Analysis of Complex Sample Survey Data using Stata Course in Nairobi, Kenya

INTRODUCTION

Standard courses on statistical analysis assume that survey data arise from a simple random sample of the target population. Little attention is given to characteristics often associated with survey data, including missing data, unequal probabilities of selection, stratified multistage sample designs, and measurement errors. Most standard statistical procedures in software packages commonly used for data analysis (e.g. SAS, SPSS, and Stata) do not allow the analyst to take these properties of survey data into account unless specialized survey procedures are used. Failure to do so can have an important impact on the results of all types of analyses, ranging from simple descriptive statistics to estimates of parameters of multivariate models.

This course provides an introduction to specialized software procedures that have been developed for the analysis of complex sample survey data including testing for between-group differences in means and proportions, regression analysis, logistic regression and multilevel modeling. We will also consider the consequences of non response and missing data on survey analysis and methods for dealing with missing data. Specialized procedures for survey data analysis from the Stata systems for data management and analysis will be used to develop course examples and exercises

DURATION

5 Days

WHO SHOULD ATTEND?

The course does not require rigorous training in mathematics; however, proficiency in basic mathematics, including algebra and functions, is essential. Survey sampling methods and a basic understanding of sampling concepts such as stratification, cluster sampling and weighting is required. Participants should also have familiarity with basic statistical concepts, including point estimates, sampling variance, confidence intervals, p-values, the maximum likelihood method of estimation and simple linear and logistic regression models.

How to register:
To register, send an email to: [email protected] You can also visit our website on www.opencastlabs-africa.com  and fill an online application form and submit to us.

February 10th - 14th 2020
Register Individual: https://cutt.ly/GrQr9E3
Register Group: https://cutt.ly/hrQr3ob

March 23rd - 27th 2020
Register Individual: https://cutt.ly/hrQr39R
Register Group: https://cutt.ly/GrQr7eI

View Related Courses: http://opencastlabs-africa.com/data-collection-and-analysis/

Contact Details:

Rwanda:

P.O Box 4543 Kigali

3rd Floor La Bonne Address House

Avenue de la Revolution

Tel: Kigali +250 788 470 532

The Training Coordination Office (Joab/Diana)
Capacity Building Division
Argwings Kodhek Road, opposite YAYA Center
P.o Box 30225 – 00100 , Nairobi, Kenya
Tel: +254 0204409651   Mobile: +254 723870644
Email : [email protected]

Language

Participants should be reasonably proficient in English.

Fee Exceptions

All international participants will cater for their, travel expenses, visa application, insurance, accommodation and other personal expenses.

Accommodation

Accommodation is arranged upon request. For reservations contact us below.

Email: [email protected]

Payment:

Payment should be transferred through bank 5 days before commencement of training.

Cancellation policy

• All requests for cancellations must be received in writing.
• Changes will become effective on the date of written confirmation being received.
• The appropriate cancellation charge will apply

TOPICS COVERED

• Survey estimation and inference for complex designs
  • Complex sample designs, survey estimation and inference
  • Multi-stage designs, stratification, cluster sampling, weighting, item missing data, finite population corrections
  • Models and assumptions for inference from complex sample survey data
  • Sampling distributions, confidence intervals
  • Design effects.
• Sampling error calculation models; ultimate clusters
• Sampling error estimation for descriptive statistics
• Replication Methods for Variance Estimation
• Estimation and inference for special statistics (percentiles, indices)
• Methods for Categorical Data
• Linear Regression Analysis
• Logistic Regression Analysis
• Multinomial, ordinal logistic regression
• Poisson and negative binomial regression
• Survival analysis and event history analysis
• Multiple imputation inference for survey data
• Multi-level models for complex sample survey data.

The 5 day course costs 750$ (75,000 KES), The Cost includes all training fees, materials, lunch and refreshments as well as certificates and 6 month post training support.