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<!DOCTYPE html>
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<head>
<meta charset="utf-8">
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<title>Protection Assessment Toolkit</title>
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<h1>
Guidelines and Templates <br>
</h1>
<h2>
to facilitate assessment planning and design<br> and to support the “technical” implementation of existing guidances
</h2>
<p>
Last update : 7 May 2017
</p>
</div>
<div id="presentation" class="section level2">
<h2>Why a “Protection Assessment Toolkit”?</h2>
<p>The kit is a comprehensive set of tools to guide survey teams through every step of a protection assessment based on <strong>Household survey</strong> – from overall planning, design and data collection in the field to data processing, analysis, interpretation, documentation and dissemination. Becausse it addresses the specific challenges related to household surveys, it fits more for protracted situations and it <strong>complements</strong> other approaches such as the <a href="http://www.unhcr.org/450e963f2.html">UNHCR Tool for Participatory Assessment in Operations</a>, the <a href="https://emergency.unhcr.org/entry/50209">Needs Assessment for Refugee Emergencies (NARE) Checklist</a> for Refugees operations and the <a href="http://www.globalprotectioncluster.org/en/tools-and-guidance/information-and-data-management.html">Rapid Protection Assessment Tools (RPAT)</a> for IDPs operations. The kit is also organised to ensure that all findings and recommandation will allow to inform prioritisation between all potential protection activities and subsequent ressources allocation in terms of programme, through the following elements :</p>
<ul>
<li>Produce <strong>impact indicators</strong> that are used to assess the conditions of beneficiaries over time;</li>
<li>Support the <strong>analysis of vulnerabilites</strong> and the discovery of clusters of individuals with similar profile;</li>
<li>Allow for the development of <strong>targetting models</strong> for both response (for instance cash) and prevention activities (for instance protection);</li>
<li>Provide basis for <strong>public advocacy</strong> on issues faced by the population group.</li>
</ul>
<div class="figure">
<img src="images/process.png">
</div>
<p>This toolkit supports the technical implementation of already existing guidelines and guidances, namely the <a href="http://gbvguidelines.org/">Guidelines for Integrating Gender-Based Violence Interventions in Humanitarian Action</a>, the <a href="http://www.globalprotectioncluster.org/_assets/files/tools_and_guidance/info_data_management/CPRA_English-EN.pdf">Child Protection Rapid Assessment Toolkit</a>, the <a href="http://jet.jips.org/">Joint IDP Profiling Service Essential Toolkit- JET</a>, the <a href="http://unhcr.org/4aa76c279.pdf">Heightened Risk Identification Tool</a>, The <a href="http://www.cashlearning.org/downloads/operational-guidance-and-toolkit-for-multipurpose-cash-grants---web.pdf">Operational Guidance and Toolkit for Multipurpose Cash Grants</a> etc. The proposed technical implementation approach was inspired by the <a href="http://sens.unhcr.org">UNHCR Standardised Expanded Nutrition Survey</a> and the <a href="http://mics.unicef.org/tools">UNICEF Multiple Indicator Cluster Surveys</a>.</p>
</div>
<div id="why-technical" class="section level2">
<h2>Why “technical”?</h2>
On the top of the summary narrative guidelines below, the toolkit is organised around 4 keys technical componnents that facilitate the easy replication and customisation of an assessment from an operation to another. Re-using tested proofed platforms, questions & report format, technical staff in charge will save significant amount of time.
<div class="note">
<ul>
<li><p>A pre-organised <kbd><a href="https://docs.google.com/spreadsheets/d/1zGnaLXouP9vTfjqVvUVOSfzeSkvpd63f8Z-zvqGJtNU">XLSFORM Questions Library</a></kbd> in order to leverage good practices and enforce core questions during design of the assessment form.</p></li>
<li><p>A <kbd><a href="hhtps://kobo.unhcr.org">KoboToolBox</a></kbd> secured server to perform the data collection. This server uses the xlsform developed during the design phase.</p></li>
<li><p>Multiple <kbd><a href="https://github.com/unhcr-mena/protection-assessment-toolkit">R statistical analysis scripts</a></kbd> to clean & analyse data, and then to generate automatically standard report and to facilitate the creation of presentation slides and infographics.</p></li>
<li>A series of <kbd><a href="https://github.com/unhcr-mena/protection-assessment-toolkit">Github Repository</a></kbd> to exchange collaboratively analysis between operations and generate a knowledge base. Github is also used for the maintenance of the toolkit itself.</li>
</ul>
</div>
</div>
<div id="for-whom" class="section level2">
<h2>For whom?</h2>
<p>The targeted audience of the toolkit are <em>technical staff tasked to work on a protection assessment</em>: assessment focal points, information management officers and data scientists… The toolkit is to be used once all emergency assessment and secondary data review have been implemented and developped. With a bit of configuration at the begining, the toolkit will allow for the quick generation of results and will ensure that minimum data quality standards are enforced. In addition, because of the standard data format that are enforced through the kit, it will be possible to obtain comparable results from different operations.</p>
<div class="alert alert-warning" style="font-weight: bold;">
<h2 id="disclaimer">Disclaimer</h2>
<p>
The toolkit is a <em>collaborative effort</em>: if you have suggestions, please share them <a href="https://github.com/unhcr-mena/protection-assessment-toolkit/issues" style="color: white;">through this link</a>.
</p>
<p>
The Toolkit is a <em>work in progress</em>: if you identify issues, please share them <a href="https://github.com/unhcr-mena/protection-assessment-toolkit/issues" style="color: white;">through this link</a>.
</p>
</div>
</div>
<div id="tdm" class="section level2">
<h2>Table of Content</h2>
<div id="assessment-methodology-form-design" class="section level3">
<h3>Assessment methodology & form design</h3>
<div class="row">
<div class="col-md-4">
<p>
<strong>Planning</strong>
</p>
<div class="list-group">
<p><a href="#Assessment-Project-Document" class="list-group-item">Assessment Project Document</a> <a href="#Memorandum-of-Understanding" class="list-group-item">Memorandum of Understanding</a> <a href="#Terms-of-Reference-for-Assessment-Focal-Point" class="list-group-item">Terms of Reference for Assessment Focal Point</a></p>
</div>
</div>
<div class="col-md-4">
<p>
<strong>Methodology</strong>
</p>
<div class="list-group">
<p><a href="#Sampling" class="list-group-item">Sampling</a> <a href="#Interview" class="list-group-item">Interview approach</a> <a href="#Pre-Assessment" class="list-group-item">Pre-Assessment</a></p>
</div>
</div>
<div class="col-md-4">
<p>
<strong>Form</strong>
</p>
<div class="list-group">
<p><a href="#protection-Topics" class="list-group-item">Protection Topics</a> <a href="#Module-questions" class="list-group-item">Questions Modules</a> <a href="#Guidelines-for-Customisation" class="list-group-item">Guidelines for Customisation</a></p>
</div>
</div>
</div>
</div>
<div id="data-collection" class="section level3">
<h3>Data collection</h3>
<div class="row">
<div class="col-md-4">
<p>
<strong>Preparing for fieldwork</strong>
</p>
<div class="list-group">
<p><a href="#Fieldwork-Training-Agenda" class="list-group-item">Fieldwork Training and Agenda</a> <a href="#Pre-test-Phase" class="list-group-item">Pre-test Phase</a> <a href="#Managing-Devices" class="list-group-item">Managing Devices</a></p>
</div>
</div>
<div class="col-md-4">
<p>
<strong>Fieldwork manual</strong>
</p>
<div class="list-group">
<p><a href="#Instructions-for-Interviewers" class="list-group-item">Instructions for Interviewers</a> <a href="#Instructions-for-Supervisors-Editors" class="list-group-item">Instructions for Supervisors and Editors</a> <a href="#Instructions-for-Managers" class="list-group-item">Instructions for Managers</a></p>
</div>
</div>
<div class="col-md-4">
<p>
<strong>Using KoboToolBox</strong>
</p>
<div class="list-group">
<p><a href="#Data-Protection-Impact-Assessment" class="list-group-item">Data Protection Impact Assessment</a> <a href="#Server-Configuration" class="list-group-item">Server Configuration</a> <a href="#Data-Entry" class="list-group-item">Data Entry</a></p>
</div>
</div>
</div>
</div>
<div id="analysis-dissemination" class="section level3">
<h3>Analysis & dissemination</h3>
<div class="row">
<div class="col-md-4">
<p>
<strong>Analysis Steps</strong>
</p>
<div class="list-group">
<p><a href="#Discover" class="list-group-item">Discover</a> <a href="#Predict" class="list-group-item">Predict</a> <a href="#Advise" class="list-group-item">Advise</a></p>
</div>
</div>
<div class="col-md-4">
<p>
<strong>Report</strong>
</p>
<div class="list-group">
<p><a href="#Analysis-Script" class="list-group-item">Analysis Scripts</a> <a href="#Model-for-Key-Findings-Report" class="list-group-item">Model for Key Findings Report</a> <a href="#Model-for-Final-Report" class="list-group-item">Model for Final Report</a></p>
</div>
</div>
<div class="col-md-4">
<p>
<strong>Communication</strong>
</p>
<div class="list-group">
<p><a href="#Slides-Infographics" class="list-group-item">Slides & Infographics</a> <a href="#Microdata" class="list-group-item">Sharing microdata for social scientist</a></p>
</div>
</div>
</div>
</div>
<div id="credits" class="section level3">
<h3>Credits</h3>
<p>Large parts of the toolkit are extracted from other existing guidelines referenced above.</p>
</div>
</div>
</article>
<article id="Assessment-Project-Document"><div class="fluid-row" id="Assessment-Project-Document_header">
<h1 class="title toc-ignore">Assessment Project Document</h1>
</div>
<div class="TOC">
<ul>
<li><a href="#Assessment-Project-Document_background-and-objective">Background and Objective</a></li>
<li><a href="#Assessment-Project-Document_governance-structure">Governance Structure</a></li>
<li><a href="#Assessment-Project-Document_questionnaires-content">Questionnaires Content</a></li>
<li><a href="#Assessment-Project-Document_sample-design">Sample Design</a></li>
<li><a href="#Assessment-Project-Document_recruitment-and-training-of-fieldwork-staff">Recruitment and Training of Fieldwork Staff</a></li>
<li><a href="#Assessment-Project-Document_fieldwork">Fieldwork</a></li>
<li><a href="#Assessment-Project-Document_budget">Budget</a></li>
<li><a href="#Assessment-Project-Document_timeline-for-tasks">Timeline for Tasks</a></li>
</ul>
</div>
<div class="note">
<p>A protection Assessment needs to be carefully planned. The First step of this plan is to document all the elements of the Asesssement</p>
</div>
<div id="Assessment-Project-Document_background-and-objective" class="section level2">
<h2>Background and Objective</h2>
<p>Protection Assessment are designed to collect statistically sound, internationally comparable estimates of key indicators and analysis that are used to assess the protection situation of displaced persons (Refugees & IDP’s) and to prioritize protection intervention.</p>
</div>
<div id="Assessment-Project-Document_governance-structure" class="section level2">
<h2>Governance Structure</h2>
<ul>
<li>Give the name and type (government agency or other agency) of implementing agency.</li>
<li>Provide overview of Memorandum of Understanding (MoU) (Parties, critical components affecting survey planning, etc)</li>
<li>Give the names and affiliations of those who will be responsible for the management, technical work, and coordination activities. Include the survey coordinator, the sampling expert, and data processing expert assigned from the implementing agency, as well as others, if applicable. If already identified, the UNICEF MICS Consultant and other key regional experts/consultants together with their respective responsibilities should also be included.</li>
<li>Describe the roles and contributions of national and international stakeholders and funding agencies.</li>
<li>Describe the status, composition and roles and responsibilities of the Steering and Technical committees.</li>
<li>Provide other details on the governance structure and human resources as needed</li>
</ul>
</div>
<div id="Assessment-Project-Document_questionnaires-content" class="section level2">
<h2>Questionnaires Content</h2>
<p>List the excluded modules and provide reasons for the exclusion of each module. If the module or questions are not applicable to the country/survey you are not expected to provide a detailed explanation. However, for other exclusions, please include specific details about the reasons the modules and/or the questions that are not planned to be included and provide references to the data needs assessment.</p>
<p>Provide information on the plans for the translation and back-translation of the questionnaires into local languages and plans for pre-testing the questionnaires. Indicate that the pre-test results will be compiled in a report, and that the results of the pre-test will be used to further modify, customize, and finalize the questionnaires.</p>
</div>
<div id="Assessment-Project-Document_sample-design" class="section level2">
<h2>Sample Design</h2>
<p>In this section, under separate sub-headings, as appropriate, describe:</p>
<ul>
<li>The Type of sampling design shoudl be stated (Rationale for sampling design explained)</li>
<li>State definition of Household used in the assessment</li>
<li>Sample size, including the expected numbers of households, women, men and under-5s. Include information on sub-sampling of men, if applicable</li>
<li>How the sample size was calculated, including the indicators used for the calculation of the sample size</li>
<li>The level of disaggregation sought for reporting</li>
<li>What sample frame will be used and if the sample frame needs to be updated, plans for mapping, listing and household selection</li>
</ul>
</div>
<div id="Assessment-Project-Document_recruitment-and-training-of-fieldwork-staff" class="section level2">
<h2>Recruitment and Training of Fieldwork Staff</h2>
<p>In this section, under separate sub-headings as appropriate, describe:</p>
<ul>
<li>Plans for recruitment of fieldwork staff, including details of the type of personnel (interviewers, data entry, supervisors, measurers, data entry clerks), their education/background, sex, numbers etc.</li>
<li>Timing of training</li>
<li>Length of training</li>
<li>Methodology and content of training</li>
<li>Profiles of trainers</li>
<li>How training will be organized – central location, in separate districts, including how standardization will be ensured if not central location</li>
</ul>
</div>
<div id="Assessment-Project-Document_fieldwork" class="section level2">
<h2>Fieldwork</h2>
<p>In this section, under separate sub-headings as appropriate, describe:</p>
<ul>
<li>Timing of fieldwork, constraints on timing of fieldwork</li>
<li>Team composition, including numbers</li>
<li>Expected duration of fieldwork and how the duration was calculated</li>
<li>Plans for monitoring data collection and fieldwork supervision as well as plans for handling questionnaires for data entry</li>
<li>Fieldwork logistics</li>
</ul>
</div>
<div id="Assessment-Project-Document_budget" class="section level2">
<h2>Budget</h2>
<p>In this section, under separate sub-headings as appropriate, describe:</p>
<ul>
<li>Expected total cost of the survey</li>
<li>Breakdown of total cost by budget line items</li>
<li>Amount of funding secured and funding source(s)</li>
<li>Amount of extra funding needed, including plans, if any, on how the funding shortfall will be secured</li>
</ul>
</div>
<div id="Assessment-Project-Document_timeline-for-tasks" class="section level2">
<h2>Timeline for Tasks</h2>
<ul>
<li>Identify survey coordinator, survey personnel, and plan survey; establish steering and technical committees</li>
<li>Adapt and pre-test questionnaires; translate questionnaires and manuals</li>
<li>Carry out sampling and household listing; order scales, boards, salt test kits, and GPS equipment</li>
<li>Complete logistical arrangements</li>
<li>Select and train fieldwork personnel (interviewers, editors, measurers, and supervisors)</li>
<li>Conduct pilot study and collect data</li>
<li>Complete data processing, including secondary editing</li>
<li>Prepare summary findings report and final report, and disseminate widely; prepare survey archive</li>
</ul>
</div>
</article>
<article id="Memorandum-of-Understanding"><div class="fluid-row" id="Memorandum-of-Understanding_header">
<h1 class="title toc-ignore">Memorandum of Understanding</h1>
</div>
<div class="TOC">
<ul>
<li><a href="#Memorandum-of-Understanding_implementation-model">Implementation Model</a></li>
<li><a href="#Memorandum-of-Understanding_field-level-memorandum-of-understanding">Field Level Memorandum of Understanding</a></li>
</ul>
</div>
<div class="important">
<p>Whether it is for the data collection or the analysis, protection assessment are often done in partnership. To avoid confusion and misunderstnading within the proces, it is recommended to establish a clear Memorandum of Understanding</p>
</div>
<div id="Memorandum-of-Understanding_implementation-model" class="section level2">
<h2>Implementation Model</h2>
<p>According to the particular context, the assessment might be implemented using une of the following models :</p>
<ul>
<li>Assigning full data collection responsibility to different agencies in different geographic areas</li>
<li>Pooling human and logistical resources centrally</li>
<li>Delegating data collection responsibilities to one or more NGO partners, ideally local NGOs, through a project agreement.</li>
</ul>
<p>Regardless of the model chosen, it is important to observe four principles:</p>
<ul>
<li>The objectives and methodology of the asessment need to be decided by consensus among particpant. Agencies who assume particular data collection responsibilities do not acquire a privileged say in choosing indicators, sites or data collection methods.<br>
</li>
<li>Particpant contribute resources to the implementation of the asessment, to the measure of their capacities and possibilities.<br>
</li>
<li>Common standards and understanding of assessment questions need to be agreed and maintained.<br>
</li>
<li>Clear focal points need to be appointed per each particpating organisation with operational responsibility for data collection.</li>
</ul>
</div>
<div id="Memorandum-of-Understanding_field-level-memorandum-of-understanding" class="section level2">
<h2>Field Level Memorandum of Understanding</h2>
<p>The following is an outdated example that might provide some inspiration for the inital drafting of the memorandum. Any memorandum needs to be cleared by the Bureau before signature.</p>
<div id="Memorandum-of-Understanding_scope-of-works" class="section level4">
<h4>Scope of Works</h4>
<p>The following is an example of MoU.</p>
<blockquote>
<ul>
<li><p>The following Memorandum of Understanding between the United Nations High Commissioner for Refugees and <kbd>Partner Name</kbd> is not attempt to repeat the basic principles of already existing global MOU, including descriptions of the agency responsibilities towards various populations, but will instead highlight the specific areas where close cooperation will be taking place.</p></li>
<li><p>This MoU covers the geographic Coverage for <kbd>population group</kbd>. All areas will be covered based on <kbd>sampling methodology</kbd></p></li>
<li><p>UNHCR and <kbd>Partner Name</kbd> will agree on a joint questionnaire subsequently used for all data collection related to the profiling exercise, through mobile data collection devices and a <kbd>methodlogy</kbd> (for instance: combination data collection methodologies: direct observation, key informant interviews and as means of triangulation in areas with a high concentration of <kbd>population group</kbd>, carry out Focus Group Discussions).</p></li>
<li><p>All data collectors will be selected jointly and need to sign the code of conduct. They will receive a ½ day training on the principles and objectives of the code of conduct. In addition, data collectors will be trained at a minimum in: interviewing techniques, protection principles, data protection (confidentiality, informed consent etc.), referral mechanism, usage of mobile devices, the questionnaire, and basic security principles. This introductory training will be conducted before any data collection takes place and will last 3 to 4 days. One day of field testing with the data collectors is foreseen at the beginning of the roll-out. Technical documentation of the profiling exercise will include: data collectors manual, team leader manual, data analysis plan, data entry manual and the respective Standard Operating Procedures for the project.</p></li>
<li><p>The role of the Government from the beginning of this exercise is crucial to ensure a responsible handover at the end of the project and overall ownership by the Government. To this end, the Government will be included in the project through training and in particular Line Ministries in the localities to contribute to data collection.</p></li>
<li><p>The questionnaire will be presented to and feedback sought from partners (UN, NGOs and Government) to achieve buy-in and ensure that the questionnaire meets the information needs of partners providing protection and assistance to <kbd>population group</kbd>; however, given the need for timely information delivery, contributions from partners are expected to be provided within a week from the day they receive the draft questionnaire.</p></li>
<li><p>UNHCR and <kbd>Partner Name</kbd> will have joint data ownership. The data will be stored on a UNHCR server, while UNHCR and <kbd>Partner Name</kbd> will have both administrative rights to access the data base. UNHCR and <kbd>Partner Name</kbd> will disseminate and/or publish the data collected jointly. None of them will be producing the data alone to publish products /reports /websites etc. under its own logo or other branding.. The design and layout of all information products of this project will be agreed jointly. Data collection will be an ongoing exercise to ensure that information is updated, relevant and timely. At the end of the project the data will be handed over to the Government.</p></li>
<li><p>UNHCR and <kbd>Partner Name</kbd> will establish a joint budget and enter into a cost-sharing arrangement to finance this project.</p></li>
<li><p>In line with UNHCR’s mandate for refugees, UNHCR will be collecting data on refugees residing outside camps which is not part of this MoU.</p></li>
<li><p>Nothing in this MOU shall affect the relations of either signatory to its Governing Body, nor the contractual relationship and administrative supervision of UNHCR and <kbd>Partner Name</kbd> to their operational partners.</p></li>
<li><p>The implementation of the MOU will be in compliance with the respective administrative and financial rules and procedures of UNHCR and <kbd>Partner Name</kbd> and be subject to the availability of funds.</p></li>
<li><p>This MOU will enter into force upon signature and shall be of indefinite duration.</p></li>
<li><p>This MOU may be terminated by either party upon 90 days written notice.</p></li>
<li><p>This MOU may be modified at any time by mutual consent of the parties.</p></li>
<li><p>The Representatives of both organizations will meet when necessary to discuss policy issues and will nominate officers to meet regularly to review strategic and implementation issues of particular interest to both organizations and to propose possible courses of action to address them.</p></li>
</ul>
</blockquote>
</div>
</div>
</article>
<article id="Terms-of-Reference-for-Assessment-Focal-Point"><div class="fluid-row" id="Terms-of-Reference-for-Assessment-Focal-Point_header">
<h1 class="title toc-ignore">Terms of Reference for Assessment Focal Point</h1>
</div>
<div class="TOC">
<ul>
<li><a href="#Terms-of-Reference-for-Assessment-Focal-Point_background">Background</a></li>
<li><a href="#Terms-of-Reference-for-Assessment-Focal-Point_methodology">Methodology</a></li>
<li><a href="#Terms-of-Reference-for-Assessment-Focal-Point_objectives">Objectives</a></li>
<li><a href="#Terms-of-Reference-for-Assessment-Focal-Point_deliverables">Deliverables</a></li>
<li><a href="#Terms-of-Reference-for-Assessment-Focal-Point_reporting">Reporting</a></li>
<li><a href="#Terms-of-Reference-for-Assessment-Focal-Point_time-frame">Time frame</a></li>
<li><a href="#Terms-of-Reference-for-Assessment-Focal-Point_qualification-experience-required">Qualification & Experience required</a></li>
</ul>
</div>
<div id="Terms-of-Reference-for-Assessment-Focal-Point_background" class="section level2">
<h2>Background</h2>
<p>Insert</p>
<ul>
<li>background on current protection situation,</li>
<li>details on previous assessment or what is known of the protection situation.</li>
</ul>
<p>Explain why the current assessment is planned and if there is a specific trigger that would indicate a situation change.</p>
<p>Insert any other relevant detail.</p>
</div>
<div id="Terms-of-Reference-for-Assessment-Focal-Point_methodology" class="section level2">
<h2>Methodology</h2>
<p>The survey will be developed using the Protection Assessment Toolkit. Survey methodology should be reviewed by UNHCR regional or HQ Protection Infornmatiuon Management Officer prior to data collection.</p>
</div>
<div id="Terms-of-Reference-for-Assessment-Focal-Point_objectives" class="section level2">
<h2>Objectives</h2>
<p>The Assessment Focal Point will oversee the Protection Assessment for: - <kbd>Operation</kbd> - <kbd>Population Group</kbd> - <kbd>Geographic Coverage</kbd> - <kbd>Timeframe</kbd></p>
</div>
<div id="Terms-of-Reference-for-Assessment-Focal-Point_deliverables" class="section level2">
<h2>Deliverables</h2>
<ul>
<li><p>A final assessment report including recommendations on actions to address the situation is to be submitted at the end of the mission. Results of standardisation tests, details of data cleaning and plausibility checks should be presented in the final report.</p></li>
<li><p>Standardised tables as presented in the Protection Assessment Toolkit.</p></li>
<li><p>The findings and major recommendations are to be presented to partners at the mission level (oral presentation and slides).</p></li>
<li><p>The final analysis script.</p></li>
</ul>
</div>
<div id="Terms-of-Reference-for-Assessment-Focal-Point_reporting" class="section level2">
<h2>Reporting</h2>
<p>The consultant will report on regular basis to the UNHCR [insert title of UNHCR person responsible], who will have the overall responsibility of the survey.</p>
</div>
<div id="Terms-of-Reference-for-Assessment-Focal-Point_time-frame" class="section level2">
<h2>Time frame</h2>
<p>The consultancy will last approximately [insert number of months], starting from [Insert start date].</p>
</div>
<div id="Terms-of-Reference-for-Assessment-Focal-Point_qualification-experience-required" class="section level2">
<h2>Qualification & Experience required</h2>
<p>The successful candidate will:</p>
<ul>
<li>Have a university degree or the equivalent in social science, with a specific competency in humanitarian emergencies.</li>
<li>Have significant experience in undertaking surveys (design and methodologies, staff recruitment and training, field supervision and data analysis/write up).</li>
<li>Be familiar with the survey methodology and R statistical language.</li>
<li>Be fluent in English with excellent writing and presentation skills [insert any other language requirements].</li>
</ul>
</div>
</article>
<article id="Sampling"><div class="fluid-row" id="Sampling_header">
<h1 class="title toc-ignore">Sampling</h1>
</div>
<div class="TOC">
<ul>
<li><a href="#Sampling_declaration-bias">Declaration Bias</a></li>
<li>
<a href="#Sampling_sampling-strategy">Sampling strategy</a><ul>
<li><a href="#Sampling_non-probabilistic-approaches">Non-probabilistic approaches</a></li>
<li><a href="#Sampling_probalistics-approaches">Probalistics approaches</a></li>
</ul>
</li>
<li>
<a href="#Sampling_sample-weight">Sample Weight</a><ul>
<li><a href="#Sampling_how-are-the-oversampledundersampled-areas-corrected-in-data-analysis">How are the oversampled/undersampled areas corrected in data analysis?</a></li>
<li><a href="#Sampling_what-does-it-mean-to-normalize-the-weights">What does it mean to normalize the weights?</a></li>
</ul>
</li>
</ul>
</div>
<div class="important">
<p>The sampling strategy is constrainted by both available budget, field accessibility and time. The sampling approach reflects a trade off between representativity of the results, rapid delivery and</p>
</div>
<div id="Sampling_declaration-bias" class="section level3">
<h3>Declaration Bias</h3>
</div>
<div id="Sampling_sampling-strategy" class="section level2">
<h2>Sampling strategy</h2>
<p>Sampling strategy can be either probabilistic or non-probabilistic. a good introduction can be found <a href="http://www.fao.org/docrep/W3241E/w3241e08.htm">here</a></p>
<div id="Sampling_non-probabilistic-approaches" class="section level3">
<h3>Non-probabilistic approaches</h3>
<p>Non-probabilistic approaches are usually <strong>favored during the emergency phase</strong> where both time and field access represent the main challenge.</p>
<div id="Sampling_convenience-sampling" class="section level4">
<h4>Convenience sampling</h4>
<p>It is a frequently used method in emergency situations. It relies on sampling those respondents who are easiest to access.</p>
<p>Practically speaking those couldd be either: * key Informant that are ready to report by themself</p>
<ul>
<li><p>Individuals or household among those who have settled along roadsides, or who present themselves to administrative center of the returnee settlement or the assistance desk etc.</p></li>
<li><p>Advantages: Easy and quick to implement, especially when time and access are the main constraints.</p></li>
<li><p>Disadvantage: The danger with this type of data collection approach is that it will often lead to biased results as the sample may not be representative of the majority, i.e. those with the most resources or power are often the ones who settle in the most easily accessible areas.</p></li>
</ul>
</div>
<div id="Sampling_snowball-sampling" class="section level4">
<h4>Snowball sampling</h4>
<p>Snowball sampling (or <a href="https://en.wikipedia.org/wiki/Snowball_sampling">chain sampling, chain-referral sampling, referral sampling</a>) is a non-probability sampling technique where existing study subjects recruit future subjects from among their acquaintances. This technique is subject to numerous biases. For example, people who have many friends are more likely to be recruited into the sample.</p>
<ul>
<li><p>Advantages: Useful when targeting specific groups that might be difficult to reach (hidden population).</p></li>
<li><p>Disadvantage: This approach might underweight the most vulnerable individuals.</p></li>
</ul>
</div>
<div id="Sampling_purposive-sampling" class="section level4">
<h4>Purposive sampling</h4>
<p>It is based on previous knowledge about who might be able to provide valuable or specific information. It uses the judgement of community representatives, project staff or assessors to select typical locations and/or informants. The sampling of children or women, for example, is a type of purposive sampling.</p>
<p>Purposive sampling can also be done through Key Informant.</p>
<ul>
<li><p>Advantages: Moderately rigorous if well and clear criteria for sampling are followed. Useful when targeting specific groups of affected population or specific affected areas. Less time consuming and less expensive than representative sampling.</p></li>
<li><p>Disadvantage: Generalisations are biased and not recommended. Samples are not representative of population due to subjectivity of respondents.</p></li>
</ul>
<p>The risk of loosing certain componnent of the population can be addressed by defining strata within the purposive sample.</p>
<p>In the case of Desk interview or key Informant, the more observation the better. Some kind of <a href="http://iomiraqdtm.info/Downloads/00-%20DTM%20Methodology%20Documents/DTM_LA_Credibility_Scoring_Methodology.pdf">credibility scoring</a> can be obtained for each locations based on a review of the key informant.</p>
</div>
<div id="Sampling_quota-sample" class="section level4">
<h4>Quota sample</h4>
<p>A quota sample might be representative of the population (if quotas actually do work, which they not always do). But a quota sample will never satisfy the strict randomness requirements that statistics require. Only if we are working with a random sample can we make inferences from the sample to the population. In quota samples, there is not sufficient randomness, as the interviewer selects the interviewees actively. Therefore, quota samples cannot be used to reason about the general population.</p>
</div>
</div>
<div id="Sampling_probalistics-approaches" class="section level3">
<h3>Probalistics approaches</h3>
<p>Whenever the situation is becoming more <strong>protracted</strong>, probabilistic approaches should be favored. They will allow to generate more reliable results.</p>
<div id="Sampling_respondent-driven-sampling--rds" class="section level4">
<h4>Respondent-driven sampling -RDS</h4>
<p>A declination of snowball sampling is the <a href="http://www.respondentdrivensampling.org/">Respondent-driven sampling -RDS</a> approach. It combines “snowball sampling” with a mathematical model that weights the sample to compensate for the fact that the sample was collected in a non-random way. As such it can be classified as probabilistic approach. The advantage is that seeds selection is specific and does not require sample frame.</p>
<p>While data requirements for RDS analysis are minimal, there are three pieces of information which are essential for analysis (RDS analysis CANNOT BE PERFORMED without these fields for each respondent):</p>
<ul>
<li><p>Personal Network Size (Degree) - Number of people the respondent knows within the target population.</p></li>
<li><p>Respondent’s Serial Number - Serial number of the coupon the respondent was recruited with.</p></li>
<li><p>Respondent’s Recruiting Serial Numbers - Serial numbers from the coupons the respondent is given to recruit others.</p></li>
</ul>
</div>
<div id="Sampling_time-location-sampling" class="section level4">
<h4>Time-Location Sampling</h4>
<p>The Time-Location Sampling (TLS) approach can be used when the goal is to have a representation of population in movement. The idea and the assumption is to sample persons at locations and at time at which they may be found.</p>
<p>Time-location sampling is used to sample a population for which a sampling frame cannot be constructed but locations are known at which the population of interest can be found, or for which it is more efficient to sample at these locations. As such the approach is likely appropriate when the survey is taking place at a <strong>border</strong>.</p>
<p>More practical guidelines for TLS are available in a dedicated <a href="http://globalhealthsciences.ucsf.edu/sites/default/files/content/pphg/surveillance/modules/global-trainings/tls-res-guide-2nd-edition.pdf">Resource Guide TLS</a> and some application on Border Monitoring for <a href="http://meetings.sis-statistica.org/index.php/sm/sm2012/paper/viewFile/2180/149">tourism</a> or <a href="https://books.google.jo/books?id=Gz9eAgAAQBAJ&pg=PA53&lpg=PA53&dq=Border+surveys+and+Time+Location+Sampling&source=bl&ots=6i5IgC-2Mb&sig=P3CdG8-LvC0Y_LCK-MZ047gAJNQ&hl=en&sa=X&redir_esc=y#v=onepage&q=Border%20surveys%20and%20Time%20Location%20Sampling&f=false">illegal migrants</a>.</p>
</div>
<div id="Sampling_random-sampling" class="section level4">
<h4>Random sampling</h4>
<p>If you need a purely random sample, the size of the sample is a calculation that takes 3 variables:</p>
<ul>
<li><p>Size of the full population. In refugee Context, Data is coming from proGres while in IDP context, data is coming from a Displacement Tracking System.</p></li>
<li><p>Confidence level: for what proportion of the population you want to get the right estimation (usually either 90%, 95% or 99%)</p></li>
<li><p>Error Margin (or confidence interval): How much error are you willing to tolerate for each questions? i.e. + or – your estimated ratio for each questions on the top of the confidence interval (usually either 5%, 2% or 1%)</p></li>
</ul>
<p>There are <a href="https://www.surveymonkey.com/mp/sample-size-calculator/">online calculator</a> for this. Alternatively one can use the excel formula from this <a href="http://archive.snh.gov.uk/vmm/Resources/R38%20SAMPLE%20SIZE%20CALCULATOR.xls">example</a></p>
<table>
<thead><tr class="header">
<th>For 400,000 Syrians</th>
<th>5% error margin</th>
<th>2% error margin</th>
<th>1% error margin</th>
</tr></thead>
<tbody>
<tr class="odd">
<td>90% Confidence level</td>
<td>272</td>
<td>1694</td>
<td>6692</td>
</tr>
<tr class="even">
<td>95% Confidence level</td>
<td>384</td>
<td>2387</td>
<td>9379</td>
</tr>
<tr class="odd">
<td>99% Confidence level</td>
<td>662</td>
<td>4105</td>
<td>15929</td>
</tr>
</tbody>
</table>
<table>
<thead><tr class="header">
<th>For 150,000 Afghans</th>
<th>5% error margin</th>
<th>2% error margin</th>
<th>1% error margin</th>
</tr></thead>
<tbody>
<tr class="odd">
<td>90% Confidence level</td>
<td>272</td>
<td>1682</td>
<td>6511</td>
</tr>
<tr class="even">
<td>95% Confidence level</td>
<td>383</td>
<td>2363</td>
<td>9026</td>
</tr>
<tr class="odd">
<td>99% Confidence level</td>
<td>661</td>
<td>4036</td>
<td>14937</td>
</tr>
</tbody>
</table>
<p>Usually the decision on the right confidence level and error margin to be selected is also influenced by cost implication and the final usage of the figures that is looked for.</p>
</div>
<div id="Sampling_stratified-sampling" class="section level4">
<h4>Stratified sampling</h4>
<p>You can refer to this <a href="https://www.youtube.com/watch?v=WakK8Wzmw6o&list=PLyLpEs0x9BnmPTE2RRRJW058Nf7R_2xQa&index=5">Introduction video</a> or this <a href="http://ocw.jhsph.edu/courses/StatMethodsForSampleSurveys/PDFs/Lecture4.pdf">presentation</a> and this <a href="https://resources.vam.wfp.org/sites/default/files/mVAM_Generic%20training%20for%20live%20call%20operators.pptx">one formt eh WFP VAM</a>.</p>
<p>A stratified random sample can only be carried out if a complete list of the population is available. In stratified sampling the population is partitioned into groups, called strata, and sampling is performed separately within each stratum.</p>
<p>This can be done for the following reasons:</p>
<ul>
<li><p>Population groups may have different values for the responses of interest.</p></li>
<li><p>If we want to improve our estimation for each group separately.</p></li>
<li><p>To ensure adequate sample size for each group.</p></li>
</ul>
<p>In stratified sampling designs, it is assumed that:</p>
<ul>
<li><p>stratum variables are mutually exclusive (non-over lapping), e.g., urban/rural areas, economic categories, geographic regions, race, sex, etc.</p></li>
<li><p>the population (elements) should be homogenous within-stratum, and</p></li>
<li><p>the population (elements) should be heterogenous between the strata.</p></li>
</ul>
<p>The major task of stratified sampling design is the appropriate allocation of samples to different strata. The different types of allocation methods includes:</p>
<ul>
<li><p><strong>Equal allocation</strong>: Divide the number of sample units n equally among the k strata. This implies to use “weighted analysis” (disproportionate selection).</p></li>
<li><p><strong>Proportional to stratum size</strong>: Make the proportion of each stratum sampled identical to the proportion of the population. A major disadvantage of proportional allocation is that sample size in a stratum may be low – provide and provide unreliable stratum-specific results. In terms of analysis, data will be Self-weighted (equal proportion from each stratum).</p></li>
<li><p>Allocation based on <strong>variance differences among the strata</strong> (called Optimal allocation). Optimal allocation minimizes the overall variance for a specified cost, or equivalently minimizes the overall cost for a specified variance. In situations where the standard deviations of the strata are known it may be advantageous to make a disproportionate allocation. Suppose that, we had stratum A and stratum B, but we know that the individuals assigned to stratum A were more varied with respect to their opinions than those assigned to stratum B. Optimum allocation minimises the standard error of the estimated mean by ensuring that more respondents are assigned to the stratum within which there is greatest variation. Stratum variances are susually defined by previous surveys. This approach also implies to use “weighted analysis” (disproportionate selection).</p></li>
<li><p>Allocation based on the <strong>relative cost of each survey record</strong> (called Neyman Allocation).Neyman allocation is a special case of optimal allocation where the costs per unit are the same for all strata. In this case, the ideal sample allocation allow to maximize precision, given a Stratified Sample With a fixed Sample Size. The ideal sample allocation plan would provide the most precision for the least cost. This implies to sample more heavily from a stratum when the cost to sample an element from the stratum is low, the population size of the stratum is large or the variability within the stratum is large.This approach also implies to use “weighted analysis” (disproportionate selection).</p></li>
</ul>
<p>Typically, when developping the stata definition, in case of optimal or neyman allocation, i.e. when stratea variance are already known through a previous survey, the following objectives can be looked at: * Find minimum sample size, given a fixed error * Find minimum error, given a fixed sample size * Find minimum error, given a fixed budget * Find minimum cost to achieve a fixed error</p>
<p>Typical workflow to define sample size in case of stratified sampling:</p>
<ol style="list-style-type: decimal">
<li>Choose the stratification (e.g.regions, district,….)</li>
<li>Define the population (N) of each strata</li>
<li>Decide on key indicator(s)</li>
<li>Estimate mean & variance or prevalence of key indicator</li>
<li>Decide on precision and confidence level</li>
<li>Calculate the initial total sample size (n) according to the budget/time</li>
<li>Use simple random sample per strata to select your representative sample</li>
</ol>
<p>To estimate sample size, you need to know:</p>
<ul>
<li>Estimate of the prevalence or mean & STDev of the key indicator (e.g. 30% return intention). Prevalence is the total number of cases for a variable of interest that is <strong>typically binary</strong> within a population divided by its total population. Mean is the expected value of a variable of interest that is <strong>typically continuous</strong> within a prescribed range for a given population (e.g. expenditure per case)</li>
<li>Precision desired (for example: ± 5%). Precision is the variability of the estimate.</li>
<li>Level of confidence (for example: 95%). It represents the probability of the same result if you re-sampled, all other things equal.</li>
<li>Population (only if below 10,000, otherwise it will not influence the required sample size)</li>
<li>Expected response rate (for example: 90%)</li>
<li>Number of eligible individuals per household (if applicable)</li>
</ul>
<p>Stratified sampling can be performed with R. <a href="https://github.com/unhcr-mena/stratified-sampling">Tutorial scripts are available here</a>.</p>
</div>
<div id="Sampling_post-stratification" class="section level4">
<h4>Post stratification</h4>
<p>One can also use weights, computed through a <a href="https://www.r-bloggers.com/survey-computing-your-own-post-stratification-weights-in-r/">post-stratification process</a>, to get potentially biased surveys, like online surveys, to better fit the underlying population. The only thing that weights can do, is ensure that your sample composition better mimics the general population’s characteristics. Weights will never help you if the process governing non-response is part of the puzzle you want to solve.</p>
<p>In a random sample, we define a population, draw from that population at random and then compute and apply weights to align the sample with the population. This weighting is necessary because some people originally sampled might be e.g. harder to reach than others, thereby biasing the sample. Once the post-stratification weights have been applied, the random sample is representative of the population it was drawn from. Statistics gives us a method to tell just how accurately the findings from the sample can be generalized.</p>
</div>
<div id="Sampling_cluster-sampling" class="section level4">
<h4>Cluster sampling</h4>
<p>Cluster sampling is a technique that allows to reduce the surveying budget when <strong>travel cost are important</strong>. Instead of covering a whole territory, the cluster sampling implies to divide the population into separate groups, called clusters. Then, a simple random sample of clusters is selected from the population.</p>
<p>Cluster sampling are therefore not relevant when techniques such as phone interview are used as there’s no marginal surveying cost involved with location of interview.</p>
<p>Given equal sample sizes, cluster sampling usually provides less precision than either simple random sampling or stratified sampling.</p>
<p>different approaches can be used for cluster sampling</p>
<ul>
<li>One-stage sampling. All of the elements within selected clusters are included in the sample.</li>
<li>Two-stage sampling. A subset of elements within each selected cluster is randomly selected for inclusion in the sample.</li>
</ul>
</div>
<div id="Sampling_sampling-with-replacement-and-sampling-without-replacement" class="section level4">
<h4>Sampling With Replacement and Sampling Without Replacement</h4>
<p>When a population element can be selected more than one time, we are sampling with replacement. When a population element can be selected only one time, we are sampling without replacement. When we sample with replacement, the two sample values are independent. Practically, this means that what we get on the first one doesn’t affect what we get on the second. Mathematically, this means that the covariance between the two is zero.In sampling without replacement, the two sample values aren’t independent. Practically, this means that what we got on the for the first one affects what we can get for the second one. Mathematically, this means that the covariance between the two isn’t zero.</p>
<p>In small populations and often in large ones, sampling is typically done “without replacement”, i.e., one deliberately avoids choosing any member of the population more than once. Although sampling can be conducted with replacement instead, this is less common and for a small sample from a large population, sampling without replacement is approximately the same as sampling with replacement, since the odds of choosing the same individual twice is low.You can tell how dramatic the results are by calculating the covariance. That’s a measure of how much two items’s probabilities are linked together; the higher the covariance, the more dramatic the results. A covariance of zero would mean there’s no difference between sampling with replacement or sampling without.</p>
<p>As explained in this <a href="http://www.statcan.gc.ca/pub/12-001-x/2001002/article/6089-eng.pdf">paper</a>, bias may be introduced into population estimates through Telephone surveys, however, by the exclusion of nontelephone households from these surveys.The bias introduced can be significant since “non-telephone households” may differ from telephone households in ways that are not adequately handled by poststratification. Many households, called “transients”, move in and out of the telephone population during the year, sometimes due to economic reasons or relocation. The transient telephone population may be representative of the non-telephone population in general since its members have recently been in the non-telephone population.</p>
</div>
</div>
</div>
<div id="Sampling_sample-weight" class="section level2">
<h2>Sample Weight</h2>
<p>Over-sampling in regions with small populations ensures that they have a large enough sample to be representative. Under-sampling is done in regions with large populations to save costs. Sample weights are mathematical adjustments applied to the data to correct for over-sampling, under-sampling, and different response rates to the survey in different regions.</p>
<div id="Sampling_how-are-the-oversampledundersampled-areas-corrected-in-data-analysis" class="section level3">
<h3>How are the oversampled/undersampled areas corrected in data analysis?</h3>
<p>The samples are designed to permit data analysis of regional subsets within the sample population. When the expected number of cases for some of these regions is too small for analysis, it is necessary to oversample those areas. When the expected number of cases for some of these regions is unnecessarily large, those areas may be undersampled to accommodate logistical or budgetary constraints.</p>
<p>During analysis, it is then necessary to “weight down” the oversampled areas and “weight up” the undersampled areas. The developing of the sampling weights has taken this factor into account. Always use the weight variable found in the DHS data set. Even in surveys that come from a self-weighting sample, it is still necessary to use the sampling weights in analysis because the response behavior may differ by response groups.</p>
</div>
<div id="Sampling_what-does-it-mean-to-normalize-the-weights" class="section level3">
<h3>What does it mean to normalize the weights?</h3>
<p>After the weights are initially calculated, they are normalized, or standardized, by dividing each weight by the average of the initial weights (equal to the sum of the initial weight divided by the sum of the number of cases) so that the sum of the normalized/standardized weights equals the sum of the cases over the entire sample. The standardization is done separately for each weight for the entire sample.</p>
<p>The entire set of household sample weights is multiplied by a constant, thus, the total weighted number of households equals the total unweighted number of households at the national level.</p>
<p>Individual sample weights are normalized separately for women and men. Thus, the total weighted number of women equals the total unweighted number of women, and the total weighted number of men equals the total unweighted number of men. Women and men are normalized separately because all non-HIV calculations are performed on women and men separately. We do not provide survey estimates on the joint population of women and men combined for anything other than HIV prevalence.</p>
</div>
</div>
</article>
<article id="Interview"><div class="fluid-row" id="Interview_header">
<h1 class="title toc-ignore">Interview</h1>
</div>
<div class="TOC">
<ul>
<li>
<a href="#Interview_definition-of-household-and-relations-with-unhr-registration-case">Definition of household and relations with UNHR Registration case</a><ul>
<li><a href="#Interview_definition-of-households">Definition of households</a></li>
<li><a href="#Interview_relations-with-unhcr-cases-as-per-registration">Relations with UNHCR cases as per Registration</a></li>
</ul>
</li>
<li>
<a href="#Interview_comparison-of-interview-approaches">Comparison of interview approaches</a><ul>
<li><a href="#Interview_face-to-face-interview">Face to Face interview</a></li>
<li><a href="#Interview_telephone-interview-through-call-center">Telephone interview through Call Center</a></li>
<li><a href="#Interview_self-administered-with-online-quota-survey">Self administered with online quota survey</a></li>
<li><a href="#Interview_interactive-voice-response-short-text-message-sms-pools">Interactive Voice Response & Short text Message (SMS) Pools</a></li>
</ul>
</li>
<li><a href="#Interview_interview-incentives">Interview incentives</a></li>
<li><a href="#Interview_interview-lenght">Interview lenght</a></li>
<li><a href="#Interview_who-to-interview">Who to interview?</a></li>
<li><a href="#Interview_how-to-deal-with-sensitive-questions">How to deal with Sensitive questions?</a></li>
</ul>
</div>
<div class="important">
<p>Several aspects come into play in the data collection process. The three most crucial aspects include: the cost of the selected data collection method; the accuracy of data collected; and the efficiency of data collection.</p>
<p>In regard to behavioural characteristics, it is generally recongised that face-to-face data deliver the best results, followed by telephone interviews and finally online quota survey. Interactive Voice Response & Short text Message (SMS) Pools are adequate only in very specific cases.</p>
<p>interview incentive can be very effective to ensure a good response ratio.</p>
</div>
<p>May guidelines are available such as:</p>
<ul>
<li><a href="http://unstats.un.org/unsd/demographic/sources/surveys/Series_F98en.pdf">Designing Household Survey Samples: Practical Guidelines</a></li>
<li><a href="https://openknowledge.worldbank.org/bitstream/handle/10986/6975/350340The0Powe1n0REV01OFFICIAL0USE1.pdf?sequence=1">The Power of Survey Design</a></li>
</ul>
<div id="Interview_definition-of-household-and-relations-with-unhr-registration-case" class="section level2">
<h2>Definition of household and relations with UNHR Registration case</h2>
<div id="Interview_definition-of-households" class="section level3">
<h3>Definition of households</h3>
<p>This concept is explained in details in the (Principles and Recommendations for <a href="http://unstats.un.org/unsd/publication/seriesM/Series_M67rev3en.pdf">Population and Housing Censuses</a>.</p>
<p>The concept of household include those persons who live together and have communal arrangements concerning subsistence and other necessities of life, such as eating together. This implies therefore 2 important arrangement;</p>
<ul>
<li><p>The <strong>household dwelling</strong> concept regards all persons living in a housing unit as belonging to the same household. According to this concept, there is one household per occupied housing unit. Therefore, the number of occupied housing units and the number of households occupying them are equal and the locations of the housing units and households are identical.</p></li>
<li><p>The <strong>housekeeping concept</strong>, that is to say, a person or a group of two or more persons living together who make common provision for food or other essentials for living, with or without combining with any other person to form part of a multi-person household. The persons in the group may pool their resources and have a common budget; they may be related or unrelated persons or a combination of persons both related and unrelated.</p></li>
</ul>
<div id="Interview_household-types" class="section level4">
<h4>Household types</h4>
<p>3 types of households can be distinguished:</p>
<p><strong>Nuclear household</strong>: It is defined as a household consisting entirely of a single family nucleus. It may be classified into:</p>
<ul>
<li>Married-couple family: With child(ren) or Without child(ren);</li>
<li>Partner in consensual union (cohabiting partner): With child(ren) or Without child(ren);</li>
<li>Father with child(ren);</li>
<li>Mother with child(ren);</li>
</ul>
<p><strong>Extended household</strong>: It is defined as a household consisting of any one of the following:</p>
<ul>
<li>A single family nucleus and other persons related to the nucleus, for example, a father with child(ren) and other relative(s) or a married couple with other relative(s) only;</li>
<li>Two or more family nuclei related to each other without any other persons, for example, two or more married couples with child(ren) only;</li>
<li>Two or more family nuclei related to each other plus other persons related to at least one of the nuclei, for example, two or more married couples with other relative(s) only;</li>
<li>Two or more persons related to each other, none of whom constitute a family nucleus;</li>
</ul>
<p><strong>Composite household</strong> It is like an extended household with the difference of :</p>
<ul>
<li>A single family nucleus plus other persons, some of whom are related to the nucleus and some of whom are not, for example, mother with child(ren) and other relatives and non-relatives;</li>
<li>A single family nucleus plus other persons, none of whom is related to the nucleus, for example, father with child(ren) and non-relatives);</li>
<li>Two or more family nuclei related to each other plus other persons, some of whom are related to at least one of the nuclei and some of whom are not related to any of the nuclei, for example, two or more couples with other relatives and non-relatives only;</li>
<li>Two or more family nuclei related to each other plus other persons, none of whom is related to any of the nuclei, for example, two or more married couples one or more of which with child(ren) and non-relatives;</li>
<li>Two or more family nuclei not related to each other, with or without any other persons;</li>
<li>Two or more persons related to each other but none of whom constitute a family nucleus, plus other unrelated persons;</li>
<li>Non-related persons only;</li>
</ul>
</div>
</div>
<div id="Interview_relations-with-unhcr-cases-as-per-registration" class="section level3">
<h3>Relations with UNHCR cases as per Registration</h3>
<p>The UNHCR case is the equivalent of Nuclear household. NHCR case are used a basis for large part of the assistance delivery.</p>
<p>When surveying Households, it is important to make connection between the households and the cases:</p>
<ul>
<li>Case 1: One single family nucleus which then equals a UNHCR case. In this case both dwelling & housekeeping are de facto shared.</li>
<li>Case 2: An extended household with two or more than two UNHCR cases. In this case, the surveyor will record if dwelling & housekeeping are effectively shared between cases.</li>
<li>Case 3: A composite household with two or more than two UNHCR cases, as well as additional members, such as host communities individuals. In this case, the surveyor will record if dwelling & housekeeping are effectively shared between cases, as well as with the members that are not part of the cases.</li>
</ul>
<p>The main point is to allow for understanding the allocation of expenses (housekeeping & dwelling) between cases that would be grouped together in the same extended or composite household. The allocation coudl be based for instance on:</p>
<ul>
<li>One case covering for all other cases;</li>
<li>One case covering for non-UNHCR case members;</li>
<li>Allocation based on number of individuals in each case;</li>
<li>Allocation based on number of adults individuals in each case;</li>
<li>Allocation based on number of individuals that get an income in each case, etc.</li>
</ul>
</div>
</div>
<div id="Interview_comparison-of-interview-approaches" class="section level2">
<h2>Comparison of interview approaches</h2>
<p>The follwing is based on Literature review from <a href="http://www.electionstudies.org/resources/papers/documents/nes010871.pdf">here</a> and <a href="http://academyofwinebusiness.com/wp-content/uploads/2013/04/Szolnoki-Hoffmann.pdf">here</a>.</p>
<div id="Interview_face-to-face-interview" class="section level3">
<h3>Face to Face interview</h3>
<p>Advantages:</p>
<ul>
<li>Accurate screening. Face-to-face interviews help with more accurate screening. The individual being interviewed is unable to provide false information during screening questions such as gender, age, or race.</li>
<li>Keep focus. The interviewer is the one that has control over the interview and can keep the interviewee focused and on track to completion.<br>
</li>
<li>Capture emotions and behaviors. Face-to-face interviews can no doubt capture an interviewee’s emotions and behaviors. Interviewer opinion can be a very good predictor of vulneraility for instance</li>
</ul>
<p>Disadvantages:</p>
<ul>
<li>Cost. Cost is a major disadvantage for face-to-face interviews. They require a staff of people to conduct the interviews, which means there will be personnel costs.</li>
<li>Quality of data by interviewer. The likelihood of the entire interviewing staff having those skills is low. Some interviewers may also have their own biases that could impact the way they input responses.<br>
</li>
<li>Reluctance: Women and the elderly may feel more physically vulnerable than men and younger people. So the first of these groups may be more reluctant to allow a stranger into their homes for an interview, whereas they may be willing to talk with an interviewer over the telephone.<br>
</li>
<li>Limit sample size. The size of the sample is limited to the size of your interviewing staff, the area in which the interviews are conducted, and the number of qualified respondents within that area.<br>
</li>
<li>Higher level of “unknown” reponse are boserved and were demonstrated by <a href="http://egap.org/content/brief-36-face-face-interviews-cognitive-skill-and-non-response">studies</a>: “There is more item non-response in in-person interviews and that non-response is being driven by people with low levels of cognitive skills. The fact that there was an increased rate of correct responses to fact-based questions in the in-person interviews compared to the self-completed ones – with the concomitant decrease in “don’t knows” – suggests that it is not the case that people are randomly guessing in the self-completed modes. The in-person interview seems to keep people from answering even when they know the correct response”.</li>
</ul>
</div>
<div id="Interview_telephone-interview-through-call-center" class="section level3">
<h3>Telephone interview through Call Center</h3>
<p>Telephone surveys may provide a good alternative, but we would advise use of a larger sample.</p>
<p>Advantages:</p>
<ul>
<li>Increasing rates of telephone coverage,</li>
<li>Low cost of telephone surveys relative to face-to-face interviews,</li>
<li>speed with which telephone surveys can be conducted.</li>
</ul>
<p>Disadvantages:</p>
<ul>
<li>people without telephones can only participate in face-to-face surveys. The systematic exclusion of this latter group from telephone surveys may introduce bias if this group is both sufficiently sizable and also sufficiently different from telephone owners. A</li>
<li>Young adults are more transient and less settled than middle or older age adults, the former individuals may be less likely to own telephones and therefore may be under-represented in telephone samples.<br>
</li>
<li>Telephone survey responses manifest more social desirability response bias than the Internet survey;</li>
<li>Risk of selecting random people who lost/changed their phone.</li>
</ul>
</div>
<div id="Interview_self-administered-with-online-quota-survey" class="section level3">
<h3>Self administered with online quota survey</h3>
<p>The emergence of Internet surveys in the 1990s threatened the dominance of telephone surveys due to their advantages in terms of cost and speed. Indeed, Internet surveys soon appeared as a promising alternative to prior methods; nevertheless, there are still problems with the coverage and, as a result, with the representativeness of online surveys.</p>
<p><a href="http://jssam.oxfordjournals.org/content/2/4/498">Scrolling versus Paging, SMS versus E-mail Invitations</a> have an impact on response rates in web surveys completed on personal computers. Scrolling design leads to significantly faster completion times, lower (though not significantly lower) breakoff rates, fewer technical problems, and higher subjective ratings of the questionnaire. SMS invitations are more effective than e-mail invitations in mobile web surveys.</p>
<p>Advantages:</p>
<ul>
<li>Lower cost and higher speed;</li>
<li>Visual, interactive, and flexible;</li>
<li>Do not require interviewers to be present and busy people – often educated and well-off – who systematically ignore taking part in a telephone survey are willing to answer questions posted on their computer screens;</li>
<li>Sutdies found that Internet-based surveys increased the reporting on sensitive information, compared to computer-assisted telephone interview.</li>
</ul>
<p>Disadvantages:</p>
<ul>
<li>under representation of uneducated population group: panel: one can reach only those who are online; one can reach only those who agree to become part of a panel; not all those who are invited respond; and, those who sign up for online panels are rather young and male.</li>
</ul>
</div>
<div id="Interview_interactive-voice-response-short-text-message-sms-pools" class="section level3">
<h3>Interactive Voice Response & Short text Message (SMS) Pools</h3>
<p>IVR (<a href="https://en.wikipedia.org/wiki/Interactive_voice_response">Interactive Voice Response</a>) can be used with a Free tool #.</p>
<p>Advantages:</p>
<ul>
<li>Accessible to illiterate and in multiple language</li>
<li>Can support a lot of concurrent connection</li>
</ul>
<p>Disadvantages:</p>
<ul>
<li>Technology need to be purchased</li>
<li>Can not process to complex information</li>
</ul>
<p>SMS gateway: FrontlineSMS has been already used under the project name <a href="http://innovation.unhcr.org/labs_post/ascend/">Ascend</a> and tested by <a href="http://innovation.unhcr.org/testing-ascend-in-costa-rica-refining-the-solution/">UNHCR in Costa Rica</a></p>
<p>Specific constraints:</p>
<ul>
<li>4 options max per questions</li>