Joshua Philipp Entrop

Joshua Philipp Entrop

PhD Student, Statistician, MMSc in Epidemiology

Karolinska Insitutet


I am a PhD student and statistician working at Karolinska Institutet with a passion for health data and statistical analyses. I am working in the research group on cancer epidemiology within the department of medicine at Karolinska Institutet. My research interests lie within applied biostatistics and clinical epidemiology. I am interested in statistical and methodological challenges that come along with analysing registry and survival data. Within the research process, the phase of data analysis is the most interesting one for me. I love to apply different statistical models to data, to reveal new insights, which cannot be seen at the first glance.

All my blog posts on R are also kindly shared on the R-bloggers website.


  • Survival analysis
  • Flexible parametric survival models
  • R programming
  • Epidemiology


  • MMSc Public Health Epidemiology, 2020

    Karolinska Institutet Stockholm, Sweden

  • BA Social Science, 2018

    Ruhr-University Bochum, Germany


R programming

Survival Analysis

Hiking (komoot)




Karolinska Institutet, Department of Medicine Solna, Division for Clinical Epidemiology

Apr 2021 – Present Stockholm, Sweden
As an applied statistician, I mainly work as data handler for the LymphomaBase linkage and as statistical consultant for other research projects within the Cancerepidemiology research group at the Division for Clinical Epidemiology. The LymphomaBase linkage includes data on 40,000 lymphoma patiens and 400.000 comparators from the general population. Both lymphoma patients and comparators are linked to various national Swedish registers as well as specific Swedish quality registers.

PhD Student

Karolinska Institutet, Department of Medicine Solna, Division for Clinical Epidemiology

Sep 2020 – Present Stockholm, Sweden
In my PhD project I study childbearing patterns in Hodgkin and non-Hodgkin lymphoma survivors. For these projects I use complex survival models to study differences in childbearing rates between lymphoma survivors and the general population. Within these projects I also contribue to methods development in the areas of competing risks and recurrent events.

Research Assistant Intern

National Taiwan University, College of Public Health

Jun 2019 – Jul 2019 Taipei, Taiwan
During my internship at the Taiwan National Burden of Disease Centre, I was involved in the estimation of the health burden of alcohol consumption. Most of my work in this project included data analysis and statistical analysis.

Research Intern

NRW Centre for Health, Health Assessment and Forcasting Section

Aug 2017 – Sep 2018 Bochum, Germany
During my internship at the NRW Centre for Health I was mainly engaged in the estimation of the diabetes incidence for Germany based on the Diabetes Population Risk Tool and in the estimation of the diabetes incidence for NRW from 2013 till 2030.

Student Teaching Assistant

Ruhr University Bochum, Social Policy and Social Economy Section

Apr 2017 – Jul 2018 Bochum, Germany
As a student teaching assistant I mainly conducted and planned seminars with 15 to 20 students in addition to the lecture “Introduction to Micro- and Macroeconomics”. One of these seminars was also held as an online seminar via Adobe Connect. In addition to my teaching tasks, I also administered the Moodle and Blackboard courses for both lectures.


Scholarship Holder

The DAAD awards yearly scholarships to outstanding students, who study abroad.
See certificate

Data Scientist with R Track

The Data Scientist with R track in Data Camp includes 23 courses focusing on programming, data management, data analysis and data visualisation in R. During these courses I improved my R skills a lot and became more flexible with data management in R.
See certificate

Scholarship Holder

The FES awards scholarships to outstanding students, who are also engaged in voluntary work besides their studies.

Recent Posts

{ExclusionTable} a package for keeping track of exclusions and inclusions

In today’s blog post we will take a look at a package that allows you to keep track of the number of observations that you in- or exclude from your dataset or study population.

Optimisation of a stratified Cox model using Optimx()

In this blog post we are going to fit a stratified Cox regression model by optimising its likelihood function with Optimx::optimx(). Stratified Cox regression models allow one to relax the assumption of proportional hazards over time between different exposure groups.

Optimisation of a Cox proportional hazard model using Optimx()

In this blog post we will optimise a Cox proportional hazard model using a maximum likelihood estimation (MLE) method. For this we are first going to define the likelihood function of our Cox model and its partial first derivatives, sometimes called the score function.

Comparing the confidence intervals of a Weibull model estimated with flexsurvreg() and optimx()

This blog post is a follow up on my previous post on optimising a Weibull regression model using optimx(). This time I’ll try to find a solution for the discrepancy between the confidence interval estimates of the Weibull hazard function estimated with optimx() and flexsurvreg().

Optimisation of a Weibull survival model using Optimx() in R

In this blog post we will optimise a Weibull regression model by maximising its likelihood function using optimx() from the {optimx} package in R. In my previous blog post I showed how to optimise a Poisson regression model in the same manner.

Recent Publications

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Parenthood Rates and Use of Assisted Reproductive Techniques in Younger Hodgkin Lymphoma Survivors: A Danish Population-Based Study

Type 2 diabetes risk in sarcoidosis patients untreated and treated with corticosteroids