EHESP School of Public Health

tripastroturfΤεχνίτη Νοημοσύνη και Ρομποτική

7 Νοε 2013 (πριν από 3 χρόνια και 8 μήνες)

61 εμφανίσεις




EHESP School


of Public Health








Ecole des Hautes Etudes

en Santé Publique


Master of Public Health
-

3rd trimester



Weeks

37 to 41 : from 9
th

September to
7
th

October

2009



UE 204 ; "Core
curriculum"

Information Sciences and biostatistics







Location :
To be announced

Coordinator

:
Khashayar Pakdaman



Wednesday September 9th

Wednesday September 16th

Wednesday September 23th

Wednesday September 30th

Wednesday October 7th

9h30


General introduction (interest
of using modeling,
biostatistics and information
systems techniques in public
health)



Khashayar Pakdaman

9H00


Variance analysis



Elisabeta Vergu

9H00


Time to event analysis.
Censored data, Cox model
(Part I)





Joseph N’Gatchou

㥈〰9


Ca獥⁓瑵ty⁐牥獥湴a瑩潮o
“Legionella”

P牥獥湴慴楯渠潦⁴桥⁄楳 a獥猠
睩瑨⁣潭灵汳潲y⁤ c污la瑩潮

Name Instructor


10H00
-

Coding and Dummy
variables definition

Logistic regression (Part I)

Séverine Deguen

9H00


Construction and selec
tion of
the best model

Step by step procedure


Séverine Deguen


10H30: Introduction of
interaction term in the model

Agnès Verrier

12h : Lunch

12h : Lunch

12h : Lunch

12h : Lunch

12h : Lunch

14H00


Presentation of Stata
Software


The essential
computi
ng
commands(orders)


Name Instructor

17h

14H00


Multiple linear regression



Name Instructor:

Elisabeta
Vergu


17h

14H00


Time to event analysis.
Censored data, Cox model
(Part II)


Joseph N’Gatchou


17h

14H00


Case study


Stata
Application : descr
iptive and
bivariate analysis (selection
of the variable

Séverine Deguen and Agnès
Verrier

17h

14H00


Case study


Stata
Application : Multivariate
analysis and interpretation

Homework presentation

Séverine Deguen and Agnès
Verrier

17h



Ma
s
ter of Publi
c Health
-

Semester 3

Week
45: from 2 to 6 Novem
ber 200
9


UE 214.
Minor A,


“Epidemics: models and inference”

Location:
To be announced

Coordinator: Elisabeta Vergu



Monday November 2
nd


Tuesday November 3
rd


Wednesday November 4
th


Thursday November 5
th


Friday November 6
th


9h30


Theoretical analysis of
dynamical systems
(equilibriums, phase
diagram, R
0

and bifurcation)



K. Pakdaman

9h


R
0
: concept and different
expressions depending on the
disease (directly transmitted,
vector
-
borne, etc)



E. Vergu

9h


Statistical inference
associated to stochastic
epidemic models: likelihood
-
based estimation, MCMC
approaches


Pierre
-
Yves Boelle


9h


Introduction to the methods
and issues surrounding
parameter estimation in
epidemic models (1)



S. Cauchemez

9h


Ec
onomical modelling in
public health





L.Coudeville

12h : Lunch

12h : Lunch

12h : Lunch

12h : Lunch


12h : Lunch

14h


Stochastic modelling (Reed
-
Frost model, continuous time
models, Gillespie algorithm)




Instructor: E. Vergu


17h

14h


Sensitivity ana
lysis of
epidemic models: methods
and illustrations




Instructor: J. Legrand


17h

14h


Bayesian networks and
Bayesian estimation
(modelling approach and
examples)



Instructor: J
-
B. Denis


17h

14h


Introduction to the methods
and issues surrounding
param
eter estimation in
epidemic models (2):
practical aspects (using free
software)

Instructor: S. Cauchemez


17h

14h


Estimating effective
reproductive number (R
e
) for
measles epidemic in Niger:
lessons for intervention.



Instructor: R. Freeman Grais


17h



UE215.
Minor B
,


Advanced modelling and biostatistics”

is not offered in 2009
-
2010




Master of Public Health
-

Semester 3

Week
50: from 7 to 11 December 2009


UE227.
Major A,


Introduction to R

: computing, graphics and statistics








Location : Esp
ace Vinci, Paris

Coordinator:
Arnaud Le Menach



R is a language and environment for statistical computing and graphics. R is highly extensible and is a free software. It com
piles and runs on a wide variety
of UNIX platforms, Windows and MacOS. The course
assumes no prior knowledge of R and covers the following topics.


Prerequisite: you are assumed to be familiar with elementary statistical methodology such as regression models, analysis of v
ariance, hypothesis testing, etc.




Monday Dec
ember
7

Tuesday
D
ecember 8

Wednesday
December 9

Thursday
December 10

Friday
December 11

9h30


Getting familiar with R

-

Available Help

-

R packages




Arnaud Le Menach

9H00


Basic statistical functions

-

Statistical summaries

-

Probability
distributions

-

Statistical tests


Arnau
d Le Menach

9H00


R programming


-

Writing functions

-

Loops and conditional
execution


Arnaud Le Menach

9H00


More statistics with R:

-

Linear & logistic
regression model

-

ANOVA



Arnaud Le Menach

9H00


Project






Arnaud Le Menach

12h : Lunch

12h : Lunch

1
2h : Lunch

12h : Lunch

12h : Lunch

14H00


Data management

-

Data types and
structure

-

Manipulating the data
(vector, matrix and
data frames)

-

Importing and
exporting data

Arnaud Le Menach

17H00

14H00


Exercises








Arnaud Le Menach

17H00

14H00


Graphic
al procedure

-

The plot function

-

Graphic parameters

-

Other plot functions

-

Lattice




Arnaud Le Menach

17H00

14H00


Project








Arnaud Le Menach

17H00

14H00


Presentation








Arnaud Le Menach

17H00





UE228,
Major B, “Integrative approaches t
o infectious disease modeling”
is not offered in 2009
-
2010


UE 229,
Major C, “Disciplinary synthesis”
is not offered in 2009
-
2010