Publications by Rense Nieuwenhuis
Index of the R-Sessions
The R-Sessions are a series of blog entries on using R. A large part consists of an R-manual I once wrote. Other posts include some tricks I found out, as well as entries detailing functions and packages I wrote for R. The series already entails over forty posts, so I decided to create an index. It is found below. On a fixed page on this website ...
2306 sym
Applied R: Manual for the quantitative social scientist
R-Project is an advanced software package for statistical analysis. Several years ago, already, I wrote an introductory manual for several analyses that can be performed with R. Although several parts of this are available from my blog as the R-Sessions, I never publicly published the full document. Now, this changes: for those looking for an app...
1829 sym
influence.ME updated to version 0.9
Influence.ME is an R extension package for R that provides tools for detecting influential data in multilevel regression models. It is developed by Rense Nieuwenhuis (that’s me), Manfred te Grotenhuis, and Ben Pelzer. Recently, a new version (0.9) was uploaded to CRAN, and should be available now to all users. Several improvements and changes w...
2364 sym
Influential Data in Multilevel Regression: What are your strategies?
The application of multilevel regression models has become common practice in the field of social sciences. Multilevel regression models take into account that observations on individual respondents are nested within higher-level groups such as schools, classrooms, states, and countries. In the application of multilevel models in country-compara...
1280 sym
Influence.ME: Tools for Detecting Influential Data in Multilevel Regression Models
Despite the increasing popularity of multilevel regression models, the development of diagnostic tools lagged behind. Typically, in the social sciences multilevel regression models are used to account for the nesting structure of the data, such as students in classes, migrants from origin-countries, and individuals in countries. The strength of m...
3577 sym
Sure, this is silly, but this makes me feel a little bit cooler
Look at this nice video on R statistics. It really advertises doing statistics in a way that is open to anyone! Related To leave a comment for the author, please follow the link and comment on their blog: Curving Normality » R-Project. R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topic...
524 sym
influence.ME now supports new lme4 1.0
influence.ME is an R package for detecting influential data in multilevel regression models (or, mixed effects models as they are referred to in the R community). The application of multilevel models has become common practice, but the development of diagnostic tools has lagged behind. Hence, we developed influence.ME, which calculates standardiz...
1615 sym
Influence.ME now supports sampling weights
Influence.ME is an R package that helps detecting influential cases in multilevel regression models. It has been around for a while now, and recent changes in lme4 broke the functionality of using influence.ME with sampling weights. Thanks to a kind contribution of some code by user Jennifer Bufford, influence.ME now should work with multilevel ...
962 sym
Update influence.ME, or why I love the open source community
The other day, Kevin Darras contacted me about my R package influence.ME. The package didn’t work with the kind of models he wanted to estimate, and Kevin was looking for a solution. He had been able to go ‘under the hood’ of the program code in influence.ME and to program a solution, which he kindly shared with me. After some testing, and ...
2040 sym
Weighted Effect Coding: Dummy coding when size matters
If your regression model contains a categorical predictor variable, you commonly test the significance of its categories against a preselected reference category. If all categories have (roughly) the same number of observations, you can also test all categories against the grand mean using effect (ANOVA) coding. In observational studies, however,...
1599 sym