Miguel Angel Luque-Fernandez

Complete online book with 9 chapters, 71 references, R and Stata code. From potential outcomes to TMLE.

Step-by-step TMLE implementation. Covers influence functions, fluctuation steps, and variance estimation with worked examples.

Doubly robust methods, AIPW, and TMLE in Stata using the eltmle command with real-data examples.

Derivación matemática de TMLE: funciones de influencia, teoría semiparamétrica, y estimadores doblemente robustos.

Variance estimation using the delta method for epidemiological estimands. R notebook with derivations and worked examples.

Stata simulation comparing eltmle vs competitors under dual misspecification.

Open-source Stata module for TMLE estimation of the average treatment effect with SuperLearner integration.

Kaplan-Meier estimator, log-rank tests, and Cox proportional hazards models. ULB workshop tutorial.

Standardization of net survival in a cohort analysis. For Stata users working with population-based cancer data.

Modeling net survival using STRS and Poisson regression in a cohort analysis under the relative survival framework.

Royston-Parmar flexible parametric survival models for net survival estimation. Extended tutorial with Stata code.

K-fold cross-validation, LOOCV, and bootstrap resampling for model selection and evaluation. Interactive R notebook.

Stata module to compute cross-validated area under the ROC curve with bootstrap confidence intervals.

Step-by-step guide to installing and using Claude Code for statistical programming and data analysis in Windows. Covers R, Stata, Python, and Quarto workflows.

Calculate expected delivery date with gestational age uncertainty intervals.

Visualize comorbidity patterns among cancer patients using interactive network analysis.

Explore parametric survival distributions (Weibull, log-normal, Gompertz) and their hazard functions interactively.

Interactive demonstration of collider bias and selection bias effects in causal inference and epidemiology.

Interactive simulation tool for teaching the Central Limit Theorem. Draw samples from four distributions (Normal, Uniform, Exponential, Bimodal) and visualize how the sampling distribution converges to normality step by step.

Targeted Maximum Likelihood Estimation for Stata. Implements TMLE for the average treatment effect with SuperLearner ensemble learning.

Cross-validated area under the ROC curve for binary outcome predictors. Bootstrap confidence intervals and k-fold CV.

Tabulation of matched pairs in 1:1 matched case-control studies by exposure status. Simple, fast, and well-tested.

Classical biostatistics routines for health sciences — companion package to Matemática Estadística Médica con R. Covers probability, inference, regression, and epidemiological analysis.

Comprehensive Quarto book (9 chapters) covering potential outcomes, DAGs, G-formula, propensity scores, AIPW, TMLE, longitudinal data, mediation, and sensitivity analysis. With ~65 R and Stata examples.

Open-access textbook on mathematical statistics with applications in R and Quarto. Covers probability, inference, regression, and computational methods for medicine and health sciences. In Spanish.

Applied biostatistics methods for epidemiological studies. Covers survival analysis, longitudinal models, causal inference, and diagnostic test evaluation with R implementations.

Guía paso a paso para instalar y usar Claude Code en Windows, orientada a estadísticos y científicos de datos.