R packages

simstudy

https://cran.r-project.org/web/packages/simstudy/vignettes/simstudy.html

psych::sim.multilevel

http://personality-project.org/r/html/sim.multilevel.html

 

Re-creating data sets

https://stats.stackexchange.com/questions/30303/how-to-simulate-data-that-satisfy-specific-constraints-such-as-having-specific-m

 

A complex but thorough simulation example from idre.ucla

http://stats.idre.ucla.edu/r/codefragments/mesimulation/

 

Mark-recapture designs for wildlife studies

https://sites.google.com/site/wild8390/software/simulate

 

Multilevel Simulation with specified ICC

https://psychometroscar.wordpress.com/simulate-a-2-level-multilevelhlmlinear-mixed-model/

 

Other

http://clayford.github.io/dwir/dwr_12_generating_data.html

https://web.stanford.edu/class/bios221/labs/simulation/Lab_3_simulation.html

http://stackoverflow.com/questions/23256694/how-can-i-efficiently-generate-a-dataframe-of-simulated-values

 

http://xcelab.net/rm/wp-content/uploads/2010/03/sim.pdf

 

http://www.quantumforest.com/2011/10/simulating-data-following-a-given-covariance-structure/

Bolkers GLMM FAQ: Model summaries (goodness-of-fit, decomposition of variance, etc.) http://bbolker.github.io/mixedmodels-misc/glmmFAQ.html#how-do-i-compute-a-coefficient-of-determination-r2-or-an-analogue-for-glmms

Listserve thread: http://thread.gmane.org/gmane.comp.lang.r.lme4.devel/3281, including a comment by Doug Bates: http://thread.gmane.org/gmane.comp.lang.r.lme4.devel/3281

Listserve thread: http://thread.gmane.org/gmane.comp.lang.r.lme4.devel/684

Cross Validated

A problem that interests me: small marging $R^2$ values for otherwise interesting models:  Is it worth reporting small fixed-effect R2 (marginal R2), large model R2 (conditional R2)?

Partitioning explained variance to fixed effects by comparing r squared (R2) between linear mixed models

Is R2 useful or dangerous? (general issues with R2)

Misc. references on R2 in GLMMs at Proportion of explained variance in a mixed-effects model

Good explanation of Nakagawa and Schielzeth (2013) at: R2 for mixed models with multiple fixed and random effects

An open question: R2 for negative binomial GLMM: R2 from a generalized linear mixed-effects models (GLMM) using a negative binomial distribution

In response to the question Calculating R2 in mixed models using Nakagawa & Schielzeth’s (2013) R2glmm method, some re-posts a response from Douglas Bates where he voices his extreme skepticism about R2 for mixed models.

A related topics: Does the variance of a sum equal the sum of the variances?

R Packages for R2

muMIn::r.squaredGLMM

piecewiseSEM::rsquared

sjstats::r2

sjstats:cod “coefficient of discrimination” for logistic regression.  See Tjur T (2009) Coefficients of determination in logistic regression models – a new proposal: The coefficient of discrimination. The American Statistician, 63(4): 366-372

sjstats:rsme “root mean square error”

Documentation for sjstats discusses how ICC can be used to investigate amount of variance due to clustering

R Packages for related stuff

rptR: Repeatability estimation for Gaussian and non-Gaussian dataAn introduction to repeatability estimation with rptR

References

Jaeger et al 2017.  An R2 statistic for fixed effects in the generalized linear mixed model.  http://www.tandfonline.com/doi/abs/10.1080/02664763.2016.1193725?journalCode=cjas20

LaHuis et al.  2014.  Explained Variance Measures for Multilevel Models.  http://journals.sagepub.com/doi/abs/10.1177/1094428114541701

Tjur T (2009) Coefficients of determination in logistic regression models – a new proposal: The coefficient of discrimination. The American Statistician, 63(4): 366-372

http://www.tandfonline.com/doi/abs/10.1198/tast.2009.08210

 

Assessing the Fit of Regression Models

http://www.theanalysisfactor.com/assessing-the-fit-of-regression-models/

merTools

https://cran.r-project.org/web/packages/merTools/vignettes/merToolsIntro.html

 

predictmeans: “This package provides functions to diagnose and make inferences from various linear models, such as … ‘lme’, and ‘lmer’. Inferences include predicted means and standard errors, contrasts, multiple comparisons, permutation tests and graphs.”

https://cran.r-project.org/web/packages/predictmeans/index.html

 

iccbeta: “This package quantifies the share of variance in a dependent variable that is attributed to group heterogeneity in slopes.”

https://cran.r-project.org/web/packages/iccbeta/iccbeta.pdf

 

influence.ME

https://cran.r-project.org/web/packages/influence.ME/index.html

 

lmerTest

https://cran.r-project.org/web/packages/lmerTest/index.html

 

longpower: sample size calculation for longitudinal data

https://cran.r-project.org/web/packages/longpower/index.html

 

mlmRev: example of lmer

https://cran.r-project.org/web/packages/mlmRev/index.html

 

0) enthought Python distribution

https://www.enthought.com/products/epd/

This seems like a good approach but I couldn’t get it to install

1) General info

How to Set Up a Python Development Environment on Windows

https://www.davidbaumgold.com/tutorials/set-up-python-windows/

 

2) A good IDE: Sublime text:

https://www.sublimetext.com/

 

3) Installing curl for downloading from internet

For installing curl after an initial cygwin installation

How do I install cURL on cygwin?

https://stackoverflow.com/questions/3647569/how-do-i-install-curl-on-cygwin

Scroll down for how to do this from the windows command line and within cygwin; note that the name of the cygwin installer might vary from what is listed in teh answer.

 

4)Add python to you path:  Go to Control Panel, System, Advanced system settings, click on Environment Variables, click on Path, ad something like “;C:Python27”.  See Haddock and Dunn Practical computing for biologists  pg 456 for more details.

4)Install ez_setup.py; uses wget

https://serverfault.com/questions/7282/how-to-run-easy-install-in-cygwin

 

On getting scipy

Installing SciPy, NumPy and matplotlib Under Cygwin

https://www.codefull.org/2015/12/installing-scipy-numpy-and-matplotlib-under-cygwin/

 

extracting tarballs

https://www.interserver.net/tips/kb/extract-tar-gz-files-using-linux-command-line/

 

 

Information on pip, which is installed for me automatically

https://stackoverflow.com/questions/30863501/installing-new-versions-of-python-on-cygwin-does-not-install-pip

 

On installing setup tools

https://packaging.python.org/tutorials/installing-packages/

 

On wheel files .whl

https://pip.pypa.io/en/latest/user_guide/#installing-from-wheels

 

This looks useful:

Getting to Know the Command Line

https://www.davidbaumgold.com/tutorials/command-line/

 

 

This looks useful

https://datanitro.com/blog/python_on_windows

GitHub For Beginners: Don’t Get Scared, Get Started

https://readwrite.com/2013/09/30/understanding-github-a-journey-for-beginners-part-1/

General introduction, starting with downloading git and getting it working via the command line tool that comes with git.

 

GitHub For Beginners: Commit, Push And Go

https://readwrite.com/2013/10/02/github-for-beginners-part-2/

Follow up to “GitHub for Beginners: Don’t get scared, Get Started”

 

Curating Research Assets in Behavioral Sciences: A Tutorial on the Git Version Control System

https://osf.io/preprints/psyarxiv/6tzh8/ (pdf)

Git for Scientists: A Tutorial

http://nyuccl.org/pages/GitTutorial/

 

 

 

rstudio.com: Version Control with Git and SVN

https://support.rstudio.com/hc/en-us/articles/200532077-Version-Control-with-Git-and-SVN

The official RStudio outline of the technical details.  Not much on getting git to work, mostly on how to use it via RStudio.

 

An introduction to Git and how to use it with RStudio

http://r-bio.github.io/intro-git-rstudio/

General introduction to version control

 

The Basic Workflow of Version Control

https://www.git-tower.com/blog/workflow-of-version-control

Comprehensive infographic on version control workflows with git