Skip to content

Matherion/userfriendlyscience

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

userfriendlyscience (UFS)

CRAN version badge Monthly downloads badge Total downloads badge Documentation badge Travis-CI Build Status codecov

Userfriendlyscience contains a number of functions that serve two goals. First, to make R more accessible to people migrating from SPSS by adding a number of functions that behave roughly like their SPSS equivalents (also see http://rosettastats.com). Second, to make a number of slightly more advanced functions more user friendly to relatively novice users. The package also conveniently houses a number of additional functions that are intended to increase the quality of methodology and statistics in psychology, not by offering technical solutions, but by shifting perspectives, for example towards reasoning based on sampling distributions as opposed to on point estimates.

The package imports functions from many other packages, which is in line with its function as a 'wrapper package': UFS aims to make many existing functions easier for users coming from SPSS, so sometimes a function is added when it saves the user just some data preparing.

The only publications where the package has been mentioned so far are available at:

Four more have been submitted for publication and are currently available as preprints at PsyArXiv:

  • Peters, G.-J. Y. & Crutzen, R. (2017). Knowing exactly how effective an intervention, treatment, or manipulation is and ensuring that a study replicates: accuracy in parameter estimation as a partial solution to the replication crisis. http://osf.io/cjsk2/

  • Peters, G.-J. Y. & Gruijters, S. (2017). Why your experiments fail: sample sizes required for randomization to generate equivalent groups as a partial solution to the replication crisis. http://osf.io/38vfn/

  • Crutzen, R., Peters, G.-J. Y., & Noijen, J. (2017). How to Select Relevant Social-Cognitive Determinants and Use them in the Development of Behaviour Change Interventions? Confidence Interval-Based Estimation of Relevance. http://osf.io/5gnmz/

  • Gruijters, S., & Peters, G.-J. Y. (2017). Introducing the Numbers Needed for Change (NNC): A practical measure of effect size for intervention research. http://osf.io/2bau7/

All are (and will be) Open Access. Please cite the manual and/or one of these publications when you use the package.

If you have any questions, you can reach me at [email protected].

About

The R userfriendlyscience package

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages