R - Complementary Training - Page 5

• # What Is Propensity Matching and How Can We Improve Validity of Causality Claims?

Researchers usually try to randomize correctly, but sometimes the effect is not in the treatment, but maybe in the difference between group (pre-treatment) or during the treatment (for example volume of training) which should be similar/same so we can judge the effects of something else of interest (for example novel periodization). The solutions are to involve covariates in the…

• # R Playbook: Injury Prediction using Random Forest

This is the problem I have been wrestling with for some time and I tried to solve it using Bannister model. I even asked for help on Twitter and couple of data scientists suggested taking a look into “functional data analysis” or creating summary variables and performing regression/classification (which I did here).

• # Workbook: Change Point Analysis of HRV Data

What is Change Point Analysis and why and how can you use it to help you out to make sense of your monitoring data? Find out more….

• # R Playbook: Introduction to Multilevel/Hierarchical Models

I wrote about mixed-level models before and I want to expand on it here. I sort-of finished Andrew Gelman’s Data Analysis Using Regression and Multilevel/Hierarchical Models and will continue to play with it. As far as I know Andrew uses the term multilevel models and avoids the terms fixed and random effect. This is a great book to have.

My…

• # Velocity-Based Training: Signal vs. Noise

This is a R workbook using my older bench press data, in which I want to discuss Signal vs. Noise of Velocity-Based Training (VBT) measurements. This could be used for future reliability studies. The goal is to compare within-individual variations of velocity over load-velocity relationship (noise) with smallest practical velocity difference (in my opinion difference in velocities across nRM,…

• # Non-responders: are they really?

Latest obsession of the researches is individual variation in training responses. The motivation behind this approach (known and emphasized in theory of training as individualization principle) is the creation of personalized medicine or personalized training.

Unfortunately, sometimes we see these individual differences (in treatment reaction), although they are artefacts of within-individual typical variation/error of measurement and regression to the mean.

• # R Playbook: Introduction to Mixed-Models

I just started reading more about mixed-models (multilevel/hierarchical) and will use this as a playbook. Mostly because I learn the best by experimenting with the data and I suggest everyone to try to do the same. So please note that this is just a published playbook – if you find it useful, great, if you find some errors, please…

• # AFL Game GPS Stats Analytics Workbook

Keith Lyons shared one game of data for one AFL game across four quarters for the #UCSIA15 course. I took some time to analyze it using R and created interactive and reproducible document (HTML) using knitr and markdown. You can download markdown file and CSV data file HERE