About

I work as a methodologist/data scientist/scientific programmer at Statistics Netherlands. In my spare time I play table top role playing games and I like to build stuff: electronics, dioramas, wood, 3d-printing, …

Software

I am the author of a small number of R-packages:

reclin2: Record Linkage Toolkit.

Functions to assist in performing probabilistic record linkage and deduplication: generating pairs, comparing records, em-algorithm for estimating m- and u-probabilities, forcing one-to-one matching. Can also be used for pre- and post-processing for machine learning methods for record linkage. Focus is on memory, CPU performance and flexibility.

simplermarkdown: Simple Engine for Generating Reports using R.

Runs R-code present in a pandoc markdown file and includes the resulting output in the resulting markdown file. This file can then be converted into any of the output formats supported by pandoc. The package can also be used as an engine for writing package vignettes.

LaF: Fast Access to Large ASCII Files

Methods for fast access to large ASCII files. Currently the following file formats are supported: comma separated format (CSV) and fixed width format. It is assumed that the files are too large to fit into memory, although the package can also be used to efficiently access files that do fit into memory. Methods are provided to access and process files blockwise. Furthermore, an opened file can be accessed as one would an ordinary data.frame. The LaF vignette gives an overview of the functionality provided.

Some other projects

datapackage: An R-package for reading and writing data packages.

codelist: An attempt to make working with code lists (as used for categorical variables) easier in R.

bagger: Code for downloading the Dutch Buildings Register (Basisadministratie Gebouwen/BAG) and converting it to CSV format.

fatnetworklib: work in progress on a R-package for working with large networks.

And a lot of project in varying states of completion/abandonment.

Papers

The list below shows some of the more recent papers I have contributed to:

CBS. “Kenmerken Die Samenhangen Met De Kans Om Uit Kinderarmoede Te Komen.” Den Haag: CBS, 2024. Online.

D. J. van der Laan, E. de Jonge, and M. Das. “Development of Educational Segregation Measures using Longitudinal Population Scale Network Data.” Presented at the 9th International Conference on Computational Social Science (IC2S2), Copenhagen, July 17-20, 2023

E. de Jonge, and D. J. van der Laan. “Network Segregation Bubble Size.” Presented at the 9th International Conference on Computational Social Science (IC2S2), Copenhagen, July 17-20, 2023

B. Bos, M. Das, H. Posthumus, J. van der Laan, V. de Heij, and P. Nieuwbeerta. “Persoonsnetwerken en criminaliteit van Nederlandse jongeren.” Tijdschrift voor Criminologie, vol. 64, no. 2, pp. 170–195, 2022, doi: 10.5553/TvC/0165182X2022064002002.

D. J. van der Laan, E. de Jonge, M. Das, S. Te Riele, and T. Emery. “A whole population network and its application for the social sciences.” European Sociological Review, vol. jcac026, 2022, doi: 10.1093/esr/jcac026.

D. J. van der Laan, N. Schalken, and S. Tan. “Risicofactoren voor transitie uit armoede -vervolgonderzoek.” Den Haag: CBS, 2022. Online.

D. J. van der Laan et al., “Risicofactoren voor transities in en uit armoede.” Den Haag: CBS, 2021. Online.

D. J. van der Laan and E. de Jonge, “Measuring local assortativity in the presence of missing values.” in Complex Networks and Their Applications VIII, H. Cherifi, S. Gaito, J. Mendes, E. Moro, and L. Rocha, Eds. Springer, 2020. doi: 10.1007/978-3-030-36683-4_23.

D. J. van der Laan and E. de Jonge, “The importance of work, family, neighbour and school networks for social segregation.” 2020. Presentation on The 6th International Conference on Computational Social Science (IC2S2), 17-20 July 2020.

P.-P. de Wolf, D. J. van der Laan, and D. Zult, “Connecting correction methods for linkage error in capture-recapture.” Journal of Official Statistics, vol. 35, no. 3, pp. 577–597, 2019, doi: 10.2478/jos-2019-0024.

D. J. van der Laan and E. de Jonge, “Maximum likelihood reconstruction of population densities from mobile signalling data.” 2019. Presentation on Netmob, 8-10 July 2019, Mathematical Institute, Oxford University, Oxford, VK