choxos
- 46 skills
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- 7 hours ago last updated
- ▌ Meta Analysis 2 · choxosBayesian meta-analysis models including fixed effects, random effects, and network meta-analysis with Stan and JAGS implementations.
- ▌ Math Typography · choxosMathematical rendering with MathTex, Tex, tex_to_color_map, custom equation classes, and formula animation patterns.
- ▌ Component Design · choxosReusable component patterns including VGroup subclasses, helper methods, encapsulated visualizations, and always_redraw patterns.
- ▌ Camera Techniques · choxosCamera manipulation including zoom, pan, save/restore state, line width compensation, and focus transitions.
- ▌ Animation Patterns · choxosProduction animation patterns including reveal, transform, progressive reveal, emphasis, and cleanup patterns.
- ▌ Manim Fundamentals · choxosCore Manim concepts including Scene lifecycle, Mobject hierarchy, coordinate systems, animation lifecycle, and rate functions.
- ▌ Production Quality · choxos3Blue1Brown-style production standards including color palettes, timing guidelines, positioning rules, cleanup patterns, and typography standards.
- ▌ Nma Methodology · choxosDeep methodology knowledge for network meta-analysis including transitivity, consistency assessment, treatment rankings, and model selection. Use when conducting or reviewing NMA.
- ▌ Stc Methodology · choxosDeep methodology knowledge for STC including outcome regression, effect modifier selection, covariate centering, and comparison with MAIC. Use when conducting or reviewing STC analyses.
- ▌ Model Tuning · choxosHyperparameter tuning in tidymodels with grids, Bayesian optimization, racing, and workflow finalization.
- ▌ Maic Methodology · choxosDeep methodology knowledge for MAIC including assumptions, weight diagnostics, ESS interpretation, and anchored vs unanchored decisions. Use when conducting or reviewing MAIC analyses.
- ▌ Tidy Itc Workflow · choxosMaster tidy modelling patterns for ITC analyses following TMwR principles. Covers workflow structure, consistent interfaces, reproducibility best practices, and data validation. Use when setting up ITC analysis projects or building pipelines.
- ▌ Ml Nmr Methodology · choxosDeep methodology knowledge for ML-NMR including IPD/AgD integration, population adjustment, numerical integration, and prediction to target populations. Use when conducting or reviewing ML-NMR analyses.
- ▌ Clinical Trials · choxosClinical trial design and analysis methods in R, including randomization, estimands, multiplicity, and reporting.
- ▌ Causal Mediation · choxosCausal mediation analysis in R, including direct and indirect effects, assumptions, and sensitivity analysis.
- ▌ Health Economics · choxosHealth economic analysis in R, including cost-effectiveness, QALYs, decision models, and budget impact.
- ▌ Model Evaluation · choxosModel evaluation in R with performance metrics, calibration, ROC analysis, decision curves, and validation.
- ▌ Pharmacokinetics · choxosPharmacokinetic and pharmacodynamic analysis in R, including NCA, compartmental modeling, and bioequivalence.
- ▌ Recipes Patterns · choxosFeature engineering patterns with recipes, including imputation, encoding, normalization, interactions, and leakage control.
- ▌ Roxygen2 Pkgdown · choxosR package documentation with roxygen2 and pkgdown, including reference topics, articles, and site configuration.
- ▌ Bayesian Modeling · choxosBayesian modeling in R with brms, rstanarm, priors, diagnostics, posterior checks, and model comparison.
- ▌ Genomics Analysis · choxosGenomics analysis in R with Bioconductor, differential expression, enrichment, batch correction, and single-cell workflows.
- ▌ Ipd Meta Analysis · choxosIndividual participant data meta-analysis in R, including one-stage, two-stage, survival, and IPD with aggregate data.
- ▌ Survival Analysis · choxosSurvival analysis in R, including Kaplan-Meier, Cox models, competing risks, RMST, and multi-state models.
- ▌ Pymc Fundamentals · choxosFoundational knowledge for writing current PyMC models including syntax, distributions, sampling, and ArviZ diagnostics. Use when creating or reviewing PyMC models.
- ▌ Stan Fundamentals · choxosFoundational knowledge for writing modern Stan models including program structure, type system, distributions, and best practices. Use when creating or reviewing Stan models.
- ▌ Diagnostic Accuracy · choxosDiagnostic accuracy analysis in R, including sensitivity, specificity, ROC curves, likelihood ratios, and decision curves.
- ▌ Real World Evidence · choxosReal-world evidence analysis in R, including target trial emulation, propensity scores, external controls, and bias analysis.
- ▌ Tidymodels Workflow · choxosTidymodels workflow patterns with recipes, models, workflows, resampling, tuning, and final evaluation.
- ▌ Epidemiology Methods · choxosEpidemiological analysis methods in R for cohort, case-control, confounding control, and causal inference.
- ▌ Network Meta Analysis · choxosNetwork meta-analysis in R, including network setup, consistency, treatment rankings, and league tables.
- ▌ Resampling Strategies · choxosResampling strategies in tidymodels, including validation splits, cross-validation, bootstrap, nested resampling, and grouped data.
- ▌ Mendelian Randomization · choxosMendelian randomization in R, including instrument selection, two-sample MR, pleiotropy checks, and sensitivity analysis.
- ▌ Advanced Adaptive Trials · choxosAdaptive trial designs in R, including platform, basket, MAMS, response-adaptive, and interim decision methods.
- ▌ R Documentation Patterns · choxosR documentation patterns with roxygen2, pkgdown, vignettes, examples, and package site structure.
- ▌ Tidymodels Review Patterns · choxosReview patterns for tidymodels workflows, including leakage, resampling, tuning, metrics, and reproducibility.
- ▌ Mediana Fundamentals · choxosCore Mediana package functions for Clinical Scenario Evaluation (CSE). Use when designing data models, analysis models, evaluation models, and running comprehensive trial simulations.
- ▌ Multiplicity Methods · choxosMultiple testing procedures reference for clinical trials. Use when selecting or implementing multiplicity adjustments, gatekeeping procedures, or graphical approaches.
- ▌ Simtrial Fundamentals · choxosCore simtrial package functions for time-to-event clinical trial simulation. Use when generating survival data, performing weighted logrank tests, or running TTE simulations.
- ▌ Time To Event Methods · choxosSurvival analysis methods including weighted logrank, MaxCombo, RMST, and milestone tests. Use when analyzing TTE data or choosing analysis methods for non-proportional hazards.
- ▌ Group Sequential Methods · choxosGroup sequential design methods for interim analyses, alpha spending, and futility stopping. Use when designing trials with interim looks or implementing spending functions.
- ▌ Power Optimization Patterns · choxosDirect and tradeoff-based optimization strategies for clinical trial design. Use when optimizing sample size, selecting design parameters, or performing sensitivity analysis.
- ▌ Clinical Trial Design Patterns · choxosCommon clinical trial design patterns including multi-arm, multi-endpoint, adaptive, and stratified designs. Use when selecting or implementing trial designs.
- ▌ Meta Analysis · choxosBayesian meta-analysis models including fixed effects, random effects, and network meta-analysis with Stan and JAGS implementations.
- ▌ Regression Models · choxosBayesian regression models including linear, logistic, Poisson, negative binomial, and robust regression with Stan and JAGS implementations.
- ▌ Time Series Models · choxosBayesian time series models including AR, MA, ARMA, state-space models, and dynamic linear models in Stan and JAGS.