJECTIVES: In evaluating non-randomized interventions, propensity scores (PS) estimate the probability of assignment to the treatment group given observed characteristics. Machine learning algorithms have been proposed as an alte...
Observational Studies as Topic Models, Statistical Data Interpretation, Statistical Propensity Score Humans Monte Carlo Method Machine Learning Computer Simulation Logistic Models
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A doubly robust approach for cost-effectiveness estimation from observational data.

Statistical methods in medical research Feb 27, 2017
Estimation of common cost-effectiveness measures, including the incremental cost-effectiveness ratio and the net monetary benefit, is complicated by the need to account for informative censoring and inherent skewness of the data. In addition, since t...
Lung Neoplasms Observation Machine Learning Cost-Benefit Analysis Algorithms Diagnostic Tests, Routine Databases, Factual Radiography, Thoracic Tomography, X-Ray Computed Propensity Score
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Impact of chromogranin A, differentiation, and mitoses in nonfunctional pancreatic neuroendocrine tumors ≤ 2 cm.

The Journal of surgical research Dec 29, 2016
BACKGROUND: Small pancreatic neuroendocrine tumors (PNETs) are a unique subset of pancreatic neoplasms. Chromogranin A (CgA) levels, mitotic rate, and histologic differentiation are often used to characterize PNET behavior. This study evaluates the i...
Adolescent Logistic Models Humans Retrospective Studies Adult Survival Analysis Mitosis Pancreatic Neoplasms Databases, Factual Female Multivariate Analysis Biomarkers, Tumor Neuroendocrine Tumors Prognosis Cell Differentiation Aged Propensity Score Male Middle Aged Neoplasm Staging Aged, 80 and over Chromogranin A Young Adult
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The Balance Super Learner: A robust adaptation of the Super Learner to improve estimation of the average treatment effect in the treated based on propensity score matching.

Statistical methods in medical research Dec 15, 2016
Consistency of the propensity score estimators rely on correct specification of the propensity score model. The propensity score is frequently estimated using a main effect logistic regression. It has recently been shown that the use of ensemble mach...
Humans Machine Learning Algorithms Computer Simulation Logistic Models Propensity Score
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Targeted Maximum Likelihood Estimation for Causal Inference in Observational Studies.

American journal of epidemiology Dec 9, 2016
Estimation of causal effects using observational data continues to grow in popularity in the epidemiologic literature. While many applications of causal effect estimation use propensity score methods or G-computation, targeted maximum likelihood esti...
Propensity Score Likelihood Functions Confounding Factors, Epidemiologic Epidemiologic Research Design Humans Machine Learning Depression Computer Simulation Exercise Causality Observational Studies as Topic Data Interpretation, Statistical Bias
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Ileostomy creation in colorectal cancer surgery: risk of acute kidney injury and chronic kidney disease.

The Journal of surgical research Nov 29, 2016
BACKGROUND: Ileostomy creation is associated with postoperative dehydration and readmission; however, the effect on renal function is unknown. Our goal was to characterize the impact of ileostomy creation on acute and chronic renal function.
Logistic Models Renal Insufficiency, Chronic Treatment Outcome Follow-Up Studies Patient Readmission Proportional Hazards Models Propensity Score Ileostomy Adult Colorectal Neoplasms Male Middle Aged Postoperative Complications Female Risk Factors Aged Aged, 80 and over Humans Retrospective Studies Acute Kidney Injury
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Assessing Hospital Performance After Percutaneous Coronary Intervention Using Big Data.

Circulation. Cardiovascular quality and outcomes Nov 8, 2016
BACKGROUND: Although risk adjustment remains a cornerstone for comparing outcomes across hospitals, optimal strategies continue to evolve in the presence of many confounders. We compared conventional regression-based model to approaches particularly ...
Humans Process Assessment, Health Care Multivariate Analysis Machine Learning Hospitals Propensity Score Risk Factors Cause of Death Algorithms Likelihood Functions Aged Time Factors Registries Databases, Factual Massachusetts Aged, 80 and over Hospital Mortality Percutaneous Coronary Intervention Female Male Logistic Models Data Mining Middle Aged Treatment Outcome Quality Indicators, Health Care
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Combining machine learning and propensity score weighting to estimate causal effects in multivalued treatments.

Journal of evaluation in clinical practice Jul 15, 2016
RATIONALE, AIMS AND OBJECTIVES: Interventions with multivalued treatments are common in medical and health research; examples include comparing the efficacy of competing interventions and contrasting various doses of a drug. In recent years, there ha...
Humans Machine Learning Algorithms Female Causality Regression Analysis Propensity Score Observation Aged Empirical Research Male Middle Aged Treatment Outcome
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Combining machine learning and matching techniques to improve causal inference in program evaluation.

Journal of evaluation in clinical practice Jun 29, 2016
RATIONALE, AIMS AND OBJECTIVES: Program evaluations often utilize various matching approaches to emulate the randomization process for group assignment in experimental studies. Typically, the matching strategy is implemented, and then covariate balan...
Female Adult Male Middle Aged Causality Humans Machine Learning Algorithms Program Evaluation Chronic Disease Discriminant Analysis Random Allocation Propensity Score
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Using machine learning to assess covariate balance in matching studies.

Journal of evaluation in clinical practice Mar 23, 2016
In order to assess the effectiveness of matching approaches in observational studies, investigators typically present summary statistics for each observed pre-intervention covariate, with the objective of showing that matching reduces the difference ...
Propensity Score Retrospective Studies Female Adult Male Middle Aged Pilot Projects Humans Observational Studies as Topic Machine Learning Patient-Centered Care Algorithms Discriminant Analysis Research Design
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