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1 = SMALL AREA ESTIMATION, SPRING 2015 =
2
3 **Lecturer**
4
5 **~ **__[[Risto Lehtonen>>url:http://wiki.helsinki.fi/display/mathstatHenkilokunta/Lehtonen%2C+Risto||shape="rect"]]__
6
7 **Code**
8
9 78405
10
11 **Type and Credits**
12
13 Intermediate level course
14 Exam (6 cu) or exam plus (optional) practical/theoretical homework (2 cu), total 8 cu
15
16 Advanced level course
17 Exam (6 cu) plus (compulsory) practical/theoretical homework (2 cu), total 8 cu
18
19 **Scope**
20
21 Lectures 15 hours, PC classes 15 hours
22
23 **Description**
24
25 The course covers topics in modern statistical methods for the estimation of parameters for population subgroups or domains and small areas (Small Area Estimation, SAE). Topics include sampling design for SAE, design-based model-assisted methods (generalized regression estimation, calibration techniques), model-based methods (synthetic, EBLUP and EBP estimators), variance and MSE estimation, SAS tools, R tools, and real-world applications (mainly in social and health sciences and official statistics). Case studies include applications in the estimation of poverty indicators (poverty rate, inequality indicators) for regional areas (small or large). The course is of applied type.
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27 When completing the course, students are expected to be familiar with approaches, methods and computational tools in the estimation for regions and other population subgroups and becoming capable to apply the methods in typical real-world analysis situations. Basic knowledge in statistical modelling, sampling methods and statistical computation (R, SAS) would help successful participation.
28
29 **Target group**
30
31 The course is intended to fit for students majoring or graduating in statistics and for Master level and post-graduate (doctoral) students in quantitative studies in applied sciences incl. social and behavioral sciences and economics (e.g. REMS). As an applied type course, the course also would fit well for statisticians and researchers in research institutes and elsewhere.
32
33 **Schedule**
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35 III period
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37 Lecture sessions:  Tuesday at **16-19** Exactum CK111, Kumpula campus (note time change)
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39 PC training sessions: Thursday** at 16-19** Exactum C128, Kumpula campus
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41 Exam: Tuesday 24.2.2015 at 16-18 Exactum CK111
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43
44
45 |(((
46 **Lectures**
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52 **PC training**
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57 Tuesday13.1.
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61 -
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68 Thursday 22.1.
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71 Tuesday 27.1.
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75 Thursday 29.1.
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78 Tuesday 3.2.
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82 Thursday 5.2.
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85 Tuesday 10.2.
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89 Thursday 12.2.
90 (% style="color: rgb(0,0,0);" %)R tools for SAE
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93 (% style="color: rgb(0,0,0);" %)Tuesday 17.2.
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97 (% style="color: rgb(0,0,0);" %)Thursday 19.2.
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100 (% style="color: rgb(255,0,0);" %)EXAM(%%)
101 (% style="color: rgb(255,0,0);" %)Tuesday 24.2.
102 at 16:00-18:00
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108
109 **~ **
110
111 **Textbooks and selected articles**
112
113 **~ **Rao J.N.K. (2003). [[Small Area Estimation>>url:http://eu.wiley.com/WileyCDA/WileyTitle/productCd-0471413747.html||shape="rect"]]. New York: John Wiley & Sons.
114
115 Lehtonen R. and Pahkinen E. (2004). Practical Methods for Design and Analysis of Complex Surveys. Second Edition. Chichester: Wiley. [[Chapter 6>>attach:Lehtonen_Pahkinen Chapter_6.pdf]].
116 e-book: Dawsonera [[Helka>>url:https://helka.linneanet.fi/cgi-bin/Pwebrecon.cgi?LANGUAGE=English&DB=local&PAGE=First&init=1||shape="rect"]]
117
118 Lehtonen R. and Veijanen A. (2009). Design-based methods of estimation for domains and small areas. In: C. R. Rao and D. Pfeffermann (eds.), Handbook of Statistics 29B. Sample Surveys: Inference and Analysis. Amsterdam: Elsevier. pp. 219-249.
119 Download[[ here>>attach:Ch31-N53124.pdf]]
120
121 Lehtonen R. and Veijanen A. Model-assisted methods to small area estimation of poverty indicators. In: Pratesi M. (Ed.) (2015). Analysis of Poverty Data by Small Area Estimation. Chichester: Wiley. (Forthcoming, to be distributed to participants)
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123 Lehtonen R. and Djerf K. (2008). Survey sampling reference guidelines. Luxembourg: Eurostat Methodologies and Working papers.
124 Download [[here>>attach:ENG_Survey-sampling-reference-guidelines_KS-RA-08-003-EN.pdf]]
125
126 **Web materials**
127
128 VLISS-virtual laboratory in survey sampling [[http:~~/~~/vliss.helsinki.fi>>url:http://vliss.helsinki.fi/||shape="rect"]]
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130 [[Small Area Estimation resources>>url:http://civilstat.com/2013/02/small-area-estimation-resources/||shape="rect"]]
131
132 **Lecture materials**
133
134 [[Topic 1>>attach:Topic1.pdf]] Introduction to SAE
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136 [[Topic 2>>attach:Topic2.pdf]] Basic concepts and approaches
137
138 [[Topic 3>>attach:Topic3.pdf]] Direct estimators for domains
139 [[Example>>attach:Example_HT_Hajek.pdf]]
140 [[Supplement >>attach:SUPPLEMENT_Topic_3.pdf]]to Topic 3
141
142 [[Topic 4 - Part 1>>attach:Topic4_Part-1.pdf]]
143 [[Extract >>attach:Ote_Lehtonen-Veijanen_2009.pdf]](Lehtonen-Veijanen 2009)
144
145 [[Topic 4 - Part 2>>attach:Topic4_Part-2.pdf]]
146 [[Supplement>>attach:Summary_Examples.pdf]]: Summary of examples
147
148
149 [[Topic 4 - Part 3>>attach:Topic4_Part-3.pdf]][[Supplement:>>attach:SUPPLEMENT to Topic4_Part3.pdf]] Extended family of GREG estimators
150
151 [[Topic 5>>attach:SAE_Final lecture.pdf]]
152 [[Supplement:>>attach:SAE_SUPPLENENT to Topic5_EBLUP.pdf]] EBLUP
153 [[Summary>>attach:SAE_Summary.pdf]]
154
155 [[Additional reference>>url:http://eprints.soton.ac.uk/8165/1/8165-01.pdf||shape="rect"]]: Saei and Chambers (2003)
156 Small area estimation under linear and generalized linear mixed models with time and area effects.
157 University of Southampton: S3RI Methodology Working Paper M03/15.
158
159 Case studies                   
160 [[Case Study 1>>attach:Case_study-1.pdf]]
161 [[Case Study 2>>attach:Case_study-2.pdf]]
162
163 **PC training materials**
164
165 [[PC class 1>>attach:PC-class_1_update.sas]] (updated in PC class 22 Jan.)
166
167 [[PC class 2>>attach:PC-class_2_update.sas]] (updated in PC class 29 Jan.)
168 [[SAS macro >>attach:PC-class_2_simul.sas]]for simulation
169
170 [[PC class 3>>attach:PC_class_3_update.sas]] (updated in PC class 5 Feb.)
171 [[Technical summary>>attach:PC3_SRSWOR-kaavat.pdf]] for HT and GREG
172
173 PC class 4 on Thursday 12 Feb.    
174 Guest speaker: Adj.Prof. Ari Veijanen
175 [[RDomest materials >>attach:RDomest materials.zip]](zipped folder)
176
177 [[PC class 5>>attach:PC-class_5_update.sas]] (updated 19 Feb.)
178
179 **Data**
180
181 [[Population dataset>>attach:pop.sas7bdat]] (SAS-data to be downloaded)
182
183 [[Population dataset >>attach:pop.txt]](pop.txt)
184
185 **SAS tools
186 [[Small area estimation in SAS>>attach:SAS_Small-area-estimation.pdf]]**
187
188 **SAS macro EBLUPGREG** (Dr Ari Veijanen)
189 [[EBLUPGREG manual>>attach:SAS_Macro_EBLUPGREG_Manual.pdf]]
190 [[Macro EBLUPGREG code>>attach:Macro_EBLUPGREG-2.sas]]
191 [[SAS Catalog>>attach:eurarea.sas7bcat]]
192
193 **Resources to help you learn and use SAS
194 **(UCLA Statistical Consulting Group )
195 [[http:~~/~~/www.ats.ucla.edu/stat/sas/>>url:http://www.ats.ucla.edu/stat/sas/||shape="rect"]]
196
197 **R tools
198 **RDomest** ** (Dr Ari Veijanen)
199
200 **Additional R tools
201 **Package [[Survey>>url:http://cran.r-project.org/web/packages/survey/index.html||shape="rect"]] (Thomas Lumley)
202 Package [[SAE>>url:http://cran.r-project.org/web/packages/sae/sae.pdf||shape="rect"]] (Isabel Molina)
203
204 **Homework**
205
206 [[Homework assignment >>attach:SAE_Homework.pdf]](for intermediate and advanced levels)
207
208 **[[Register for the course>>url:https://weboodi.helsinki.fi/hy/opettaptied.jsp?html=1&OpetTap=101816052||shape="rect"]][[url:https://weboodi.helsinki.fi/hy/opettaptied.jsp?html=1&OpetTap=101818037||shape="rect"]]**
209
210 Did you forget to register? Please contact tilasto-info[at]helsinki.fi.
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