Invited Speaker: Drs Vanessa Cave, David Baird and Roger Payne

October 14, 2022

New Developments in Genstat 22

The 22nd Edition of Genstat was released earlier this year. In this presentation, we will showcase some of the new enhancements and features in Genstat 22 and provide a glimpse into the developments underway in Genstat 23.

A key statistical enhancement in Genstat 22 is provided by the new menus and procedures for generalised linear mixed model (GLMM) analysis. Genstat 22 provides considerably greater functionality for displaying and saving output from a GLMM, producing predictions, plotting residuals, and visualising the fit of a GLMM in a separation plot. Furthermore, you can now assess the significance of the fixed terms in a GLMM using permutation tests.

Another development is the addition of equivalence, non-inferiority and non-superiority tests. These are extremely useful tests when the aim of the study is to demonstrate that two treatment means are effectively the same, or that one treatment mean is effectively no smaller or no larger than another. For example, in a medical trial when the aim is to prove that a new drug treatment is just as effective as the standard drug, or in the plant breeding context, when the aim is to show that a new cultivar is at least as resistant to disease as the industry standard. The new menus for t-tests and ANOVA make it easy for you perform equivalence, non-inferiority and non-superiority tests.

Yet another innovation is the ability to analyse data with either fixed-threshold left- or right- censoring using a linear mixed model. During data collection, censoring occurs when measurements cannot be taken above or below a bound. For example, chemical concentrations may be left-censored when they fall below a minimum level of quantification. The new Linear Mixed Models with Censoring menu enables users to easily and quickly fit a linear mixed model to censored data. In the Genstat 23 these facilities are being extended to include left- and right-censored Poisson data.

With Genstat 22 the more flexible RLM web-based licensing system was rolled out. This makes accessing, amending and renewing a license a much smoother process, and moreover it allows us to deliver and manage your license entitlements via a cloud-based license server without installing license server software on your individual device or network.

Genstat 22 also offers many other new menus and commands to help you perform your desired statistical task. For example, there are new menus and procedures for analysing rainfall data, plotting confidence, prediction and equal-frequency ellipses for bivariate data, assessing the importance of fixed effects in a REML analysis using random permutation tests, importing Excel file cell formulae and formatting information into Genstat, editing command windows and lots more! Unfortunately, we cannot showcase all these new features here, so to learn more please do visit:

Development of Genstat 23 is well underway, including new features for displaying large bivariate data sets with observations classified into groups and also for exploring multi-dimensional data.


Roger Payne leads the development of Genstat at VSN, now working part-time after 15 years in the full-time role of VSN’s Chief Science and Technology Officer. He has a degree in Mathematics and a PhD in Mathematical Statistics from University of Cambridge and is a Chartered Statistician of the Royal Statistical Society. Prior to joining VSN, Roger was a statistical consultant and researcher at Rothamsted, becoming their expert on design and analysis of experiments, as well as leader of their statistical computing activities. He originally took over the leadership of Genstat there in 1985 when John Nelder retired. His other statistical interests include generalized and hierarchical generalized linear models, linear mixed models, the study of efficient identification methods (with applications in particular to the identification of yeasts). Roger’s statistical research has resulted in 9 books with commercial publishers, as well as over 100 scientific papers. He has a visiting professorship at Liverpool John Moores University, and also retains an honorary position at Rothamsted, to help him keep in touch with practical statistics.

David Baird is a consultant statistician with 35-years’ experience and has been a Genstat developer for 25 years. He was a biometrician at AgResearch for 25 years before starting his own company VSN NZ. He has worked in a wide range of disciplines including biosecurity, entomology, agriculture, ecology, soil science, plant breeding and microarrays. His statistical interests include experimental design, spatial analysis, data mining and statistical modelling. For the last 9 years he has been the NZ Earthquakes Commission’s statistical consultant. In 2019 he was awarded an ALF Cornish award for contributions to biometrics in Australasia. David has a MSc in Applied Statistics from the University of Reading and a PhD in Statistics from the University of Otago.

Vanessa Cave is an applied statistician interested in the application of statistics to the biosciences, in particular agriculture and ecology, and is a developer of the Genstat statistical software package. She has many years’ experience collaborating with scientists in the agricultural and environmental sciences, using statistics to solve real-world problems. As a biometrician, Vanessa provides expertise on experiment and survey design, data collection and management, statistical analysis, and the interpretation of statistical findings. Vanessa is also an active member of the Australasian statistical community, serving on the New Zealand Statistical Association committee and president-elect of the Australasian Region of the International Biometric Society. She is also an editorial board member for New Zealand Veterinary Journal, an associate editor for Agronomy Journal and an honorary academic at the University of Auckland. Vanessa has an honours degree in Statistics from the University of Otago and a PhD in Statistics from the University of St Andrews.