What collaborators say:
"He has a deep understanding of statistics, yet is able to skillfully explain complex concepts to people with little-to-no background in statistics both in French and English."
Elsa Brunet-Ratnasingham
Post-doc, UCSF
"I had never before worked with a biostatistician who speaks the same language as me! [...] Personally, our collaboration has allowed me to reconcile with statistics."
Manon Nayrac
Post-doc, CRCHUM
"I highly recommend Justin and his team for your data processing needs in order to have a more robust statistical model than the tests we are accustomed to conducting as biologists!"
Gérémy Sannier
Ph.D candidate, CRCHUM
"Thanks to him, statistics appeared to me as solutions rather than obstacles."
Mathieu Dubé
Research Associate, CRCHUM
As a finishing PhD candidate studying viral immunology, I was trying to wrap up ongoing projects in the lab. We had started researching the dynamics of the immune response against SARS-CoV-2 infection in humans, I had ended up with an explosion of data that I was not trained in analyzing. While preliminary analyses were suggesting that the data was following a specific model, I did not know how to test it statistically.
When I reached out to Justin, he was immediately curious about the project and, even without having a background in immunology, asked insightful questions relating to the biology of my findings. While he looked over my data, we had a lot of back-and-forth to make sure we were on the same page. He did research on his end, then proposed an analysis strategy with a deck of slides that he walked me through in simplified terms. His estimation of the workload was accurate, he would send the results in a detailed email.
We then would schedule a video call or in-person meeting to discuss the meaning of the results and the next step. He has a deep understanding of statistics, yet is able to skillfully explain complex concepts to people with little-to-no background in statistics both in French and English. He also is very open to collaborate with others to solve particularly difficult problems : in the case of one dataset suffering from data sparsity, he interacted with two groups (machine learning and mathematical modeling), trying a number of different strategies until he found one that fit.
One year after we started working on the first dataset together, he has worked on three additional ones with me, two of which are included in a manuscript under preparation, and one already published (https://www.thelancet.com/journals/ebiom/article/PIIS2352-3964(22)00436-4/fulltext). In addition to the statistical analyses, he has written the Statistics section in the Material and Methods, helped in the design of the figures, and corrected the text – where he is quick to spot overinterpretation of statistical results.
In conclusion, I highly recommend Justin’s services in statistical analyses, particularly in the context of large complex biology-related datasets. He is creative in the strategies he proposes, often allowing me to consider my data in new ways. He is highly efficient, responsive via email, well versed in statistics, resourceful, and persevering in the projects he takes on. I look forward to working with him again in the future.
Before the publication of one of my scientific articles, the editor asked me for clarifications and modifications regarding the statistical analyses I had conducted. Finding myself stuck with certain issues, the expertise of Justin was highly recommended to me by one of my colleagues. Justin took the time to understand the biological significance of what I was trying to demonstrate, and he reworked all the data I provided to apply the correct methodological and mathematical approach for my project.
I highly recommend Justin’s services. He is very attentive and extremely instructive. He is capable of working with collaborators from different backgrounds because he takes the time to fully understand our projects. He also dedicates a lot of time to ensure that his counterparts understand his work. He offers both technical and scientific, as well as educational, services. His work is efficient, clean, and remarkably fast!
Thanks to Justin’s assistance, I added value to the work I published. His mathematical approach has also been applied to two other projects.
Personally, our collaboration has allowed me to reconcile with statistics. I now have a better understanding of different mathematical approaches, which has helped me refine my critical thinking.
Justin is very attentive and makes his work accessible to EVERYONE. I had never before worked with a biostatistician who speaks the same language as me!
Over the past year, I have collaborated multiple times with Justin and his team in the context of my research. During my PhD, I have consistently used statistical tests such as Fisher, Kruskal-Wallis, Friedman, Wilcoxon, etc. Recently, I encountered much more complex data to analyze due to paired samples with missing values and very small values. The aforementioned tests do not take into account missing values during multiple comparisons. Justin and his team assisted us in developing a mixed linear model with Holm-Bonferroni correction for multiple comparisons.
In addition to their professionalism and prompt data processing, Justin and his team are always eager to develop models and propose hypotheses to best address our statistical questions. Furthermore, Justin is a very approachable individual and does not hesitate to take the time to explain the results he has obtained and the models developed, which can be challenging to understand without statistical knowledge.
I highly recommend Justin and his team for your data processing needs in order to have a more robust statistical model than the tests we are accustomed to conducting as biologists!
We recently published a series of studies focusing on the immune responses generated by vaccination during the COVID pandemic. A particularly critical review demanded parametric paired statistical tests that could not accommodate the few missing samples in our data set. We were faced with a situation where we had to exclude participants with incomplete sampling and, as a result, lose statistical power.
Justin listened carefully to our needs and limitations, without hesitation in sharing his opinion. Our interactions led him to develop an innovative mixed model that perfectly accommodated the peculiarities of our existing data.
He stood out with his active listening, evident scientific curiosity, multidisciplinary intelligence, and rigorous work, a combination of qualities that I have rarely encountered among statisticians. Thanks to him, statistics appeared to me as solutions rather than obstacles.