Statistical Analysis of Networks using R packages
APPLICATIONS FOR THIS EVENT ARE NOW CLOSED. IF YOU HAVE ANY QUESTIONS PLEASE CONTACT firstname.lastname@example.org
13 December 2016
University of Sheffield
This is a one-day hands-on training workshop led by Dr Nema Dean, University of Glasgow.
Statistical network analysis, otherwise known as social network analysis, is made up of a suite of techniques for summarizing, graphing and modeling network or graph data. This kind of data comes about when the main interest lies in the relationships or connections between objects (be they people, businesses or other items) rather than the objects themselves. This is also known as relational data. Some of this kind of data comes from social media but other examples include diplomatic relationships between countries, shared board membership of company boards and many others. Interest in this data may lie in summarizing global characteristics, characterizing the relationship between explanatory variables and the likelihood/strength of connections, optimal plotting of the graph underlying the data or grouping together the objects that are more tightly connected.
To offer intensive training in statistical network analysis using a variety of R packages including: network, igraph, intergraph, ergm, statnet and sna
- Learn how to create, import and transform network data in R
- Learn how to implement a range of social network methods for different types of data using R
- Introduction to graph summaries and how to interpret their values
- Learn how to create plots of graphs of network data to allow visual exploration
- Learn about exponential graph models and how to fit them to network data
- Looking at different partition and clustering methods for graph data
- Discuss limitations of statistical network analysis methods and areas of current research
Criteria for selection
Participants must have a good understanding and practical experience of introductory statistics including descriptive statistics (such as the mean, median, sd), probabilities and distributions. It is also important that applicants are using R and can use R to run basic descriptive statistics and graphs.
About the Trainer
Dr Nema Dean’s research interests are in developing new clustering and classification methods. Past work has involved research on finite mixture model based methods and variations that incorporate variable selection and semi-supervised updating. She is currently working on creating hybrid clustering methods using both parametric and classical algorithmic approaches. She has also developed new mixture model clustering methods for discrete and space-restricted data. Social network analysis and dynamic treatment regimes are also current areas of interest. Application areas she worked on include: housing markets, cDNA microarrays, electronic educational testing, food authenticity studies and many others. Dr Dean is on the committee for an International Federation of Classification Societies initiative to promote good benchmarking practices in clustering research.
This training course is offered free of charge to doctoral students registered on a social science degree programme at a Scottish University or to doctoral students studying at an ESRC-funded Doctoral Training Centre.
Remaining places will be open to others for a fee:
|Doctoral students studying at a non-DTC institution||£30|
|Academic staff, ESRC funded researchers and UK registered charitable organisations||£60|
Please note that AQMeN can only accept payment for training via the University of Edinburgh ePay system. We are unable to issue invoices or accept cheques for payment. All payments must be received within 14 days of a place being offered otherwise the place will be released. Payment should not be made until you have received confirmation that you have been allocated a place on the course.
There are 15 places available on the course and places will be allocated following a process of application.
To apply for this event, a completed on-line application form should be submitted by 12 noon on 4th November. Successful applicants will be notified by 11th November.
Travel and accommodation bursaries:
Doctoral students registered on a social science degree programme at a Scottish university or at an ESRC-funded DTC may be eligible to claim travel and/or accommodation costs to attend.
In order to be eligible for a bursary you must reside outside Sheffield and attend a university outside Sheffield. Reimbursement can only take place if you follow the reimbursement process detailed below and bursaries for eligible students will be capped at the following rates:
|Travel time (by rail) from Sheffield||Maximum Travel Contribution
|Up to 1 hour (travelling each day)||2 return trips @£25/trip = £50||NIL|
|Up to 1 hour(with accomodation)||1 return trip @£25/trip = £25||Up to 1 nights accomodation at maximum £60 per night|
|Up to 2 hours||1 return trip @£50/trip = £50||Up to 1 nights accomodation at maximum £60 per night|
|Over 2 hours||1 return trip @£100/trip = £100||Up to 1 nights accomodation at maximum £60 per night|
Students are responsible for arranging travel and/or accommodation (if applicable) themselves and will only be reimbursed upon presentation of original receipts (no photocopies or credit card receipts will be accepted) and completion of the relevant expense claim form which will be provided post-event.
AQMeN will not reimburse the following costs (unless agreed prior to the event):
- First class travel
- Meals or room service
- Inter-city travel (e.g. buses to and from event venue)
- Taxi fares
- Credit card fees
- Sundries (e.g.wireless internet access or newspapers at accommodation)
All expense claims and receipts must be received by the AQMeN office no later than 2 weeks following the last day of the event in order to be eligible for reimbursement.
Cancellation and Non-attendance:
By applying for this course, you are expected to attend for the full duration. Failure to attend all sessions (unless by prior agreement with the AQMeN core team) may result in a charge of £50 per day of the course missed, non-reimbursement of expenses and ineligibility to be considered for future AQMeN training courses and events.
If after receiving an allocated place on the course you are no longer able to attend, you must notify AQMeN as soon as possible to allow the place to be offered to someone on the waiting list. Failure to do so may result in a charge of £50 per day of the course, non-reimbursement of expenses and ineligibility to be considered for future AQMeN training courses and events.
Course fees are non-refundable. In exceptional cirumstances a refund may by permitted at the discretion of the AQMeN Research and Development Manager.
If you have any questions regarding the course, please feel free to contact email@example.com or + 44 (0) 131 650 2105