Nicola Orsini

Nicola Orsini

Researcher

Researcher and teacher of statistical sciences in the fields of medical and global public health sciences.

About me

Nicola Orsini, Ph.D. is Senior Researcher, Associate Professor of Medical Statistics, and Head of the Biostatistics Team at the Department of Global Public Health, Karolinska Institutet. Dr. Orsini has worked for more than 15 years on development and application of quantitative methods widely used in medical and epidemiological research, including dose-response meta-analysis, sensitivity analysis, time-to-event analysis, quantile analysis, and intervention time-series analysis, leading to the publication of more than 180 research articles (H-index=61, i10-index=146).

He is best known for his work on dose-response meta-analysis based on observational and experimental findings. A book chapter on this topic with Donna Spiegelman, Professor Emerita of Epidemiologic Methods at Harvard School of Public Health (Handbook of Meta-Analysis, Chapman & Hall/CRC Handbooks of Modern Statistical Methods, 2020) is available here.

His awards include the 2009 Torgny Wännström Prize for the best doctoral thesis in the field of public health from the Swedish Medical Association. In recognition of exceptional research performance demonstrated by multiple highly cited papers, Dr. Orsini has been named by Web of Science (Clarivate Analytics) among the world's most top-cited (top 1%) scientists whose research leads the world in the field of Social Science for four consecutive years (2017, 2018, 2019, 2020).

He developed, documented, and freely shared several statistical software components in the Stata language. Dr. Orsini is a fellow of the Royal Statistical Society. In 2020 Dr. Orsini has been elected member of the Society of Research Synthesis Methodology. He is in the Executive Board of the Strategic Research Program in Epidemiology at Karolinska Institutet.

Research description

Previous doctoral and postdoctoral students

Alessio Crippa - Development of novel statistical methods for meta-analysis.

Andrea Bellavia - A percentile approach to time-to-event outcomes

Andrea Discacciati - Risk factors for prostate cancer: analysis of primary data, pooling, and related methodological aspects

XingWu Zhou - Methods for intervention time-series analysis.

Selected publications

  • Orsini N. Weighted mixed-effects dose-response models for tables of correlated contrasts. Stata Journal. 2021 (2), 320-347.
  • Orsini, N., and Spiegelman D. Meta-Analysis of Dose-Response Relationships. Chapter 18. Handbook of Meta-Analysis. Chapman and Hall/CRC, 2020. 395-428.
  • Bottai M, Orsini N. qmodel: A command for fitting parametric quantile models. The Stata Journal. 2019 (2), 261-293.
  • Crippa A, Discacciati A, Bottai M, Spiegelman D, and Orsini N. One-stage dose–response meta-analysis for aggregated data. Statistical Methods in Medical Research. 2019. 28 (5), 1579-1596.
  • Crippa A, Thomas I, Orsini N. A pointwise approach to dose-response meta-analysis of aggregated data. International Journal of Statistics in Medical Research. 2018. 7 (2), 25-32.
  • Discacciati A, Crippa A, Orsini N. Goodness of fit tools for dose-response meta-analysis of binary outcomes. Research Synthesis Methods. 2017 Jun; 8(2):149.
  • Crippa A, Khudyakov P, Wang M, Orsini N, Spiegelman D. A new measure of between-studies heterogeneity in meta-analysis. Statistics in Medicine. 2016; 35(21):3661–75.
  • Bellavia A, Bottai M, Orsini N. Evaluating additive interaction using survival percentiles. Epidemiology. 2016 May;27(3):360-4.
  • Crippa A, and Orsini N. Multivariate dose–response meta-analysis: the dosresmeta R Package. Journal of Statistical Software 2016; 72(1):1–15.
  • Discacciati A, Bellavia A, Orsini N, Greenland S. On the interpretation of risk and rate advancement periods. International Journal of Epidemiology. 2015. Dec 15. pii: dyv320.
  • Bellavia A, Discacciati A, Bottai M, Wolk A, Orsini N. Using Laplace regression to model and predict percentiles of age at death, when age is the primary time-scale. American Journal of Epidemiology. 2015. Aug 1;182(3):271-7.
  • Bellavia A, Bottai M, Orsini N. Adjusted survival curves with multivariable Laplace regression. Epidemiology. 2015. Volume 26 - Issue 2. pp: 137-288,e14-e30.
  • Bottai M, Orsini N, Geraci M. A Gradient Search Maximization Algorithm for the Asymmetric Laplace Likelihood. Journal of Statistical Computation and Simulation. 2015. Volume 85, Issue 10.
  • Discacciati A, Orsini N, Greenland S. Approximate Bayesian logistic regression via penalized likelihood by data augmentation. Stata Journal. Volume 15 Number 3: pp. 712-736.
  • Bottai M, Orsini N, A command for Laplace regression. Stata Journal. 2013. Vol. 13, Nr.2, pp. 302-314.
  • Orsini N, Bellocco R, Sjölander A. Doubly robust estimation in Generalized Linear Models. Stata Journal. 2013. Vol. 13, Nr.1. pp. 185-205.
  • Orsini N, Wolk A, Bottai M. Evaluating Percentiles of Survival. Epidemiology. 2012 Sep;23(5):770-1.
  • Orsini N, Ruifeng L, Wolk A, Khudyakov P, Spiegelman D. Meta-analysis for linear and non-linear dose-response relationships: examples, an evaluation of approximations, and software. American Journal of Epidemiology. 2012 Jan 1;175(1):66-73.
  • Orsini N, Bottai M. Logistic quantile regression in Stata. Stata Journal. 2011. Volume 11 Number 3: pp. 327-344.
  • Orsini N, Greenland S. A procedure to tabulate and plot results after flexible modeling of a quantitative covariate. Stata Journal. 2011. 11, Number 1, pp. 1–29.
  • Larsson SC, Orsini N, Wolk A. Vitamin B6 and the Risk of Colorectal Cancer: A Meta-Analysis of Prospective Studies. 2010. JAMA. Mar 17;303(11):1077-83.
  • Orsini N, Bellocco R, Greenland S. Generalized least squares for trend estimation of summarized dose-response data. Stata Journal. 2006, 6: 40-57.

Teaching portfolio

Master Program in Public Health

Course Director "Biostatistics I" (5 weeks) in the Master Program of Public Health, Karolinska Institutet.

Course Director "Biostatistics II" (5 weeks) in the Master Program in Public Health, Karolinska Institutet.

Doctoral Program in Epidemiology

Course Director of "Fundamentals of Stata language " (1 week) in the Doctoral Program in Epidemiology, Karolinska Institutet.

Course Director of "Fundamentals of using Python in Health Related Research" (1 week) in the Doctoral Program in Epidemiology, Karolinska Institutet.

Course Director of "Biostatistics II: Logistic regression for Epidemiologists" (1 week) in the Doctoral Program in Epidemiology, Karolinska Institutet.

Education

Doctoral Degree in Medical Science, Epidemiology, 2008. Karolinska Institutet.

Licentiate Degree in Medical Science, Epidemiology, 2006. Karolinska Institutet.

Academic honours, awards and prizes

  • 2020 Highly Cited Researcher. My research ranks among the top 1% most cited works in the field of Social Sciences. Clarivate Analytics. Web of Science.
  • 2020 Elected Member of the Society of Research Synthesis Methodology.
  • 2019 Highly Cited Researcher. My research ranks among the top 1% most cited works in the field of Social Sciences. Clarivate Analytics. Web of Science.
  • 2018 Highly Cited Researcher. My research ranks among the top 1% most cited works in the field of Social Sciences. Clarivate Analytics. Web of Science.
  • 2017 Highly Cited Researcher. My research ranks among the top 1% most cited works in the field of Social Sciences. Clarivate Analytics. Web of Science.
  • 2012 Young Scholar Award from the Karolinska Institutet's Strategic Program in Epidemiology. Development of novel procedures in epidemiology: A percentiles-based approach to analyse continuous outcomes.
  • 2010 Young Scholar Award from the Karolinska Institutet's Strategic Program in Epidemiology. Developing user-friendly statistical methods for health researchers.
  • 2009 Torgny Wännström Prize. For the best doctoral thesis in the medical field of public health. Nominations submitted by the medical faculties of the universities and the Swedish Medical Society's research mission appoints award winner.
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