Analysis of Complex Sample Survey Data using Stata

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

10 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.

COURSE LEVEL:

Register for the course


Face to Face Schedules By Location
Nairobi Schedules:
Code Date Duration Location Fees
ACS001 6 Mar 2023 - 17 Mar 2023 10 days Nairobi, Kenya KES 150,000 | USD 2,200 Register
ACS001 6 Feb 2023 - 17 Feb 2023 10 days Nairobi, Kenya KES 150,000 | USD 2,200 Register
ACS001 3 Apr 2023 - 14 Apr 2023 10 days Nairobi, Kenya KES 150,000 | USD 2,200 Register
ACS001 1 May 2023 - 12 May 2023 10 days Nairobi, Kenya KES 150,000 | USD 2,200 Register
ACS001 5 Jun 2023 - 16 Jun 2023 10 days Nairobi, Kenya KES 150,000 | USD 2,200 Register
ACS001 3 Jul 2023 - 14 Jul 2023 10 days Nairobi, Kenya KES 150,000 | USD 2,200 Register
ACS001 7 Aug 2023 - 18 Aug 2023 10 days Nairobi, Kenya KES 150,000 | USD 2,200 Register
ACS001 4 Sep 2023 - 15 Sep 2023 10 days Nairobi, Kenya KES 150,000 | USD 2,200 Register
ACS001 2 Oct 2023 - 13 Oct 2023 10 days Nairobi, Kenya KES 150,000 | USD 2,200 Register
ACS001 6 Nov 2023 - 17 Nov 2023 10 days Nairobi, Kenya KES 150,000 | USD 2,200 Register
ACS001 4 Dec 2023 - 15 Dec 2023 10 days Nairobi, Kenya KES 150,000 | USD 2,200 Register
Kigali Schedules:
Mombasa Schedules:
Nakuru Schedules:
Kisumu Schedules:
Naivasha Schedules:
Virtual Trainer Led Schedules
Contact Us on (+254) 715 077 817 / (+254) 792 516 000 or email us [email protected] for a virtual schedule.
E-Learning

Contact Us on (+254) 715 077 817 / (+254) 792 516 000 or email us [email protected] for E-Learning course.


  • Enhance Survey estimation and inference for complex designs
  • Determine Sampling error calculation models; ultimate clusters
  • Sampling error estimation for descriptive statistics
  • Replication Methods for Variance Estimation

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.

Course Administration Details:

ACCREDITATION

Upon successful completion of this training, participants will be issued with an Indepth Research Institute (IRES) certificate certified by the National Industrial Training Authority (NITA).

TRAINING VENUE

The training will be held at IRES Training Centre. The course fee covers the course tuition, training materials, two break refreshments and lunch.

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

ACCOMMODATION AND AIRPORT PICKUP

Accommodation and airport pickup are arranged upon request. For reservations contact the Training Officer.

Email:[email protected].  

Mob: +254 715 077 817/+250789621067

TAILOR- MADE

This training can also be customized to suit the needs of your institution upon request. You can have it delivered in our IRES Training Centre or at a convenient location.

For further inquiries, please contact us on Tel: +254 715 077 817/+250789621067.

Mob: +254 792516000+254 792516010 ,or mail [email protected]/[email protected]

PAYMENT

Payment should be transferred to IRES account through bank on or before start of the course

Send proof of payment to [email protected]/[email protected]


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# Job Title Organisation Country
1 PRINCIPAL HUMAN RESOURCE PLANNING AND DEVELOPMENT OFFICER Ministry of Labour, National Human Resource Planning and Development Department Kenya
2 PRINCIPAL HUMAN RESOURCE PLANNING AND DEVELOPMENT OFFICER Ministry of Labour, National Human Resource Planning and Development Department Kenya
3 PRINCIPAL HUMAN RESOURCE PLANNING AND DEVELOPMENT OFFICER Ministry of Labour, National Human Resource Planning and Development Department Kenya
4 PRINCIPAL HUMAN RESOURCE PLANNING AND DEVELOPMENT OFFICER Ministry of Labour, National Human Resource Planning and Development Department Kenya
5 PRINCIPAL HUMAN RESOURCE PLANNING AND DEVELOPMENT OFFICER Ministry of Labour, National Human Resource Planning and Development Department Kenya