Ørnulf Borgan

• Kvamme, Håvard & Borgan, Ørnulf (2023). The Brier Score under Administrative Censoring: Problems and a Solution. Journal of machine learning research. ISSN 1532-4435. 24(2), s. 1–26. Fulltekst i vitenarkiv
• Borgan, Ørnulf; Keogh, Ruth H. & Njøs, Aleksander (2022). Use of multiple imputation in supersampled nested case-control and case-cohort studies. Scandinavian Journal of Statistics. ISSN 0303-6898. doi: 10.1111/sjos.12624. Fulltekst i vitenarkiv
• Aalen, Odd O.; Andersen, Per K.; Borgan, Ørnulf; Gill, Richard D. & Keiding, Niels (2022). Martingales in Survival Analysis. I Mazliak, Laurent & Shafer, Glenn (Red.), The Splendors and Miseries of Martingales. Their History from the Casino to Mathematics. Birkhäuser Verlag. ISSN 978-3-031-05987-2. s. 295–320. doi: 10.1007/978-3-031-05988-9. Fulltekst i vitenarkiv
• Kvamme, Håvard & Borgan, Ørnulf (2021). Continuous and discrete-time survival prediction with neural networks. Lifetime Data Analysis. ISSN 1380-7870. 27(4), s. 710–736. doi: 10.1007/s10985-021-09532-6. Fulltekst i vitenarkiv
• Lingjærde, Camilla; Lien, Tonje Gulbrandsen; Borgan, Ørnulf; Bergholtz, Helga & Glad, Ingrid K. (2021). Tailored graphical lasso for data integration in gene network reconstruction. BMC Bioinformatics. ISSN 1471-2105. 22(1). doi: 10.1186/s12859-021-04413-z. Fulltekst i vitenarkiv
• Nedkvitne, Eirik Nøst; Borgan, Ørnulf; Eriksen, Dag Øistein & Rui, Haakon Marius Vatten (2021). Variation in chemical composition of MSWI fly ash and dry scrubber residues. Waste Management. ISSN 0956-053X. 126, s. 623–631. doi: 10.1016/j.wasman.2021.04.007. Fulltekst i vitenarkiv
• Riiser, Even Sannes; Haverkamp, Thomas Hendricus Augustus; Varadharajan, Srinidhi; Borgan, Ørnulf; Jakobsen, Kjetill Sigurd & Jentoft, Sissel [Vis alle 7 forfattere av denne artikkelen] (2020). Metagenomic Shotgun Analyses Reveal Complex Patterns of Intra- and Interspecific Variation in the Intestinal Microbiomes of Codfishes. Applied and Environmental Microbiology. ISSN 0099-2240. 86(6), s. 1–16. doi: 10.1128/AEM.02788-19.
• Pladsen, Arne Valebjørg; Nilsen, Gro; Rueda, Oscar M.; Aure, Miriam Ragle; Borgan, Ørnulf & Liestøl, Knut [Vis alle 18 forfattere av denne artikkelen] (2020). DNA copy number motifs are strong and independent predictors of survival in breast cancer. Communications Biology. ISSN 2399-3642. 3. doi: 10.1038/s42003-020-0884-6. Fulltekst i vitenarkiv
• Kvamme, Håvard; Borgan, Ørnulf & Scheel, Ida (2019). Time-to-Event Prediction with Neural Networks and Cox Regression. Journal of machine learning research. ISSN 1532-4435. 20(129), s. 1–30. Fulltekst i vitenarkiv
• Riiser, Even Sannes; Haverkamp, Thomas Hendricus Augustus; Varadharajan, Srinidhi; Borgan, Ørnulf; Jakobsen, Kjetill Sigurd & Jentoft, Sissel [Vis alle 7 forfattere av denne artikkelen] (2019). Switching on the light: using metagenomic shotgun sequencing to characterize the intestinal microbiome of Atlantic cod. Environmental Microbiology. ISSN 1462-2912. 21(7), s. 2576–2594. doi: 10.1111/1462-2920.14652. Fulltekst i vitenarkiv
• Borgan, Ørnulf & Keilman, Nico (2019). Do Japanese and Italian Women Live Longer than Women in Scandinavia? European Journal of Population. ISSN 0168-6577. 35(1), s. 87–99. doi: 10.1007/s10680-018-9468-2. Fulltekst i vitenarkiv Vis sammendrag

  Life expectancies at birth are routinely computed from period life tables. When mortality is falling, such period life expectancies will typically underestimate real life expectancies, that is, life expectancies for birth cohorts. Hence, it becomes problematic to compare period life expectancies between countries when they have different historical mortality developments. For instance, life expectancies for countries in which the longevity improved early (like Norway and Sweden) are difficult to compare with those in countries where it improved later (like Italy and Japan). To get a fair comparison between the countries, one should consider cohort data. Since cohort life expectancies can only be computed for cohorts that were born more than a hundred years ago, in this paper we suggest that for younger cohorts one may consider the expected number of years lost up to a given age. Contrary to the results based on period data, our cohort results then indicate that Italian women may expect to lose more years than women in Norway and Sweden, while there are no indications that Japanese women will lose fewer years than women in Scandinavia. The large differences seen for period data may just be an artefact due to the distortion that period life tables imply in times of changing mortality.

• Riiser, Even Sannes; Haverkamp, Thomas Hendricus Augustus; Borgan, Ørnulf; Jakobsen, Kjetill Sigurd; Jentoft, Sissel & Star, Bastiaan (2018). A single vibrionales 16S rRNA oligotype dominates the intestinal microbiome in two geographically separated Atlantic cod populations. Frontiers in Microbiology. ISSN 1664-302X. 9. doi: 10.3389/fmicb.2018.01561. Fulltekst i vitenarkiv
• Ergon, Torbjørn; Borgan, Ørnulf; Nater, Chloé Rebecca & Vindenes, Yngvild (2018). The utility of mortality hazard rates in population analyses. Methods in Ecology and Evolution. ISSN 2041-210X. 9, s. 2046–2056. doi: 10.1111/2041-210X.13059.
• Borgan, Ørnulf (2018). Nested Case-Control Studies: A Counting Process Approach. I Borgan, Ørnulf; Breslow, Norman E.; Chatterjee, Nilanjan; Gail, Mitchell H.; Scott, Alastair & Wild, Christopher J. (Red.), Handbook of Statistical Methods for Case-Control Studies. CRC Press. ISSN 978-1-4987-6858-0. s. 329–349.
• Borgan, Ørnulf & Samuelsen, Sven Ove (2018). Cohort Sampling for Time-to-Event Data: An Overview. I Borgan, Ørnulf; Breslow, Norman E.; Chatterjee, Nilanjan; Gail, Mitchell H.; Scott, Alastair & Wild, Christopher J. (Red.), Handbook of Statistical Methods for Case-Control Studies. CRC Press. ISSN 978-1-4987-6858-0. s. 285–301.
• Lien, Tonje Gulbrandsen; Borgan, Ørnulf; Reppe, Sjur; Gautvik, Kaare M & Glad, Ingrid Kristine (2018). Integrated analysis of DNA-methylation and gene expression using high-dimensional penalized regression: a cohort study on bone mineral density in postmenopausal women. BMC Medical Genomics. ISSN 1755-8794. 11(24). doi: 10.1186/s12920-018-0341-2. Fulltekst i vitenarkiv
• Borgan, Ørnulf (2015). Aalen–Johansen Estimator. I Balakrishnan, N.; Brandimarte, Paolo; Everitt, Brian S.; Molenberghs, Geert; Piegorsch, Walter W. & Ruggeri, Fabrizio (Red.), Wiley StatsRef: Statistics Reference Online. John Wiley & Sons. ISSN 9781118445112.
• Borgan, Ørnulf & Zhang, Ying (2015). Using Cumulative Sums of Martingale Residuals for Model Checking in Nested Case-Control Studies. Biometrics. ISSN 0006-341X. 71(3), s. 696–703. doi: 10.1111/biom.12308.
• Strohmaier, Susanne; Røysland, Kjetil; Hoff, Rune; Borgan, Ørnulf; Pedersen, Terje Rolf & Aalen, Odd O. (2015). Dynamic path analysis - a useful tool to investigate mediation processes in clinical survival trials. Statistics in Medicine. ISSN 0277-6715. 34(29), s. 3866–3887. doi: 10.1002/sim.6598.
• Gran, Jon Michael; Lie, Stein Atle; Øyeflaten, Irene Larsen; Borgan, Ørnulf & Aalen, Odd O. (2015). Causal inference in multi-state models-sickness absence and work for 1145 participants after work rehabilitation. BMC Public Health. ISSN 1471-2458. 15:1082. doi: 10.1186/s12889-015-2408-8. Fulltekst i vitenarkiv
• Borgan, Ørnulf & Keogh, Ruth (2015). Nested case–control studies: should one break the matching? Lifetime Data Analysis. ISSN 1380-7870. 21(4), s. 517–541. doi: 10.1007/s10985-015-9319-y.
• Günther, Clara-Cecilie; Tvete, Ingunn Fride; Aas, Kjersti; Sandnes, Geir Inge & Borgan, Ørnulf (2014). Modelling and predicting customer churn from an insurance company. Scandinavian Actuarial Journal. ISSN 0346-1238. s. 58–71. doi: 10.1080/03461238.2011.636502. Vis sammendrag

  Within a company's customer relationship management strategy, finding the customers most likely to leave is a central aspect. We present a dynamic modelling approach for predicting individual customers’ risk of leaving an insurance company. A logistic longitudinal regression model that incorporates time-dynamic explanatory variables and interactions is fitted to the data. As an intermediate step in the modelling procedure, we apply generalised additive models to identify non-linear relationships between the logit and the explanatory variables. Both out-of-sample and out-of-time prediction indicate that the model performs well in terms of identifying customers likely to leave the company each month. Our approach is general and may be applied to other industries as well.

• Günther, Clara-Cecilie; Tvete, Ingunn Fride; Aas, Kjersti; Hagen, Jørgen Andreas; Kvifte, Lars & Borgan, Ørnulf (2014). Predicting Future Claims Among High Risk Policyholders Using Random Effects. I Silvestrov, Dmitrii & Martin-Löf, Anders (Red.), Modern Problems in Insurance Mathematics. Springer. ISSN 978-3-319-06652-3. s. 171–186. doi: 10.1007/978-3-319-06653-0_11. Vis sammendrag

  Insurance claims are often modelled by a standard Poisson model with fixed effects. With such a model, no individual adjustments are made to account for unobserved heterogeneity between policyholders. A Poisson model with random effects makes it possible to detect policyholders with a high or low individual risk. The premium can then be adjusted accordingly. Others have applied such models without much focus on the model’s prediction performance. As the usefulness of an insurance claims model typically is measured by its ability to predict future claims, we have chosen to focus on this aspect of the model. We model insurance claims with a Poisson random effects model and compare its performance with the standard Poisson fixed effects model. We show that the random effects model both fits the data better and gives better predictions for future claims for high risk policy holders than the standard model.

• Nilsen, Gro; Borgan, Ørnulf; Liestøl, Knut & Lingjærde, Ole Christian (2013). Identifying clusters in genomics data by recursive partitioning. Statistical Applications in Genetics and Molecular Biology. ISSN 1544-6115. 12(5), s. 637–652. doi: 10.1515/sagmb-2013-0016.
• Borgan, Ørnulf & Samuelsen, Sven Ove (2013). Nested Case-Control and Case-Cohort Studies. I Klein, John P; van Houwelingen, Hans C; Ibrahim, Joseph G & Scheike, Thomas H (Red.), Handbook of Survival Analysis. CRC Press. ISSN 9781466555662. s. 343–367.
• Paulsen, Jonas; Lien, Tonje Gulbrandsen; Sandve, Geir Kjetil; Holden, Lars; Borgan, Ørnulf & Glad, Ingrid Kristine [Vis alle 7 forfattere av denne artikkelen] (2013). Handling realistic assumptions in hypothesis testing of 3D co-localization of genomic elements. Nucleic Acids Research (NAR). ISSN 0305-1048. 41(10), s. 5164–5174. doi: 10.1093/nar/gkt227. Vis sammendrag

  The study of chromatin 3D structure has recently gained much focus owing to novel techniques for detecting genome-wide chromatin contacts using next-generation sequencing. A deeper understanding of the architecture of the DNA inside the nucleus is crucial for gaining insight into fundamental processes such as transcriptional regulation, genome dynamics and genome stability. Chromatin conformation capture-based methods, such as Hi-C and ChIA-PET, are now paving the way for routine genome-wide studies of chromatin 3D structure in a range of organisms and tissues. However, appropriate methods for analyzing such data are lacking. Here, we propose a hypothesis test and an enrichment score of 3D co-localization of genomic elements that handles intra- or interchromosomal interactions, both separately and jointly, and that adjusts for biases caused by structural dependencies in the 3D data. We show that maintaining structural properties during resampling is essential to obtain valid estimation of P-values. We apply the method on chromatin states and a set of mutated regions in leukemia cells, and find significant co-localization of these elements, with varying enrichment scores, supporting the role of chromatin 3D structure in shaping the landscape of somatic mutations in cancer.

• Aldrin, Magne; Lyngstad, Trude Marie; Kristoffersen, Anja Bråthen; Storvik, Bård; Borgan, Ørnulf & Jansen, Peder Andreas (2011). Modelling the spread of infectious salmon anaemia among salmon farms based on seaway distances between farms and genetic relationships between infectious salmon anaemia virus isolates. Journal of the Royal Society Interface. ISSN 1742-5689. 8(62), s. 1346–1356. doi: 10.1098/rsif.2010.0737.
• Bøvelstad, Hege & Borgan, Ørnulf (2011). Assessment of evaluation criteria for survival prediction from genomic data. Biometrical Journal. ISSN 0323-3847. 53(2), s. 202–216. doi: 10.1002/bimj.201000048.
• Moger, Tron Anders; Haugen, Marion; Yip, Benjamin H. K.; Gjessing, Håkon & Borgan, Ørnulf (2011). A hierarchical frailty model applied to two-generation melanoma data. Lifetime Data Analysis. ISSN 1380-7870. 17(3), s. 445–460. doi: 10.1007/s10985-010-9188-3.
• Bøvelstad, Hege; Nygård, Ståle & Borgan, Ørnulf (2009). Survival prediction from clinico-genomic models - a comparative study. BMC Bioinformatics. ISSN 1471-2105. 10. doi: 10.1186/1471-2105-10-413. Fulltekst i vitenarkiv Vis sammendrag

  Background Survival prediction from high-dimensional genomic data is an active field in today's medical research. Most of the proposed prediction methods make use of genomic data alone without considering established clinical covariates that often are available and known to have predictive value. Recent studies suggest that combining clinical and genomic information may improve predictions, but there is a lack of systematic studies on the topic. Also, for the widely used Cox regression model, it is not obvious how to handle such combined models. Results We propose a way to combine classical clinical covariates with genomic data in a clinico-genomic prediction model based on the Cox regression model. The prediction model is obtained by a simultaneous use of both types of covariates, but applying dimension reduction only to the high-dimensional genomic variables. We describe how this can be done for seven well-known prediction methods: variable selection, unsupervised and supervised principal components regression and partial least squares regression, ridge regression, and the lasso. We further perform a systematic comparison of the performance of prediction models using clinical covariates only, genomic data only, or a combination of the two. The comparison is done using three survival data sets containing both clinical information and microarray gene expression data. Matlab code for the clinico-genomic prediction methods is available at http://www.med.uio.no/imb/stat/bmms/software/clinico-genomic/ webcite. Conclusions Based on our three data sets, the comparison shows that established clinical covariates will often lead to better predictions than what can be obtained from genomic data alone. In the cases where the genomic models are better than the clinical, ridge regression is used for dimension reduction. We also find that the clinico-genomic models tend to outperform the models based on only genomic data. Further, clinico-genomic models and the use of ridge regression gives for all three data sets better predictions than models based on the clinical covariates alone.

• Aalen, Odd O.; Andersen, Per Kragh; Borgan, Ørnulf; Gill, Richard D. & Keiding, Niels (2009). History of applications of martingales in survival analysis. Journal Électronique d'Histoire des Probabililtés et de la Statistique. ISSN 1773-0074. 5(1), s. 1–28.
• Moger, Tron Anders; Pawitan, Yudi & Borgan, Ørnulf (2008). Case-cohort methods for survival data on families from routine registers. Statistics in Medicine. ISSN 0277-6715. 27, s. 1062–1074. doi: 10.1002/sim.3004.
• Nygård, Ståle; Borgan, Ørnulf; Lingjærde, Ole Christian & Størvold, Hege Leite (2008). Partial least squares Cox regression for genome-wide data. Lifetime Data Analysis. ISSN 1380-7870. 14, s. 179–195. doi: 10.1007/s10985-007-9076-7.
• Borgan, Ørnulf (2007). Event history analysis: An overview and some areas of current research. I Østreng, Willy (Red.), Consilience. Centre for Advanced Study at the Norwegian Academy of Science and Letters. ISSN 978-82-996367-4-2. s. 60–64.
• Borgan, Ørnulf & Langholz, Bryan (2007). Using martingale residuals to assess goodness-of-fit for sampled risk set data. I Nair, Vijay (Red.), Advances in statistical modeling and inference. Essays in honor of Kjell A. Doksum. World Scientific. ISSN 981-270-369-1. s. 65–90.
• Gunnes, Nina; Borgan, Ørnulf & Aalen, Odd O. (2007). Estimating stage occupation probabilities in non-Markov models. Lifetime Data Analysis. ISSN 1380-7870. 13, s. 211–240. doi: 10.1007/s10985-007-9034-4.
• Borgan, Ørnulf; Fiaccone, RL; Henderson, R & Barreto, ML (2007). Dynamic analysis of recurrent event data with missing observations, with application to infant diarrhoea in Brazil. Scandinavian Journal of Statistics. ISSN 0303-6898. 34, s. 53–69. doi: 10.1111/j.1467-9469.2006.00525.x.
• Langerod, A; Zhao, H; Borgan, Ørnulf; Nesland, Jahn M; Bukholm, IR & Ikdahl, T [Vis alle 9 forfattere av denne artikkelen] (2007). TP53 mutation status and gene expression profiles are powerful prognostic markers of breast cancer. Breast Cancer Research. ISSN 1465-5411. 9. doi: 10.1186/bcr1675.
• Bøvelstad, Hege; Nygård, Ståle; Størvold, Hege Leite; Aldrin, Magne; Borgan, Ørnulf & Frigessi, Arnoldo [Vis alle 7 forfattere av denne artikkelen] (2007). Predicting survival from microarray data - a comparative study. Bioinformatics. ISSN 1367-4803. 23, s. 2080–2087. doi: 10.1093/bioinformatics/btm305.
• Stavem, K; Bjortuft, O; Borgan, Ørnulf; Geiran, O & Boe, J (2006). Lung transplantation in patients with chronic obstructive pulmonary disease in a national cohort is without obvious survival benefit. The Journal of Heart and Lung Transplantation. ISSN 1053-2498. 25.
• Fosen, Johan; Borgan, Ørnulf; Weedon-Fekjaer, H & Aalen, Odd Olai (2006). Dynamic analysis of recurrent event data using the additive hazard model. Biometrical Journal. ISSN 0323-3847. 48, s. 381–398.
• Fosen, Johan; Ferkingstad, Egil; Borgan, Ørnulf & Aalen, Odd O. (2006). Dynamic path analysis - a new approach to analyzing time-dependent covariates. Lifetime Data Analysis. ISSN 1380-7870. 12, s. 143–167.
• Aalen, Odd Olai; Fosen, Johan; Weedon-Fekjær, Harald; Borgan, Ørnulf & Husebye, Einar (2004). Dynamic analysis of multivariate failure time data. Biometrics. ISSN 0006-341X. 60, s. 764–773.
• Borgan, Ørnulf & Samuelsen, Sven Ove (2003). A review of cohort sampling designs for Cox's regression model: Potentials in epidemiology. Norsk Epidemiologi. ISSN 0803-2491. 13(2), s. 239–248.
• Borgan, Ørnulf (2002). Estimation of covariate-dependent Markov transition probabilites from nested case-control data. Statistical Methods in Medical Research. ISSN 0962-2802. 11, s. 183–202.
• Aalen, Odd Olai; Borgan, Ørnulf & Weedon-Fekjær, Harald (2001). Covariate adjustment of event histories estimated from Markov chains: The additive approach. Biometrics. ISSN 0006-341X. 57, s. 993–1001.
• Borgan, Ørnulf; Langholz, Bryan; Samuelsen, Sven Ove; Goldstein, Larry & Pogoda, Janice (2000). Exposure stratified case-cohort designs. Lifetime Data Analysis. ISSN 1380-7870. 6, s. 39–58.
• Borgan, Ørnulf & Olsen, Espen F. (1999). The efficiency of simple and counter-matched nested case-control sampling. Scandinavian Journal of Statistics. ISSN 0303-6898. 26, s. 493–509.
• Zhang, Jian & Borgan, Ørnulf (1999). Aalen's linear model for sampled risk set data: a large sample study. Lifetime Data Analysis. ISSN 1380-7870. 5, s. 345–363.
• Borgan, Ørnulf & Langholz, Bryan (1998). Risk set sampling for proportional hazards models. I Everitt, Brian S. & Dunn, Graham (Red.), Statistical Analysis of Medical Data: New Developments. Arnold, London. ISSN 0-340-67775-9. s. 75–100.
• Borgan, Ørnulf & Langholz, Bryan (1997). Estimation of excess risk from case-control data using Aalen's linear regression model. Biometrics. ISSN 0006-341X. 53, s. 690–697.
• Langholz, Bryan & Borgan, Ørnulf (1997). Estimation of absolute risk from nested case-control data. Biometrics. ISSN 0006-341X. 53, s. 767–774.
• Grønnesby, Jon Ketil & Borgan, Ørnulf (1996). A method for checking regression models in survival analysis based on the risk score. Lifetime Data Analysis. ISSN 1380-7870. 2, s. 315–328.
• Langholz, Bryan & Borgan, Ørnulf (1995). Counter-matching: A stratified nested case-control sampling method. Biometrika. ISSN 0006-3444. 82, s. 69–79.
• Borgan, Ørnulf; Goldstein, Larry & Langholz, Bryan (1995). Methods for the analysis of sampled cohort data in the Cox proportional hazards model. Annals of Statistics. ISSN 0090-5364. 23, s. 1749–1778.
• Borgan, Ørnulf & Langholz, Bryan (1993). Nonparametric estimation of relative mortality from nested case-control studies. Biometrics. ISSN 0006-341X. 49, s. 593–602.
• Borgan, Ørnulf & Liestøl, Knut (1990). A note on confidence intervals and bands for the survival function based on transformations. Scandinavian Journal of Statistics. ISSN 0303-6898. 17, s. 35–41.
• Borgan, Ørnulf & Hoem, Jan M (1988). Demographic reproduction rates and the estimation of an expected total count per person in an open population. Journal of the American Statistical Association. ISSN 0162-1459. 83, s. 886–891.
• Andersen, Per Kragh; Borgan, Ørnulf; Gill, Richard D. & Keiding, Niels (1988). Censoring, truncation and filtering in statistical models based on counting processes. Contemporary Mathematics. ISSN 0271-4132. 80, s. 19–60.
• Bie, Ole; Borgan, Ørnulf & Liestøl, Knut (1987). Confidence intervals and confidence bands for the cumulative hazard rate function and their small sample properties. Scandinavian Journal of Statistics. ISSN 0303-6898. 14, s. 221–233.
• Borgan, Ørnulf & Ramalu-Hansen, Henrik (1985). Demographic incidence rates and estimation of intensities with incomplete information. Annals of Statistics. ISSN 0090-5364. 13, s. 564–582.
• Andersen, Per Kragh & Borgan, Ørnulf (1985). Counting process models for life history data (with discussion). Scandinavian Journal of Statistics. ISSN 0303-6898. 12, s. 97–158.
• Borgan, Ørnulf; Liestøl, Knut & Ebbesen, Peter (1984). Efficiencies of experimental designs for an illness-death model. Biometrics. ISSN 0006-341X. 40, s. 627–638.
• Borgan, Ørnulf (1984). Maximum likelihood estimation in parametric counting process models, with applications to censored failure times data. Scandinavian Journal of Statistics. ISSN 0303-6898. 11, s. 1–16.
• Ebbesen, Peter; Borgan, Ørnulf & Liestøl, Knut (1983). Decreasing luekemia risk in old AKR mice. Experimental Gerontology. ISSN 0531-5565. 18, s. 347–353.
• Borgan, Ørnulf; Menné, Torkil & Green, Anders (1982). Interaction between nickel allergy and hand eczema in the Danish female population. Scandinavian Journal of Statistics. ISSN 0303-6898. 9, s. 183–185.
• Andersen, Per Kragh; Borgan, Ørnulf; Gill, Richard D. & Keiding, Niels (1982). Linear non-parametric tests for comparison of counting processes, with application to censored survival data (with discussion). International Statistical Review. ISSN 0306-7734. 50, s. 219–258.
• Menné, Torkil; Borgan, Ørnulf & Green, Anders (1982). Nickel allergy and hand dermatitis in a stratified sample of the Danish female population. An epidemiological study including a statistical appendix. Acta Dermato-Venereologica. ISSN 0001-5555. 62, s. 35–41.
• Borgan, Ørnulf (1981). Applications of non-homogeneous Markov chains to medical studies. Nonparametric analysis for prospective and retrospective data. I Victor, N; Lehmacher, W & van Eimeren, W (Red.), Explorative Datenanalyse, Frühjahrstagung der GMDS München, 1980, Proceedings. Springer. ISSN 3540102817. s. 102–115.
• Borgan, Ørnulf (1981). A nonasymptotic criterion for the evaluation of automobile bonus systems. Scandinavian Actuarial Journal. ISSN 0346-1238. s. 165–178.
• Aalen, Odd O.; Borgan, Ørnulf; Keiding, Niels & Thorman, Jens (1980). Interaction between life history events. Nonparametric analysis for prospective and retrospective data in the presence of censoring. Scandinavian Journal of Statistics. ISSN 0303-6898. 7, s. 161–171.
• Borgan, Ørnulf (1979). Comparison of two sequential tests for two-sided alternatives. Journal of The Royal Statistical Society Series B-statistical Methodology. ISSN 1369-7412. 41, s. 101–106.
• Borgan, Ørnulf (1979). On the theory of moving average graduation. Scandinavian Actuarial Journal. ISSN 0346-1238. s. 83–105.

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• Borgan, Ørnulf; Borge, Inger Christin; Engeseth, John; Heir, Odd; Moe, Håvard & Norderhaug, Tea Toft [Vis alle 7 forfattere av denne artikkelen] (2022). Matematikk S2. Aschehoug & Co. ISBN 9788203408991. 334 s.
• Borgan, Ørnulf; Borge, Inger Christin; Engeseth, John; Heir, Odd; Moe, Håvard & Norderhaug, Tea Toft [Vis alle 7 forfattere av denne artikkelen] (2021). Matematikk S1. Aschehoug & Co. ISBN 9788203408946. 375 s.
• Borgan, Ørnulf; Borge, Inger Christin; Engeseth, John; Heir, Odd; Moe, Håvard & Norderhaug, Tea Toft [Vis alle 7 forfattere av denne artikkelen] (2021). Matematikk R1. Aschehoug & Co. ISBN 9788203408847. 414 s.
• Borgan, Ørnulf; Breslow, Norman E.; Chatterjee, Nilanjan; Gail, Mitchell H.; Scott, Alastair & Wild, Christopher J. (2018). Handbook of Statistical Methods for Case-Control Studies. CRC Press. ISBN 978-1-4987-6858-0. 536 s.
• Aalen, Odd O.; Borgan, Ørnulf & Gjessing, Håkon K. (2008). Survival and Event History Analysis: A Process Point of View. Springer. ISBN 978-0-387-20287-7. 539 s.
• Andersen, Per; Borgan, Ørnulf; Gill, Richard D. & Keiding, Niels (1993). Statistical models based on counting processes. Springer-Verlag, New York. ISBN 0172-7397. 767 s.

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• Borgan, Ørnulf & Gjessing, Håkon K. (2019). Special issue dedicated to Odd O. Aalen. Lifetime Data Analysis. ISSN 1380-7870. 25(4), s. 587–592. doi: 10.1007/s10985-019-09483-z.
• Borgan, Ørnulf (2009). Inference and prediction in multi-state models: the additive approach. 57th Session of the International Statistical Institute.
• Borgan, Ørnulf (2007). Discussion contribution to D. Zeng and D.Y. Lin's paper "Maximum likelihood estimation in semiparametric regression models with censored data". Journal of The Royal Statistical Society Series B-statistical Methodology. ISSN 1369-7412. 69(4), s. 545–545.
• Borgan, Ørnulf & Bo H., Lindqvist (2007). Editorial. Scandinavian Journal of Statistics. ISSN 0303-6898. 34(1), s. 1–2.
• Senn, S; Keiding, N; Andrews, N; Musonda, P; Hocine, M & Moreau, T [Vis alle 16 forfattere av denne artikkelen] (2006). Semiparametric analysis of case series data - Discussion. The Journal of the Royal Statistical Society, Series C (Applied Statistics). ISSN 0035-9254. 55, s. 581–594.
• Borgan, Ørnulf; Aalen, Odd O. & Røsjø, Bjarne (2005). Bedre statistikk kan redde flere liv. [Avis]. Informasjonsblad nr 2/2005. Senter for grunnforskning.
• Borgan, Ørnulf (2004). Sverdrup, Erling (1917-1994). I Teugels, Jozef & Sund, Ståle (Red.), Encyclopedia of Actuarial Science. John Wiley & Sons. ISSN 0-470-84676-3. s. 1665–1666.
• Borgan, Ørnulf (2003). Review of "The Statistical Analysis of Failure Time Data" by J.D. Kalbfleisch and R.L. Prentice. Journal of the American Statistical Association. ISSN 0162-1459. 98(464), s. 1084–1085.
• Borgan, Ørnulf (2001). Review of "Modeling Survival Data: Extending the Cox Model" by T. M. Therneau and P. M. Grambsch. Statistics in Medicine. ISSN 0277-6715. 20, s. 2053–2054.
• Borgan, Ørnulf (2001). Cohort sampling in epidemiological studies. 53rd Session of The International Statistical Institute.
• Borgan, Ørnulf (1999). Nested case-control sampling. I Kotz, Samuel; Read, CB & Banks, DL (Red.), Encyclopedia of Statistical Sciences. Wiley, New York. s. 523–528.
• Borgan, Ørnulf (1999). Countermatched sampling. I Kotz, Samuel; Read, CB & Banks, DL (Red.), Encyclopedia of Statistical Sciences. Wiley, New York. s. 129–131.
• Borgan, Ørnulf (1999). Review of "Applied survival analysis" by C.T. Lee. Statistics in Medicine. ISSN 0277-6715. 18, s. 492–494.
• Borgan, Ørnulf (1998). Nelson-Aalen estimator. I Armitage, Peter & Colton, Theodore (Red.), Encyclopedia of Biostatistics. Wiley, New York. ISSN 0-471-97576-1. s. 2967–2972.
• Borgan, Ørnulf (1998). Kaplan-Meier estimator. I Armitage, Peter & Colton, Theodore (Red.), Encyclopedia of Biostatistics. Wiley, New York. ISSN 0-471-97576-1. s. 2154–2160.
• Borgan, Ørnulf (1998). Aalen-Johansen estimator. I Armitage, Peter & Colton, Theodore (Red.), Encyclopedia of Biostatistics. Wiley, New York. ISSN 0-471-97576-1. s. 5–10.
• Borgan, Ørnulf (1989). Discussion contribution to E. Arjas' paper "Survival models and martingale dynamics". Scandinavian Journal of Statistics. ISSN 0303-6898. 16, s. 214–215.
• Günther, Clara-Cecilie; Tvete, Ingunn Fride; Aas, Kjersti & Borgan, Ørnulf (2010). Modellering og prediksjon av kundeavgang. Norsk Regnesentral.

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