Cluster Analysis using R with Dr Nema Dean - March 2017

Details: 

23rd March 2017
09.00 - 17.00

Venue
Sheffield Methods Institute, Floor 2, ICOSS Building, The University of Sheffield.

APPLICATIONS FOR THIS COURSE HAVE NOW CLOSED.

Course Details
Cluster analysis provides a suite of techniques for grouping a set of observations or clustering variables into groups. Groups or clusters are formed where observations in the same group are more similar than observations from different groups. The methods are useful for discovering new sub-populations in populations and as a way for optimally partitioning sets of observations.  These methods have bourgeoned in recent years with a wide variety of applications for analysing social/market segregation through to optimally grouping students in classrooms according to skill mastery.
The course will use neighbourhood statistics and simulated data to illustrate how cluster analysis techniques can be applied to urban socio-economic issues.
Find out more about the trainer, Dr Nema Dean.

Objectives
To offer intensive training in cluster analysis using a variety of R packages including: stats, cluster, mclust, pgmm and poLCA  (plus clustMD, flexmix and longclust if time allows)

Learning Outcomes

  • Learn how to implement a range of cluster methods for different types of data
    (continuous, categorical, mixed, high-dimensional) using R
  • Learn how to visually explore cluster structure using simple plots and dendrograms
  • Learn how to use numerical and visual methods of deciding on the number of clusters present
    in data
  • Learn the intuition behind different methods and their advantages/disadvantages
  • Discuss limitations of cluster analysis methods and areas of current research to address these

Programme 
The workshop requires personal work and interaction among the participants and instructors. Each component of the workshop will consist of a lecture followed by a computer practical using R using real case studies in the natural and social sciences. The one-day training programme will consist of the following components with later items only covered if time permits:

  • Introductions - outline; cluster analysis overview; R; R cluster packages; case study data sets; bibliography and resources
  • Exploring data with visualisation methods– for spatially exploring univariate and bivariate data, multidimensional scaling
  • Classical clustering methods - hierarchical clustering and different linkages, partitioning methods including k-means and k-medoids
  • Model-based clustering – finite mixture models, Information criteria, mixture of factor analysers for high-dimensional data
  • Basic latent class analysis – clustering for categorical data
  • Model-based clustering for mixed data (Time permitting) – finite mixture clustering method for datasets with both continuous and categorical data
  • Mixture of regressions (Time permitting) – groups of regressions (rather than single population regression)
  • Longitudinal data clustering (Time permitting) – finite mixture longitudinal clustering

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.

Course costs
This training course is offered free of charge to doctoral students registered on a social science degree programme 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 £100
Academic staff, ESRC funded researchers and UK registered charitable organisations £200
Others £500

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.

Penalty for 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.

Non-paying delegates
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.

Paying delegates
Course fees are non-refundable.  In exceptional circumstances a refund may by permitted at the discretion of the AQMeN Research and Development Manager.

Application process
There are 15 places available on the course. 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 8th March 2017.  Successful applicants will be notified by 13th March 2017.

Travel and accommodation bursaries
Doctoral students registered 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) to Sheffield

Maximum Travel Contribution

Accommodation Contribution

Up to 1 hour (travelling each day)   

2 return trips @£25/trip = £50

NIL

Up to 1 hour (with accommodation)

1 return trip @£25/trip = £25

Up to 1 nights accommodation at maximum £60 per night

Up to 2 hours

1 return trip @£50/trip = £50

Up to 1 nights accommodation at maximum £60 per night

Over 2 hours

1 return trip @£100/trip = £100   

Up to 1 nights accommodation at maximum £60 per night

Reimbursement process
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):

  • Mileage
  • 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.

Contact
If you have any questions regarding the course, please feel free to contact events@aqmen.ac.uk or + 44 (0) 131 651 5536

Directions and Travel
Visit http://www.sheffield.ac.uk/visitors/mapsandtravel for travel advice.

Date: 
Thursday, March 23, 2017 -
09:00 to 17:00
Organiser: 
AQMeN
Location: 
Sheffield
Venue: 
Sheffield Methods Institute, Floor 2, ICOSS¬ Building, The University of Sheffield.

Research Strand: