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 ...
Blog Archives
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 ...
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 ...
Applied R: Manual for the quantitative social scientist
Applied R for the quantitative social scientist is a manual on R written specifically as an introduction for the quantitative social scientist. To my opinion, R-Project is a magnificent statistical program, ready to be accepted and implemented in the social sciences. The flexibility of this program and the way data are handled gives the user a sense of closeness...
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 Sessions 33: Select (nested) observations with equal number of occurences
Recently, I was contacted with an question about R code. A befriended researcher was working with nested data, which was unbalanced. He was working with data in a ‘long’ format: all observations nested within the same group had the same ...
Influence.ME: Simple Analysis
With the introduction of our new package for influential data influence.ME, I’m currently writing a manual for the package. This manual will address topics for both the experienced, and the inexperienced users. I will also present much of the content ...
Presenting influence.ME at useR!
Today I presented influence.ME at the useR! conference in Rennes. Influence.ME is an R package for detecting influential data in mixed models. I developed this package together with Ben Pelzer and Manfred te Grotenhuis. More information about influence.ME can be ...
Influence.ME: don’t specify the intercept
Just recently, I was contacted by a researcher who wanted to use influence.ME to obtain model estimates from which iteratively some data was deleted. In his case, observations were nested within an area, but there were very unequal numbers of ...
One outlier and you’re out: Influential data and racial prejudice
Currently preparing a presentation on analyzing influential data in mixed effects models myself, my eye fell on an article in which important claims on racial prejudice were refuted. An important aspect of the criticism on existing work, is that in ...
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
