Maximum likelihood, profile likelihood, and penalized likelihood: a primer.
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Summary
A primer on maximum likelihood and some important extensions which have proven useful in epidemiologic research, and which reveal connections betweenmaximum likelihood and Bayesian methods.
- Type
- article
- Published
- 2014-01-15
- Cited by
- 208
- References
- 58
- Access
- Open access
- OpenAlex
- https://openalex.org/W24173548
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:3508776
Keywords
Pneumoperitoneum, Medicine, Surgery, Randomized controlled trial, Clinical endpoint
References
- Bayesian Data Analysis (2nd ed.) (Book)
- Semiparametric Theory and Missing Data
- Targeted Learning: Causal Inference for Observational and Experimental Data
- Profile Likelihood for Estimation and Confidence Intervals
- Multilevel Modeling in Epidemiology with GLIMMIX
- High-dimensional propensity score adjustment in studies of treatment effects using health care claims data
- Quasi-likelihood functions, generalized linear models, and the Gauss-Newton method
- Toward a curse of dimensionality appropriate (CODA) asymptotic theory for semi-parametric models.
- Methods for epidemiologic analyses of multiple exposures: a review and comparative study of maximum-likelihood, preliminary-testing, and empirical-Bayes regression.
- Score and Pseudo-Score Confidence Intervals for Categorical Data Analysis
- Stein's Paradox in Statistics
- Propensity score estimation: machine learning and classification methods as alternatives to logistic regression
- Problems due to small samples and sparse data in conditional logistic regression analysis.
- Model selection and multimodel inference : a practical information-theoretic approach
- A Hospital‐Based Case‐Control Study of Stillbirths and Environmental Exposure to Arsenic Using an Atmospheric Dispersion Model Linked to a Geographical Information System
- Clinical Prediction Models—a Practical Approach to Development, Validation and Updating
- Orthogonality of estimating functions and nuisance parameters
- Propensity score estimation with boosted regression for evaluating causal effects in observational studies.
- Generalized Conjugate Priors for Bayesian Analysis of Risk and Survival Regressions
- Generalized Linear Models
Cited by
- Methods to Explore Uncertainty and Bias Introduced by Job Exposure Matrices
- A Bayesian Approach to Estimating Causal Vaccine Effects on Binary Post-infection Outcomes
- Secondhand tobacco smoke exposure and lung adenocarcinoma in situ/minimally invasive adenocarcinoma (AIS/MIA)
- Phthalates, perfluoroalkyl acids, metals and organochlorines and reproductive function: a multipollutant assessment in Greenlandic, Polish and Ukrainian men
- On the existence of maximum likelihood estimates for presence‐only data
- Influenza vaccine effectiveness: potential of the test-negative design. A systematic review
- Penalization, bias reduction, and default priors in logistic and related categorical and survival regressions
- Approximate Bayesian Logistic Regression via Penalized Likelihood by Data Augmentation
- Reconstruction of the Higgs mass in events with Higgs bosons decaying into a pair of τ leptons using matrix element techniques
- Even More Direct Calculation of the Variance of a Maximum Penalized-Likelihood Estimator
- Semiparametric Adjusted Exposure-Response Curves
- Inferring the Frequency Spectrum of Derived Variants to Quantify Adaptive Molecular Evolution in Protein-Coding Genes of Drosophila melanogaster
- A review and comparison of Bayesian and likelihood-based inferences in beta regression and zero-or-one-inflated beta regression
- Predicted risk of harm versus treatment benefit in large randomised controlled trials
- Hormonal Contraception Use is Common Among Patients with Inflammatory Bowel Diseases and Elevated Risk for Deep Vein Thrombosis
- Mediation Analysis for Health Disparities Research.
- The case-crossover design via penalized regression
- Essays on Delegated Search and Temporary Work Agencies
- Estimation of Severe Middle East Respiratory Syndrome Cases in the Middle East, 2012–2016
- Errors in causal inference: an organizational schema for systematic error and random error.
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