m-clark/mixed-models-with-R

Covers the basics of mixed models, mostly using @lme4

Language: R - Size: 58.8 MB - Last synced at: 22 days ago - Pushed at: about 3 years ago - Stars: 137 - Forks: 42

drizopoulos/GLMMadaptive

GLMMs with adaptive Gaussian quadrature

Language: R - Size: 22.9 MB - Last synced at: 11 days ago - Pushed at: about 1 month ago - Stars: 60 - Forks: 14

emjun/tisane

Specification language for generating Generalized Linear Models (with or without mixed effects) from conceptual models

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AIH-SGML/mixmil

Code for the paper: Mixed Models with Multiple Instance Learning

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QCBSRworkshops/workshop07

Workshop 7 - General and generalized linear mixed models (LMM and GLMM)

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boennecd/pedmod

R package with quasi-Monte Carlo methods to estimate mixed models commonly used for random effect structures from pedigrees.

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davidruegamer/deepregression

Fitting Semi-Structured Deep Distributional Regression in R

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dirmeier/mixed-models

Reference implementations for (generalized) linear mixed models.

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panlanfeng/LatentGaussianMixtureModel.jl

The Julia package for estimating and testing a generalized linear mixed model with normal mixture random effects

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ricschuster/R_Workshop_Vienna_2018_02

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itsMidNightsw/PhD_Public

Code related to my PhD's work

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jlpscampos/Perception-of-Excessive-Sleepiness-and-Severe-Fatigue-in-Civil-Aviation-Pilots

Case study (consultancy) with the intent to analyze work conditions for civil aviation professionals in order to review labour legislation.

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celebrezze/postfire-recovery-spectral-recovery

This repository contains data, scripts, and figures for the manuscript entitled 'A fast spectral recovery does not necessarily indicate post-fire forest recovery' which compares spectral recovery, topographic and climatic data, and field measurements of post-fire vegetation dynamics in the Blue Mountains, OR. For more information, see the README

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GidonFrischkorn/Workshop_BayesianStatistics

Materials for a 3 to 4 hour workshop on Bayesian Statistics using the R package `brms`

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lundquist-ecology-lab/urban_aquatic_insects

Urban insect data collected from Binghamton, NY in 2014 and 2015 including R code examples.

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aprabaswara/Risk-Factors-for-Leptospirosis-in-Kenyan-Pastoral-Landscape

A Study of the Risk Factors for Leptospirosis Infection in Kenya.

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alpankratov/number_of_medals_predictions_with_GLMM

The aim of the GLMM Project is to build general linear (mixed) models that predicts the total number of medals won by countries. GLMs and GLMMs are examined in the Part 1 and Part 2 respectively. Refer to memos in pdf files for details.

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aritzLizoain/Analyzing-schizophrenia

Analysis of the evolution of prevalence of thought disorders

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schefferslab/Basham_et_al_2021

Repository for code and data for Basham et al 2022 (Oceologia, https://doi.org/10.1007/s00442-022-05108-9)

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dteuscher1/Catcher-Framing

Project for generalized linear models class at BYU. Modeling the probability that a pitch is a strike using generalized additive models and determining catcher framing abilities and umpire influence on the strike zone using generalized linear mixed models.

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Cyanjiner/peer-tutoring-program

This study used the data collected from Lehigh University's peer tutoring program which focused on 20 courses involving problem-solving skills over three academic years, 2003-04 through 2005-06. An OLS model and generalized liner mixed-effects models were used to measure effect of participation in tutoring in terms of hours spent getting tutored on exogenous final grade on subset of sample. Exploratory data analysis was performed to examine correlations between students' academic performance and other attributes including previous term GPA, high school rank, SAT scores, and demographic characteristics.

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