Panel Data Analysis and Multi-level Modeling using Stata
Dashen bank Staff
(December 25-27, 2017, Addis Ababa)
Training materials
1. Stata reference manuals
c. Statistics with Stata (Book)
2. Data sets
4. Lecture slides, (To be uploaded)
Basics on SAS @AAU Statistics Students
(October 26, 2017, Addis Ababa)
1. Training lecture slide (removed)
2. SAS codes, click here(removed)
3. Reference material,
Quality Management @ METEC
(August 28-31, 2017, Addis Ababa)
1. To download Minitab software clickhere
2. Lecture slides - Removed
3. Group projects - Removed
4. Additional Notes on sampling and report writing, Removed
4. Additional Notes on sampling and report writing, Removed
STATA Training for CSA Staffs
( August, 2017, Bahirdar)
1. To download the training slide click here (Removed)
2. To download datasets for the training CLICKHERE (Removed)
3. To get upto date information about STATA from STATA website click here
4. To see STATA detailed manual click here.
2. To download datasets for the training CLICKHERE (Removed)
3. To get upto date information about STATA from STATA website click here
4. To see STATA detailed manual click here.
STATA Training for CSA Staffs
( June, 2017, Addis Ababa)
1. To download the training slide click here (Removed)
2. To download datasets for the training CLICKHERE
3. To get upto date information about STATA from STATA website click here
4. To see STATA detailed manual click here.
2. To download datasets for the training CLICKHERE
3. To get upto date information about STATA from STATA website click here
4. To see STATA detailed manual click here.
SPSS Training for METEC Staffs
To download the training slide click here (Removed)
To download basic theory slide click here (Removed)
To download basic theory slide click here (Removed)
SAS Training for Health Professionals
(From August 24-29,2016)
Data set and Codes for Practice
- To download Titanic dataset, click here (removed)
- To download training codes, click here (To be uploaded)
Reading Materials
Basics on SPSS for ESA Trainee's
(From August 23-30,2016)
Lecture Slides
- To download day 1 lecture click here (removed)
Training on Mixed Models using SAS and R
Training Objectives:
At the end of the training, trainees are
expected to understand how mixed models are fitted using SAS, and R. Specifically, the training
aims:
-
To introduce the Linear Mixed model and some key
theories
-
To learn what types of data are appropriate for
LMM analysis
-
To explain the important statistical concepts
involved in mixed models
-
To learn how to set up Proc Mixed syntax ,
and lme & lmer functions to fit LMMs
for d/t types of data using SAS & R
-
To interpret output from Proc Mixed, and lme and
lmer functions
-
To understand Model-Building, Model
Selection and Model Diagnostics Strategies
-
To get diagnostic tools, perform different graphics in R
Pr-request
¨
Good understand on the basics of linear statistical modeling
¨
Basic understanding of SAS and R
¨
Install SAS and R on your PC
¨
Install nlme and lme4 packages
Downloads:
1. To download Different R packages, CLICK HERE
2. To install the current Version of R, CLICK HERE
3. To install RStudio, CLICK HERE
Lecture Slides
1. To download day 1 lecture slide: click here
2. To download day 2 lecture slide: Click here (to be uploaded)
Data Sets
- To download datasets used during the training, click hereBasics on SAS Trianing for Policy Study and Research Center Staffs
Basic Introductory Notes
1. SAS short introductory brief
2. Basic short notes on SAS
SAS Data Sets for Practice
- Data set one (Soil data-For ANOVA model) -Click Here
- Data set two (Weight data- For Regression model )- Click Here
- Training Slide-Click Here
- SAS codes -Click Here
-SAS code 2- Click Here
- Linear Statistical modeling- Click Here
- Data set two (Weight data- For Regression model )- Click Here
- Training Slide-Click Here
- SAS codes -Click Here
-SAS code 2- Click Here
- Linear Statistical modeling- Click Here
Reading Materials on SAS
SPSS training for Leadership management
Training Materials
1. SPSS training manual
2. Introduction to Basic statistics
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