CApStONE is a programme to develop research capacity in applied statistics, in partnership with research institutes and universities in southern Africa.  It is a collaboration between the University of Nottingham, UK, where it is led by Prof. Murray Lark,  and colleagues at the University of Zimbabwe with plans to expand to include Lilongwe University of Agriculture and Natural Resources (Malawi), and the University of Zambia.

The CApStONE programme builds on work that these partner institutions have done together.  Some has been specifically focused on capacity strengthening, including the development of statistical training on the R platform.   A review of the capacity strengthening impact of the project by the Liverpool School of Tropical Medicine's Centre for Capacity Research can be found here.

The first principle of CApStONE is that scientific work should be done collaboratively between researchers and statisticians.  Research capacity strengthening requires that we develop strong relationships between scientists and statisticians, and experience of how the disciplines can work together.

Following from this, we consider that the most important principles for scientists to understand are those of sound experimental or sampling design.  Design is foundational,  a poor design will, at best, be a waste of resources and, at worst, will not provide any meaningful results.

We believe in the value of reproducible science, facilitated by open-source platforms for data analysis, in particular the R platform.

A principle of the CApStONE programme is equitable partnership.  In all work to date partners from the global north and south have worked together to develop joint capacity to address problems.  

Introductory videos on the R environment are linked below

Files used in the demonstrations can be accessed here 

1.  Getting started 

2.  Vector data objects 

3.  Character vectors and factors 

4.  Patterned vectors 

5.  Matrices 

6.  Data frames 

7.  Reading data into R 

8.  R libraries and reading data from an Excel spreadsheet

Within the programme we have experience in developing experimental and survey designs for use in the field.  (Underlined text below links to papers and reports).

Surveys have been designed for the examination of shallow groundwater pumps across Malawi, Uganda and Ethiopia .  This design required engagement with a range of stakeholders to address logistical issues, requirements of NGOs and the priorities of funders and governments.  We also undertook the eventual data analysis.

We have studied how various stakeholders interpret uncertain spatial information and use it to make decisions, and evaluated different strategies to communicate the uncertainty more effectively.

Surveys were also designed to support the investigation of spatial variation in soil and other environmental constraints on the micronutrient content of staple crops across Malawi and the Amhara, Oromia and Tigray regions of Ethiopia.  This resulted in new insight into the regionalization of deficiency risks and implications for efficient interventions.

We have supported the analysis of legacy data sets at continental scale across Africa to investigate the resilience of groundwater supplies, and at national and regional scale in Zambia to compare sources of soil information and to evaluate their accessibility and quality. 

We have supported experimental design for studies on agrofortification of crops with micronutrients, both on station and on farm, using power analysis and developing tools to facilitate correct randomization.  We have developed resources to support experimenters.

We have facilitated the use of preregistered designs for agronomic experimentation.

We have developed and applied methodology for expert elicitation, including the assessment of geohazards, assessment of data quality  and interpretation of soil information by experts.

We are collaborating with scientists at CGIAR centres to develop robust statistical models for yield gap analysis