RKWard: A Comprehensive Graphical User Interface and Integrated Development Environment for Statistical Analysis with R

R is a free open-source implementation of the S statistical computing language and programming environment. The current status of R is a command line driven interface with no advanced cross-platform graphical user interface (GUI), but it includes tools for building such. Over the past years, proprietary and non-proprietary GUI solutions have emerged, based on internal or external tool kits, with different scopes and technological concepts. For example, Rgui.exe and Rgui.app have become the de facto GUI on the Microsoft Windows and Mac OS X platforms, respectively, for most users. In this paper we discuss RKWard which aims to be both a comprehensive GUI and an integrated development environment for R. RKWard is based on the KDE software libraries. Statistical procedures and plots are implemented using an extendable plugin architecture based on ECMAScript (JavaScript), R, and XML. RKWard provides an excellent tool to manage different types of data objects; even allowing for seamless editing of certain types. The objective of RKWard is to provide a portable and extensible R interface for both basic and advanced statistical and graphical analysis, while not compromising on flexibility and modularity of the R programming environment itself

A multi-level approach to travel mode choice - How person characteristics and situation specific aspects determine car use in a student sample

The presented study analyses travel mode choice in a student sample on four frequent trips: To the university, to work, to the favourite leisure activity, and to the favourite shop. The decision to use the car in contrast to alternative travel modes is modelled for each individual trip using a two-level structural equation model with trip specific attributes on Level 1 and person specific attributes on Level 2. Data was gathered in an online travel survey on a student sample of the Ruhr-University in Bochum. Three thousand five hundred and sixty students reported their mode choice for 26,865 individual trips. On the person level a comprehensive action determination model was applied to explain variation in person specific car preference, whereas on the situation level car availability, trip duration, day of travel, disruption in public transportation, weather, daylight, and purpose of the trip were included as predictors. The proposed two-level model is supported by the data, Level 1 predictors explain 62% of Level 1 variation, the Level 2 model explains 48% of Level 2 variance. The intraclass-correlation of car preference is .535. In a final step, interactions between person and trip specific variables were explored

A multi-level approach to travel mode choice - How person characteristics and situation specific aspects determine car use in a student sample

The presented study analyses travel mode choice in a student sample on four frequent trips: To the university, to work, to the favourite leisure activity, and to the favourite shop. The decision to use the car in contrast to alternative travel modes is modelled for each individual trip using a two-level structural equation model with trip specific attributes on Level 1 and person specific attributes on Level 2. Data was gathered in an online travel survey on a student sample of the Ruhr-University in Bochum. Three thousand five hundred and sixty students reported their mode choice for 26,865 individual trips. On the person level a comprehensive action determination model was applied to explain variation in person specific car preference, whereas on the situation level car availability, trip duration, day of travel, disruption in public transportation, weather, daylight, and purpose of the trip were included as predictors. The proposed two-level model is supported by the data, Level 1 predictors explain 62% of Level 1 variation, the Level 2 model explains 48% of Level 2 variance. The intraclass-correlation of car preference is .535. In a final step, interactions between person and trip specific variables were explored.2011 Elsevier Ltd. All rights reserved. This is the authors' accepted and refereed manuscript to the article