Seminarios do prof. Chris Brien

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

Caros colegas,
Estará visitando o Departamento de Ciências Exatas da ESALQ/USP,
no período de 02/06 a 01/07/2010, o professor Chris Brien
(School of Mathematics and Statistics, University of South Austrália,
Adelaide, Austrália). Nesse período, estará desenvolvendo pesquisa
conjunta com docentes do LCE e proferirá", no dia 17/06/2010, às 16h, o
seminário
"Tiers in gene-expression microarray experiments"
e dará um aula, em data e horário a serem marcados, sobre:
"Formulating mixed models for experiments, including longitudinal
experiments"

Seguem os "abstracts". Por favor, divulguem.
Cordiais saudações, Clarice

#########
Abstract 1: Tiers in gene-expression microarray experiments
Chris Brien
School of Mathematics and Statistics, University of South Australia,
Australia

Gene-expression microarray experiments are two-phased and multitiered: the
first phase is a material collection phase and the second phase is the
microarray phase. They constitute a subset of experiments with a second
phase in the laboratory. Recent papers have formulated the analysis of
some two-phase microarray experiments in which the microarray experiment
is conducted on material derived from a prior experiment. The methods used
lengthy and ad hoc. A general method, based on tiers, will be described
for synthesizing mixed models and analyses and the results compared to
those already published. In this, it will be demonstrated that
pseudofactors can be used to ensure that only real sources of variation
are retained in the analysis. Also discussed will be how, as for two-phase
experiments in general, the properties of the first-phase design shape
those of the whole experiment.

Abstract 2:
Formulating mixed models for experiments, including longitudinal experiments
Chris Brien1 and Clarice Demétrio2
1 School of Mathematics and Statistics, University of South Australia,
Australia
2 Departmento de Ciências Exatas, ESALQ, Universidade de São Paulo, Brasil

Mixed models have become important in analyzing the results of
experiments, particularly those that require more complicated models such
as those that involve longitudinal data. A method for deriving the terms
in a mixed model, described by Brien and Demétrio (2009) [J. Agric. Biol.
and Env. Stat., 14, 253-80] will be presented. It extends the method
described by Brien and Bailey [J. Roy. Stat. Soc., Series B, 68 (2006):
571-609] to explicitly identify terms for which autocorrelation and smooth
trend, arising from longitudinal observations, needs to be incorporated in
the model. At the same time we retain the principle that the model used
should include, at least, all the terms that are justified by the
randomization. This is done by dividing the factors into sets, called
tiers, based on the randomization and determining the nesting and crossing
relationships between factors. To illustrate the method, a mixed model for
the randomized complete block design with longitudinal observations is
outlined. The mixed model analysis of data from a three-phase experiment
to investigate the effect of time of refinement on Eucalyptus pulp from
four different sources is also described. For this example, cubic
smoothing splines are used to describe differences in the trend over time
and unstructured covariance matrices between times are found to be
justified.

-- 
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