There are 1 repository under linear-mixed-effects-modelling topic.
powerlmm R package for power calculations for two- and three-level longitudinal multilevel/linear mixed models.
Statistical Quantification of Individual Differences: an simulation tool for understanding multi-level phenotypic data in linear mixed models
Matlab and shell scripts associated with the paper "Correcting datasets leads to more homogeneous early 20th century sea surface warming" by Duo Chan, Elizabeth C. Kent, David I. Berry, and Peter Huybers.
Mixed effect modeling with R tutorials
Matlab scripts associated with the paper "Systematic differences in bucket sea surface temperatures caused by misclassification of engine room intake measurements" by Duo Chan and Peter Huybers.
Analyses of saliva Alpha-Amylase and Cortisol in SAM study
Data and analysis scripts associated with the manuscript: Native word order processing is not uniform: An ERP-study of verb-second word order. This paper was accepted for publication in Frontiers in Psychology - Language Sciences on Feb 3, 2022; DOI: 10.3389/fpsyg.2022.668276
Statistical tests for detecting viewer's privacy concerns for photo obfuscation.
Auxiliary material to reproduce to the results of the "How COVID-19 affected GHG emissions of ferries in Europe" manuscript
The data, R programming, and outputs for the research paper testing glucose consumption and cognitive factors. I used R to clean, process, model, and visualize the data. The outputs folder contains the finished products. Link to paper pending.
Poster is available:
Vanilja Hyppönen's special assignment "Effect of linearly increasing galvanic vestibular stimulation on balance". A special assignment is an opportunity to deepen a student's knowledge and skills in a topic of interest after the bachelor's thesis and before the master's thesis.
Workshop about multi-level modeling (MLM) for the Kennedy-Rodrigue Lab (2022-10-26)
A Simple Tutorial for Analyzing Data Using the R Language
Code and Dataset for the Vickrey Sensitivity project. The goal of this project is to identify whether the Marginal Value metric is sensitive to robot-bidder modeling.