"Fitting Linear Mixed models in Agricultural Research"

["Clarice G.B. Demetrio" <clarice@esalq.usp.br>]

 Local: Departamento de Ciências Exatas, ESALQ/USP

 Fitting Linear Mixed models in Agricultural Research

 A four day workshop presented by Prof Arthur Gilmour (PhD), NSW,
 Australia,
 (arthur.gilmour@cargovale.com.au)

at the ESALQ/USP in Piracicaba 3-6 August, 2009

 Professor Gilmour (http://www.cargovale.com.au
 <http://www.cargovale.com.au/> ) recently retired from NSW
 Dept of Primary Industries after working 38 years as a Biometrician in
 Agricultural research with a particular link to the sheep breeding group.
 His particular research interest has been the development of software for
 analysis of experimental data and he has been heavily involved in
 developing ASReml, writing most of the code.  ASReml
 (http://vsni.co.uk/software/asreml) is the tool used by many researchers
 internationally for fitting linear mixed models, especially for plant and
 animal breeding.

 The workshop will be a hands on analysis of a variety of typical research
 data sets developing from variations on analysis of variance and
 regression analysis to multivariate, multistratum and longitudinal data.
 It will be designed for researchers and statisticians (post graduate
 level) and aims to develop an understandingg of linear mixed models so
 they can confidently apply the methods to their own research data.
 Participants will be encouraged to provide data sets for class use.

-- 
Clarice Garcia Borges Demétrio
Departamento de Ciências Exatas
Escola Superior de Agricultura "Luiz de Queiroz"
Universidade de São Paulo,
13418-900 Piracicaba, SP
Brasil
phone: 55 19 34294144 R216


Biometry, the active pursuit of biological knowledge by quantitative
methods.? ? R.A. Fisher, 1948


-- 
Clarice Garcia Borges Demétrio
Departamento de Ciências Exatas
Escola Superior de Agricultura "Luiz de Queiroz"
Universidade de São Paulo,
13418-900 Piracicaba, SP
Brasil
phone: 55 19 34294144 R216


Biometry, the active pursuit of biological knowledge by quantitative
methods.? ? R.A. Fisher, 1948