On June 15 2010, at the ANed spring meeting in Utrecht the ANed Biometry Award 2010 was awarded to Judith Lok for her winning paper: Statistical modeling of causal effects in continuous time.

Marc Buyse, the chairman of the jury was present to give a presentation and to hand out the award. The jury report said:

Causal inference is an important tool to analyze the effects of time-varying treatments and confounders on time to event outcomes. The work presented here extends previous results and provides an exhaustive overview of the conceptual framework for studying causal effects in continuous time. The paper is at the same time highly readable, rigorous and mathematically elegant. It will become the reference for much applied work in the future.

Judith Lok has agreed to organise a meeting on the topic of her paper beginning 2011.

The jury also awarded 4 honorary mentions to:

• Ronald B. Geskus, Cause-specific cumulative incidence estimation and the Fine and Gray model under both left truncation and right censoring
  
• Francisca Galindo Garre, Aeilko H. Zwinderman, Ronald B. Geskus and Yvo W.J. Spijkens, A joint latent class changepoint model to improve the prediction of time to graft failure
  
• Mark A. van de Wiel, Johannes Berkhof and Wessel N. van Wieringen,Testing the prediction error difference between 2 predictors  

• Wessel N. van Wieringen and Mark A. van de Wiel, Non-parametric testing for DNA copy number induced differential mRNA gene expression

Here is an overview of all nominations for the ANed Biometry Award 2010.

On June 15 2010, at the ANed spring meeting in Utrecht the ANed Biometry Award 2010 was awarded to Judith Lok for her winning paper: Statistical modeling of causal effects in continuous time.

Marc Buyse, the chairman of the jury was present to give a presentation and to hand out the award. The jury report said:

Causal inference is an important tool to analyze the effects of time-varying treatments and confounders on time to event outcomes. The work presented here extends previous results and provides an exhaustive overview of the conceptual framework for studying causal effects in continuous time. The paper is at the same time highly readable, rigorous and mathematically elegant. It will become the reference for much applied work in the future.

Judith Lok has agreed to organise a meeting on the topic of her paper beginning 2011.

The jury also awarded 4 honorary mentions to:

• Ronald B. Geskus, Cause-specific cumulative incidence estimation and the Fine and Gray model under both left truncation and right censoring
  
• Francisca Galindo Garre, Aeilko H. Zwinderman, Ronald B. Geskus and Yvo W.J. Spijkens, A joint latent class changepoint model to improve the prediction of time to graft failure
  
• Mark A. van de Wiel, Johannes Berkhof and Wessel N. van Wieringen,Testing the prediction error difference between 2 predictors  

• Wessel N. van Wieringen and Mark A. van de Wiel, Non-parametric testing for DNA copy number induced differential mRNA gene expression

Here is an overview of all nominations for the ANed Biometry Award 2010.

Winner of the Biometry Award 2006: Rachid El Galta 

Rachid El Galta received the ANed Biometry Award on 14 June 2006 for the article

El Galta, R., van Duijn, C.M., van Houwelingen, J.C., Houwing-Duistermaat, J.J. (2005). Score statistic to test for genetic correlation for proband-family design. Annals of Human Genetics 69: 373-381.

Abstract of the winning article

In genetic epidemiological studies informative families are often oversampled to increase the power of a study. For a proband-family design, where relatives of probands are sampled, we derive the score statistic to test for clustering of binary and quantitative traits within families due to genetic factors. The derived score statistic is robust to ascertainment scheme. We considered correlation due to unspecified genetic effects and/or due to sharing alleles identical by descent (IBD) at observed marker locations in a candidate region. A simulation study was carried out to study the distribution of the statistic under the null hypothesis in small data-sets. To illustrate the score statistic, data from 33 families with type 2 diabetes mellitus (DM2) were analyzed. In addition to the binary outcome DM2 we also analyzed the quantitative outcome, body mass index (BMI). For both traits familial aggregation was highly significant. For DM2, also including IBD sharing at marker D3S3681 as a cause of correlation gave an even more significant result, which suggests the presence of a trait gene linked to this marker. We conclude that for the proband-family design the score statistic is a powerful and robust tool for detecting clustering of outcomes.

Keywords: binary and quantitative traits, random effects, familial aggregation, excess sharing of alleles IBD

Jury

Prof. dr. David Spiegelhalter
MRC, Cambridge,
United Kingdom 

Prof. dr. Werner Vach
Odense,
Denmark

Prof. dr. Daniel Sørensen
Tjele
Denmark 

Jury report

This is on the basis of the importance of the topic, the elegance of the method, and in particular the fact that the authors have made such an effort to provide a readable and clear discussion of a complex topic requiring sophisticated ideas.

Honourable mentions

Van Houwelingen, H.C., van de Velde, C.J.H., Stijnen, T. (2005). Interim analysis on survival data: Its potential bias and how to repair it. Statistics in Medicine 24: 2823-2835.

Lebrec, J., Putter, H., van Houwelingen, J.C. (2004). Score test for detecting linkage to complex traits in selected samples. Genetic Epidemiology 27: 97-108.

Nominated articles

1. Berger, MPF; Tan, FES. 2004. Robust designs for linear mixed effects models. JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS 53: 569-581.
2. Borm, GF; Melis, RJF; Teerenstra, S; Peer, PG. 2005. Pseudo cluster randomization: a treatment allocation method to minimize contamination and selection bias. STATISTICS IN MEDICINE 24 (23): 3535-3547.
3. ter Braak, CJF; Schaffers, AP. 2004. Co-correspondence analysis: A new ordination method to relate two community compositions. ECOLOGY 85 (3): 834-846.
4. van Dommelen, P; van Buuren, S; Zandwijken, GRJ; Verkerk, PH. 2005. Individual growth curve models for assessing evidence-based referral criteria in growth monitoring. STATISTICS IN MEDICINE 24 (23): 3663-3674.
5. El Galta, R; Van Duijn, CM; Van Houwelingen, JC; Houwing-Duistermaat, JJ. 2005. Score statistic to test for genetic correlation for proband-family design. ANNALS OF HUMAN GENETICS 69: 373-381, Part 4.
6. Engel, B; Bouma, A; Stegeman, A; Buist, W; Elbers, A; Kogut, J; Dopfer, D; de Jong, MCM. 2005. When can a veterinarian be expected to detect classical swine fever virus among breeding sows in a herd during an outbreak? PREVENTIVE VETERINARY MEDICINE 67 (2-3): 195-212.
7. Fiocco, M; Putter, H; Van Houwelingen, JC. 2005. Reduced rank proportional hazards model for competing risks. BIOSTATISTICS 6 (3): 465-478.
8. Geskus RB, Meyer L, Hubert J-B, Schuitemaker H, Berkhout B, Rouzioux C, Theodorou ID, Delfraissy J-F, Prins M, Coutinho RA. Causal Pathways of the Effects of Age and the CCR5-D32, CCR2-64I, and SDF-1 3#A Alleles on AIDS Development. J Acquir Immune Defic Syndr 2005;39:321–326.
9. Goeman, JJ; van de Geer, SA; de Kort, F; van Houwelingen, HC. 2004. A global test for groups of genes: testing association with a clinical outcome. BIOINFORMATICS 20 (1): 93-99.
10. Hendriks, JCM; Teerenstra, S; Punt-Van der Zalm, JPE; Wetzels, AMM; Westphal, JR; Borm, GF. 2005. Sample size calculations for a split-cluster, beta-binomial design in the assessment of toxicity. STATISTICS IN MEDICINE 24 (24): 3757-3772.
11. Holman R, Glas CAW, Lindeboom R, Zwinderman AH, de Haan RJ. 2004. Practical methods for dealing with 'not applicable' item responses in the AMC Linear Disability Score project. Health and Quality of Life Outcomes 2004, 2:29
12. van Houwelingen, HC; van de Velde, CJH; Stijnen, T. 2005. Interim analysis on survival data: Its potential bias and how to repair it. STATISTICS IN MEDICINE 24 (18): 2823-2835.
13. Houwing-Duistermaat, JJ; Uh, H-W; Lebrec, JJP; Putter, H; Hsu, L. 2005. Modeling the effect of an associated single-nucleotide polymorphism in linkage studies. BMC GENETICS 6 (Suppl 1): S46.
14. Koopman, WJM; Gort, G. 2004. Significance tests and weighted values for AFLP similarities, based on arabidopsis in silico AFLP fragment length distributions. GENETICS 167 (4): 1915-1928.
15. Lebrec, J; Putter, H; van Houwelingen, JC. 2004. Score test for detecting linkage to complex traits in selected samples. GENETIC EPIDEMIOLOGY 27 (2): 97-108.
16. Nagelkerke, N; Smits, J; le Cessie, S; van Houwelingen, H. 2005. Testing goodness-of-fit of the logistic regression model in case-control studies using sample reweighting. STATISTICS IN MEDICINE 24 (1): 121-130.
17. Nangendo, G; Stein, A; ter Steege, H; Bongers, F. 2005. Changes in woody plant composition of three vegetation types exposed to a similar fire regime for over 46 years. FOREST ECOLOGY AND MANAGEMENT 217 (2-3): 351-364.
18. Paulo, MJ; Tome, M; Otten, A; Stein, A. 2005. Comparison of three sampling methods in the characterization of cork oak stands for management purposes. CANADIAN JOURNAL OF FOREST RESEARCH-REVUE CANADIENNE DE RECHERCHE FORESTIERE 35 (10): 2295-2303.
19. Putter, H; Sasako, M; Hartgrink, HH; van de Velde, CJH; van Houwelingen, JC. 2005. Long-term survival with non-proportional hazards: results from the Dutch Gastric cancer Trial. STATISTICS IN MEDICINE 24 (18): 2807-2821.
20. Thygesen HH; Zwinderman AH. Modelling the correlation between the activities of adjacent genes in drosophila. 2005. BMC Bioinformatics, 2005, 6:10
21. van der Tweel, I; Schipper, M. 2004. Sequential tests for gene-environment interactions in matched case-control studies. STATISTICS IN MEDICINE 23 (24): 3755-3771.
22. Uh, H-W; Houwing-Duistermaat, JJ; Putter, H; van Houwelingen, HC. 2005. How to quantify information loss due to phase ambiguity in haplotype case-control studies. BMC GENETICS 2005, 6 (Suppl 1): S108.
23. Winkens, B; Schouten, HJA; van Breukelen, GJP; Berger, MPF. 2005. Optimal time-points in clinical trials with linearly divergent treatment effects. STATISTICS IN MEDICINE 24 (24): 3743-3756.

Winner of the Biometry Award 2004: Nico Nagelkerke

Nico Nagelkerke received the ANed Biometry Award on 27 April 2004 for the article

Nagelkerke, N.J., Boshuizen, H.C., de Melker, H.E., Schellekens, J.F., Peeters, M.F., Conyn-van Spaendonck, M. (2003). Estimating the incidence of subclinical infections with Legionella Pneumonia using data augmentation: analysis of an outbreak in The Netherlands. Statistics in Medicine, 22: 3713-24.

Abstract of the winning article

Infections with Legionella bacteria can cause a potentially lethal form of pneumonia known as legionnaires' disease. In 1999 a major outbreak, causing 31 deaths, occurred among visitors and exhibitors of a consumer fair in The Netherlands. The epidemiology of subclinical infections is largely unknown, as there is no reliable method to diagnose such infections. To explore the incidence of subclinical infections, IgG and IgM antibody levels among exhibitors were compared to those among a representative sample of the Dutch population. As exhibitors were assumed to comprise both infected and uninfected individuals, their antibody levels were modelled as a mixture distribution. As infected individuals are expected to cluster around a point source, the spatial aspect of the spread of infections was taken into account. To estimate the distribution of antibody levels among infected individuals and to impute infection status among exhibitors, data augmentation was used. Subclinical infection appeared to be very common and its frequency declined with the distance from the putative source of the outbreak.

Keywords: Legionella spp; data augmentation; mixture analysis; Bayesian methods; spatial statistics

Jury

Prof. dr. Anders Grimvall
Department of Mathematics, Division of Statistics
Linköping University
Sweden 

Prof. dr. Peter Green
School of Mathematics
University of Bristol
United Kingdom

Prof. dr. Geert Verbeke
Biostatistical Centre
Catholic University of Leuven
Belgium 

Jury report

For an inventive and competent statistical analysis of an event that required a thorough scientific evaluation, and for a written presentation demonstrating that statistics can be as exciting as a detective story.

Nominated articles

1. Arends, L., Voko, Z. & Stijnen, T. (2003), ‘Combining multiple outcome measures in a meta-analysis: an application’, STATISTICS IN MEDICINE 22, 1335–1353.
2. Boer, M., ter Braak, C. & Jansen, R. (2002), ‘A penalized likelihood method for mapping epistatic quantitative trait loci with one-dimensional genome searches’, GENETICS 162, 951–960.
3. Eilers, P. & Marx, B. (2002), ‘Generalized linear additive smooth structures’, JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS 11, 758–783.
4. Engel, B., van Reenen, K. & Buist, W. (2003), ‘Analysis of correlated series of repeated measurements: application to challenge data’, BIOMETRICAL JOURNAL 45, 866–886.
5. Geskus, R., Miedema, F., Goudsmit, J., Reiss, P., Schuitemaker, H. & Coutinho, R. (2003), ‘Prediction of residual time to aids and death based on markers and cofactors’, JAIDS-JOURNAL OF ACQUIRED IMMUNE DEFICIENCY SYNDROMES 32, 514–521.
6. Gielen, J. & Kranenbarg, S. (2002), ‘Oxygen balance for small organisms: an analytical model’, BULLETIN OF MATHEMATICAL BIOLOGY 64, 175–207.
7. Graffelman, J. & Aluja-Banet, T. (2003), ‘Optimal representation of supplementary variables in biplots from principal component analysis and correspondence analysis’, BIOMETRICAL JOURNAL 45, 491–509.
8. Grasman, J., Brascamp, J., Leeuwen, J. V. & Putten, B. V. (2003), ‘The multifractal structure of arterial trees’, JOURNAL OF THEORETICAL BIOLOGY 220, 75–82.
9. Holman, R., Glas, C. & de Haan, R. (2003), ‘Power analysis in randomized clinical trials based on item response theory’, CONTROLLED CLINICAL TRIALS 24, 390–410.
10. Houwing-Duistermaat, J., Bijkerk, C., Hsu, L., Stijnen, T., Slagboom, E. & van Duijn, C. (2003), ‘A unified approach to modelling linkage to quantitative and qualitative traits’, ANNALS OF HUMAN GENETICS 67, 457–463.
11. Jansen, R. (2003), ‘Studying complex biological systems using multifactorial perturbation’, NATURE REVIEWS GENETICS 4, 145–151.
12. Nagelkerke, N., Boshuizen, H., de Melker, H., Schellekens, J., Peeters, M. & van Spaendonck, M. C. (2003), ‘Estimating the incidence of subclinical infections with legionella pneumonia using data augmentation: analysis of an outbreak in the Netherlands’, STATISTICS IN MEDICINE 22, 3713–3724.
13. Nangendo, G., Stein, A., Gelens, M., de Gier, A. & Albricht, R. (2002), ‘Quantifying differences in biodiversity between a tropical forest area and a grassland area subject to traditional burning’, FOREST ECOLOGY AND MANAGEMENT 164, 109–120.
14. Nolte, I. & Meerman, G. (2002), ‘The probability that similar haplotypes are identical by descent’, ANNALS OF HUMAN GENETICS 66, 195–209.
15. Ouwens, M., Tan, F. & Berger, M. (2002), ‘Maximin D-optimal designs for longitudinal mixed effects models’, BIOMETRICS 58, 735–741.
16. Putter, H., Sandkuijl, L. & van Houwelingen, J. (2002), ‘Score test for detecting linkage to quantitative traits’, GENETIC EPIDEMIOLOGY 22, 345–355.
17. Stein, A. & Ettema, C. (2003), ‘An overview of spatial sampling procedures and experimental design of spatial studies for ecosystem comparisons’, AGRICULTURE ECOSYSTEMS & ENVIRONMENT 94, 31–47.
18. Tanck, M., Klerkx, A., Jukema, J., Knijff, P. D., Kastelein, J. & Zwinderman, A. (2003), ‘Estimation of multilocus haplotype effects using weighted penalised log-likelihood: Analysis of five sequence variations at the cholesteryl ester transfer protein gene locus’, ANNALS OF HUMAN GENETICS 67, 175–184.
19. ter Braak, C. & Etienne, R. (2003), ‘Improved bayesian analysis of metapopulation data with an application to a tree frog metapopulation’, ECOLOGY 84, 231–241.
20. van der Tweel, I. & van Noord, P. (2003), ‘Early stopping in clinical trials and epidemiologic studies for ”futility”: Conditional power versus sequential analysis’, JOURNAL OF CLINICAL EPIDEMIOLOGY 56, 610–617.
21. Xiridou, M., Geskus, R., de Wit, J., Coutinho, R. & Kretzschmar, M. (2003), ‘The contribution of steady and casual partnerships to the incidence of HIV infection among homosexual men in amsterdam’, AIDS 17, 1029–1038.