Statistical package in Python based on Pandas

Multiple hypothesis testing in Python

The Scott-Knott Effect Size Difference (ESD) test

Python package for permutation tests, for statistics and machine learning.

Design of single- and multi-stage multi-arm clinical trials

A statistics package with a variety of bootstrap and other resampling tools

Adjust p-values for multiple comparisons

Romano-Wolf p-value adjustments for multiple hypotheses testing via the wild bootstrap for objects of type fixest and fixest_multi from the fixest package

python package for generating compact letter display, summarizing results of posthoc comparison tests after ANOVA

SimOutUtils - Utilities for analyzing time series simulation output

SimTOST is an R package designed to facilitate the sample size estimation for bioequivalence studies using a simulation-based approach.

AskoR pipeline: analysis of gene expression data, using edgeR.

A statistics package with a variety of bootstrap and other resampling tools. This repository is synced to the same-named repository owned by GNU-Octave. It exists to facilitate publication of the developmental version of the statistics-resampling toolbox at MathWorks FileExchange.

Statistical testing framework using Monte Carlo simulations.

This code was written and used for statistical analysis and visualisation of data included in Drube et al. 2021.

Spatial Inference for Tractometry

Simulation studies of power and Type I error of mass univariate statistics for ERP data

This is my first repository, it contains my final project in the class of Experimental Design with R Programming. In this project i was working with my team to diagnose an appropiate statistical model for Randomized Complete Block Design (RCBD) with 3 factors.

Data analyses revealing that funnel web spiders are more abundant, more aggregated, and build lower webs in urban centers than urban forests, with plant diversity and road impact influencing their distribution. Vibratory noise may shape arthropod urban ecology.

Reproducible demonstration of the look-elsewhere effect in CMB anomaly searches, via Penrose's Hawking points. Pure Gaussian skies routinely produce 4-5 sigma 'anomalies' once you scan position and scale; the same test still confirms a real signal. A companion script reproduces the Jow & Scott (2020) null result on real Planck data.