Training course on Survey Design and Sampling for Social Protection Research

Training Course on Survey Design and Sampling for Social Protection Research 

Introduction

Survey Design and Sampling for Social Protection Research is a foundational and indispensable discipline for generating reliable and representative data to inform the design, implementation, and evaluation of social protection programs. High-quality survey data is crucial for understanding the characteristics of vulnerable populations, assessing their needs, measuring program coverage and outcomes, and conducting rigorous impact evaluations. This course moves beyond basic data collection to equip participants with the advanced theoretical and practical tools necessary to design robust surveys and draw statistically sound samples that yield credible evidence. It recognizes that the integrity of social protection research hinges on meticulous survey design and appropriate sampling strategies.

Training Course on Survey Design and Sampling for Social Protection Research is meticulously designed to equip with the advanced theoretical insights and intensive practical tools necessary to excel in Survey Design and Sampling for Social Protection Research. We will delve into the foundational concepts of survey methodology and statistical inference, master the intricacies of questionnaire development, sampling frame construction, and various sampling techniques, and explore cutting-edge approaches to digital data collection, quality assurance, and ethical considerations. A significant focus will be placed on hands-on application, analyzing real-world complex social protection contexts, and developing tailored survey instruments and sampling plans. By integrating industry best practices, analyzing complex case studies, and engaging in intensive practical exercises, attendees will develop the strategic acumen to confidently lead and implement high-quality survey-based research, fostering unparalleled data validity, representativeness, and evidence credibility.

Course Objectives

Upon completion of this course, participants will be able to:

1. Analyze the fundamental concepts of survey methodology and its role in social protection research.
2. Comprehend the principles of statistical inference and the importance of representative samples.
3. Master the process of designing comprehensive questionnaires for social protection contexts.
4. Develop expertise in formulating effective survey questions for various indicators and sensitive topics.
5. Formulate strategies for pre-testing and piloting survey instruments for optimal quality.
6. Understand the critical role of sampling frames and their construction for social protection populations.
7. Implement robust approaches to various probability sampling techniques (e.g., SRS, stratified, cluster).
8. Explore key strategies for determining appropriate sample sizes and conducting power analysis.
9. Apply methodologies for ensuring data quality assurance and validation in survey data.
10. Understand and address ethical considerations and data privacy throughout the survey process.
11. Develop preliminary skills in managing fieldwork and training enumerators.
12. Design a comprehensive survey instrument and sampling plan for a social protection research study.
13. Examine global best practices and lessons learned in survey design and sampling for social protection.

Target Audience

This course is essential for professionals involved in designing and implementing surveys for social protection research:

1. Researchers & Academics: Specializing in social policy, economics, and development studies.
2. M&E Specialists: Designing and conducting large-scale evaluations.
3. Data Analysts & Statisticians: Involved in survey data collection and analysis.
4. Social Protection Program Managers: Needing to commission and interpret survey data.
5. Government Officials: From national statistical offices and social welfare ministries.
6. Development Practitioners: From NGOs and international organizations.
7. Consultants: Providing survey design and research services.
8. Survey Methodologists: Seeking to apply their expertise to social protection.

Course Duration: 10 Days

Course Modules

Module 1: Foundations of Survey Methodology in Social Protection Research

• Define survey methodology and its role in social protection research.
• Discuss the strengths and limitations of surveys for data collection.
• Understand the survey process: from design to data analysis and reporting.
• Explore different types of surveys (e.g., cross-sectional, panel, repeated cross-sectional).
• Identify key ethical principles in survey research.

Module 2: Principles of Statistical Inference and Sampling

• Comprehend the principles of statistical inference: generalization from sample to population.
• Understand the importance of representative samples and avoiding bias.
• Discuss key concepts: population, sample, sampling unit, sampling frame.
• Explore the relationship between sampling and external validity.
• Introduce different types of sampling error.

Module 3: Questionnaire Design: Core Principles

• Master the process of designing comprehensive and effective questionnaires.
• Understand the importance of clear objectives for each survey module.
• Learn to structure questionnaires logically and ensure smooth flow.
• Discuss different question formats (open-ended, closed-ended, scales).
• Explore best practices for questionnaire layout and formatting.

Module 4: Formulating Effective Survey Questions

• Develop expertise in formulating precise and unambiguous survey questions.
• Learn to avoid common pitfalls: leading questions, double-barreled questions, jargon.
• Understand techniques for measuring sensitive topics ethically.
• Discuss the use of recall periods and proxy respondents.
• Practice drafting questions for various social protection indicators.

Module 5: Pre-testing and Piloting Survey Instruments

• Formulate strategies for rigorous pre-testing and piloting of questionnaires.
• Understand the purpose of cognitive interviewing and field pre-tests.
• Learn to identify and address issues in question wording, flow, and understanding.
• Discuss how to refine survey instruments based on pilot findings.
• Plan for iterative testing cycles for optimal instrument quality.

Module 6: Sampling Frames and Their Construction 

• Understand the critical role of sampling frames in survey research.
• Learn to identify and assess existing sampling frames (e.g., census lists, administrative registries).
• Discuss methods for constructing new sampling frames when none exist.
• Explore challenges in sampling frame coverage and accuracy for social protection populations.
• Practice evaluating the suitability of different sampling frames.

Module 7: Probability Sampling Techniques

• Implement robust approaches to various probability sampling techniques.
• Master Simple Random Sampling (SRS) and its application.
• Learn about Stratified Sampling for improving precision and representation.
• Understand Cluster Sampling for efficiency in large-scale surveys.
• Discuss multi-stage sampling designs common in social protection.

Module 8: Sample Size Calculation and Power Analysis

• Explore key strategies for determining appropriate sample sizes.
• Understand the concepts of statistical significance, effect size, and power.
• Learn to calculate sample sizes for different research objectives (e.g., estimating means, comparing groups).
• Discuss the impact of design effects (from clustering) on sample size.
• Practice conducting power analysis for social protection studies.

Module 9: Non-Probability Sampling and its Limitations

• Understand non-probability sampling methods (e.g., convenience, snowball, quota sampling).
• Discuss when non-probability sampling might be used and its inherent limitations.
• Explore the challenges of making inferences from non-probability samples.
• Learn about techniques to mitigate bias in non-probability samples.
• Ethical considerations in using non-probability samples with vulnerable groups.

Module 10: Data Quality Assurance in Surveys

• Apply methodologies for ensuring high data quality in survey data.
• Learn about real-time data validation checks during collection.
• Discuss strategies for minimizing enumerator error and fraud.
• Understand data cleaning procedures and consistency checks.
• Explore techniques for triangulating survey data with other sources.

Module 11: Fieldwork Management and Enumerator Training

• Develop preliminary skills in effective fieldwork planning and management.
• Learn to recruit, train, and supervise survey enumerators effectively.
• Discuss best practices for enumerator conduct and ethical guidelines.
• Understand logistics for field deployment, safety, and data transmission.
• Address common fieldwork challenges and solutions in social protection.

Module 12: Ethical Considerations and Data Privacy in Surveys

• Understand and address ethical considerations throughout the survey process.
• Master the informed consent process for all survey participants.
• Understand principles of data privacy, confidentiality, and anonymity.
• Learn about data protection regulations (e.g., GDPR, national laws) and compliance.
• Discuss strategies for protecting vulnerable populations in surveys.

 

Training Methodology

• Interactive Workshops: Facilitated discussions, group exercises, and problem-solving activities.
• Case Studies: Real-world examples to illustrate successful community-based surveillance practices.
• Role-Playing and Simulations: Practice engaging communities in surveillance activities.
• Expert Presentations: Insights from experienced public health professionals and community leaders.
• Group Projects: Collaborative development of community surveillance plans.
• Action Planning: Development of personalized action plans for implementing community-based surveillance.
• Digital Tools and Resources: Utilization of online platforms for collaboration and learning.
• Peer-to-Peer Learning: Sharing experiences and insights on community engagement.
• Post-Training Support: Access to online forums, mentorship, and continued learning resources.

 

Register as a group from 3 participants for a Discount

Send us an email: info@datastatresearch.org or call +254724527104

Certification

Upon successful completion of this training, participants will be issued with a globally recognized certificate.

Tailor-Made Course

We also offer tailor-made courses based on your needs.

Key Notes

• Participants must be conversant in English.
• Upon completion of training, participants will receive an Authorized Training Certificate.
• The course duration is flexible and can be modified to fit any number of days.
• Course fee includes facilitation, training materials, 2 coffee breaks, buffet lunch, and a Certificate upon successful completion.
• One-year post-training support, consultation, and coaching provided after the course.
• Payment should be made at least a week before the training commencement to DATASTAT CONSULTANCY LTD account, as indicated in the invoice, to enable better preparation.