Saturday Lectures: Nonlinear Regression Models
Starting late last year in December, Intego Group management launched a series of lectures on Nonlinear Regression Models, for Statistical Programmers working in our Clinical Division.
The lectures take place on Saturday mornings at our Development Centers in Ukraine and are separate from the expectations of our clients.
Personal advancement training for our Client’s Programmers and Software Engineers during non-working hours are not an uncommon practice here at Intego Group. The culture of our Management Team is to always go above and beyond by looking for opportunities to increase the productivity and knowledge strength of the Programmers and Software Engineers our Clients hire. It has served our Clients well over the years in delivering a best-in-class experience not often found in the outsourcing industry.
Turnout for the trainings have always been great. For this particular series, an average of 25 people have attended each weekend. It speaks volumes to their passion, dedication and work ethic to take time out of their weekends to come and add yet another talent to their skill sets, which immediately benefit the companies they work for.
What are Nonlinear Regression Models?
The name ‘Nonlinear Model’ speaks for itself. This is a type of data analysis when you try to describe data behavior with the help of a function and your function is not linear (y=a*x+b). A great example is shown on the picture below:
How do these lectures benefit the programmers?
Clinical data, quite rarely, has linear behavior, thus knowledge and understanding of nonlinear regression modeling is an important add-on to a basic Statistical Programmer’s background, since it is a powerful tool for data analysis. Many of our Client’s Programmers are asked to perform nonlinear modeling under the supervision of a Project Statistician. This course has helped them to gain a deep understanding of the mathematical and programming background for this type of analysis.
The Nonlinear Regression Model Saturday Lecture Series includes the following topics:
- Relationship between numerical variables: correlation coefficient.
- Regression diagnostics.
- Estimating parameters of regression with one response variable.
- Mixed linear models.
- Regressions with ordinal variables and analysis of covariance.
- Generalized linear models.
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