Weighting Methods & Strategies

Weighting Methods & Strategies

Weighting Methods & Strategies

23 Octubre–15 Diciembre 2023
El curso está disponible en English
Presentación del curso

Weighting is one of the major components in survey sampling. For a given sample survey, to each unit of the selected sample is attached a weight that is used to obtain estimates of population parameters of interest (e.g. means, totals, rates). The weighting process usually involves three steps: (i) obtain the design weights, which account for sample selection; (ii) adjust these weights to compensate for nonresponse; (iii) adjust the weights so that the estimates coincide to some population figures known from external trusted sources. The principle behind estimation in a probability survey is that each sample unit represents not only itself, but also several units of the survey population. The design weight of a unit usually refers to the average number of units in the population that each sampled unit represents. This weight is determined by the sampling method and is an important part of the estimation process. While the design weights can be used for estimation, most surveys produce a set of estimation weights by adjusting the design weights to improve accuracy of the final estimates. Once the final estimation weights have been calculated, they are applied to the sample data in order to compute estimates. The ILO Department of Statistics, in collaboration with the ITCILO, is proud to offer the Online course "Weighting Methods & Strategies". This course is directly linked to the course "Sampling Design: A Practical Approach" planned to take place in the spring of 2023 as both courses complement each other. Both courses are considered a learning journey that qualifies the learner to understand comprehensively Sampling design & weighting. Hence, attending both courses is strongly recommended for a fulfilling learning journey.

¿Quiénes participan en este curso?

Important Note: This course requires basic knowledge of statistics and probability! - It requires basic capacity to run procedures on statistical software using syntax (e.g. Stata do files, Spss syntax files, R scripts, Sas program files, etc.), and in particular with R3. The target audience includes: - Statisticians and practitioners from national statistical offices that have a role in designing household surveys samples.

Learning objectives

The main objective of the course is to “enhance understanding and capacities of ILO constituents and social partners to design household surveys and to process sample data in line with best methodological practices.” The course will enhance the knowledge of participants on the different weighting techniques highlighting their pros and cons through practical cases studies.

More specifically, the course aims to:

  • Enrich understanding of different weighting methods (i.e. post-stratification and calibration);
  • Provide insights about different weighting strategies, included the treatment of unit non-response;
  • Improve capacity to calculate final weights and precision of estimates;
  • Provide practical case studies on weighting sample data using either post- stratification or calibration making use of complex constraints using different sets of benchmarks available for different population sub-groups and/or for different geographical domains.
Online course content

Using a blended methodology of interactive PowerPoint presentation and case- studies, this course provides practical skills and tips to help participants understand how to calculate weights and precision of estimates. The course content includes the following:

  • Introduction of the course
  • Overview of household sample surveys
  • Frequency of data collection
  • Sample rotation
  • Wave Approach
  • Participants presenting themselves
  • Participants illustrating issues with sampling from around the globe (overview)
  • Design weights
  • Weighting methods
    • Post-stratification
    • Calibration
  • Weighting strategies
  • Introduction to the software R
  • Initial practice with R
  • Organizing folders and subfolders for processing sample data according to the GSBPM
  • Case studies on post-stratification using standard software
  • Introduction to the R package ReGenesees (for post-stratification and calibration)
  • Case studies on post-stratification using ReGenesees
  • Case studies on calibration using ReGenesees and adding several types of simultaneous benchmarks:
    • by sex and age-groups
    • at the national and regional level – for urban and rural areas
    • for national and non-nationals
  • Illustration of practical exercises for participants
  • Solution of practical exercises using ReGenesees
  • Questions and Answers
  • Case studies on calibration using ReGenesees in case of:
    • monthly allocation of quarterly sample for the production of monthly estimates – weekly allocation of quarterly sample
    • provisional monthly estimates
  • Illustration of practical exercises for participants
  • Solution of practical exercises using ReGenesees
  • Questions and Answers
  • Case studies on calibration using ReGenesees in case of:
    • integrated weights
    • wave approach (annual estimates from quarterly sub-samples)
  • Illustration of practical exercises for participants • Unit Non-Response
  • Analysis of unit non-response
  • Treatment of unit non-response
  • Case studies on calibration using ReGenesees for:
    • the treatment of non-response
    • the simultaneous treatment of non-response and the benchmark to population figures
  • Illustration of practical exercises for participants
  • Solution of practical exercises using ReGenesees
  • Questions and Answers
  • Quality Dimensions
  • Use of an R package to calculate standard errors and confidence intervals (for levels, ratios and rates) and design effect
  • Illustration of practical exercises for participants
  • Solution of practical exercises using ReGenesees
  • Questions and Answers
  • Closing session
Training methodology

The course is constructed as follows:

Lectures by experts

  • Sharing knowledge with participants around the various topics discussed in the course

Interactive exercises & case studies

  • Hands-on practical exercises and case studies on weighting and calculation of standard errors using the R package ReGenesees

The course will emphasize a unique learning approach:

Harnessing digital learning technology

  • Interactive online platform
  • Online Real-time feedback and support
  • Online forum discussions and interaction

Training methodology will combine

  • Expert presentations
  • Practical online exercises presented by experts
  • Practical exercises to be solved by participants
  • Knowledge sharing from participants
  • Group discussions

The course will take place from 23 October – 15 December 2023.


The course will be conducted in English.

Cost and financing

The course is fee-paying. The total cost is €1,500.

Payments and cancellations
  • Payments need to be received latest 14 days before the beginning of the course. Payment modalities will be communicated in the letter of acceptance. In the event of a cancellation, a participant may be substituted with another candidate. Cancellations remain free of charge if communicated latest 14 days prior to the start of the course.

  • For cancellations after this date, a penalty will be applied. For further information regarding payment, cancellation and refunds, please consult: Applications, payments, and cancellation

  • For information regarding payment, cancellation and refunds, please refer to the website: Applications, payments, and cancellation

How to apply?

To register, kindly fill in and submit the online registration form available through this link: https://oarf2.itcilo.org/DST/A9716615/en

The selection of applicants will be based on the submission of:

  • Demonstration of capacity and experience regarding the basic knowledge of statistics and probability
  • A completed online registration form
  • An official sponsorship letter issued by their organization (or donor organization),

Kindly note that we need to receive the above-mentioned documents in order to register you for the course!

We strongly recommend applying early since admission is competitive and space is limited!

Deadline for application

The deadline for applications is 9 October 2023.

  • Administrative arrangements can be coordinated through the following email (lmstats@itcilo.org);

  • For the technical coordination, please also be in contact with the ITCILO programme officer Mr. Mostafa Mohamed (m.mohamed@itcilo.org).

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