LLIN Durability Monitoring

Slides:



Advertisements
Similar presentations
Multiple Indicator Cluster Surveys MICS3 Regional Training Workshop Survey Logistics.
Advertisements

Maintaining data quality: fundamental steps
Company Name Here Industry Analysis. You must be connected to UCF’s wireless network in order to gain access to the library resources necessary to obtain.
1 Fieldwork Logistics. OBJECTIVES The importance of logistics in supporting high quality survey results and implementation schedule Key logistical.
Using SMS-Gateways for Monitoring Progress and Quality of Data Collection: Lessons Learned from the 2010 Population Census of Indonesia Thoman Pardosi.
Active Parasite Detection 2011 Supplemental Enumerator and CHW Training 14 November, 2011.
Simple Random Sampling
Mobile Data Collection
LLIN Durability Monitoring Study Design & Protocol.
IAGAP Access Database A Tutorial. Databases There are several databases available from the IAGAP Project. There are several databases available from the.
Planning for 2010: A Reengineered Census of Population and Housing Preston Jay Waite Associate Director for Decennial Census U.S. Census Bureau Presentation.
Click your mouse for next slide Dreamweaver – Setting up your Page The first way to ensure that you have a consistent design is to use table to set up.
Mobile Data Collection With Open Data Kit (ODK) Android OS- Motorola Defy Sony Ericsson Xperia Pro & Mini Pro Samsung Galaxy Tab.
Multiple Indicator Cluster Surveys Data Processing Workshop CAPI Supervisor’s Menu System MICS Data Processing Workshop.
Copyright © Cengage Learning. All rights reserved. 2 Organizing Data.
Active Parasite Detection 2011 Supplemental Enumerator and CHW Training 21 November, 2011.
Secret Book Written Activity Sample Section A (front cover) Boxes 1-3 Students select three powerful quotes from the story and write each on in the three.
MICS Survey Design Workshop Multiple Indicator Cluster Surveys Survey Design Workshop Data Entry Using Tablets / Laptops.
CASE STUDIES OF SOME SURVEYS IN SADC COUNTRIES Experience from Tanzania Household Surveys and Measurement of Labour Force with Focus on Informal Economy.
Module 3: Selecting Locations and Respondents Outcome Monitoring and Evaluation Using LQAS.
How to Use the Online Project Monitoring System (OPMS) Navigating the Survey.
Crop Cutting Questionnaire (Part A) Corinna Bordewieck October2015 Center for Agricultural Statistics (CAS) Ministry of Agriculture and Forestry.
Chester County 24 Challenge® Tournament Overview
Easy and Effective Ways to Expand Your Comprehension
Make-Up Testing/Undo Student Test Submissions
A step-by-Step Guide For labels or merges
Module 9: Choosing the Sampling Strategy
Quality assurance in population and housing census SUDAN’s EXPERIANCE in QUALITY assurance of Censuses By salah El din. A . Magid OUR EXPERIANCE IN 5.
Supervisor Instructions: Bi-Weekly Payable Time/Absence Request
Select Survey Invitations
Pre-K and PreSchool Students
Database Normalization
LLIN Hole Assessment Training for Surveyors
Tips for Taking the Computer-Based
CASE STUDIES OF SOME SURVEYS IN SADC COUNTRIES Experience from Tanzania Household Surveys and Measurement of Labour Force with Focus on Informal Economy.
Statistics for Business
Test Administrator Interface & Student Interface
Descriptive Statistics
Elementary Statistics
KS1 Therapy: Y1 Maths Commissioned by The PiXL Club Ltd. May 2018
Dismissal Staff Quick Start Guide
Module 8 CD-JEV immunization campaigns
Module 5: Data Cleaning and Building Reports
Tips for Taking the Computer-Based
Using Statistical techniques in Geography
Day 3. How to Measure.
Test Administrator Interface & Student Interface
Microsoft Official Academic Course, Access 2016
Place Value and Decimals 1 – Objectives
An AS Lesson Using the LDS to teach content on Data Collection and Processing.
CRITICAL SUMMARY ASSIGNMENT
Normal Probability Distributions
Training Workshop – Module 2
CRITICAL SUMMARY ASSIGNMENT
Measures of Position Section 3.3.
self-paced eLearning series
CRITICAL SUMMARY ASSIGNMENT
The Six-Column Work Sheet
Tips for taking the Grades 9 and 10 FCAT 2.0 Reading Test
Measures of Relative Position
Frequency Distributions
Writing a Summary Say- Now we are going to write a summary of the story I just read- The Wall by Eve Bunting.
The Kish Method.
Frequency Distributions
Bangladesh Bureau of Statistics (BBS)
SPOT CHECKS 2016.
Presentation transcript:

LLIN Durability Monitoring Household selection

Overview Sectioning the settlement Listing and numbering all eligible households Selection of households with random number lists Allocation of interviews and replacements

Sectioning a cluster 15 clusters have been selected per site If the settlement has more than 200 households, it should be sectioned into equal part of about 60-100 households These remain the same for all three survey rounds If the size of a cluster (village, community or census enumeration area) is not already known, the supervisor inquires from the local authorities the approximate size during the mobilization phase. If the size is more than 200 households, the community should be divided into 2 or more approximately equal sections. This is done because otherwise it would take too long to list all households and would require an additional day to cover that cluster.

Sectioning a settlement This should be done with local authorities or chief With the help of the local authorities or chief a rough sketch of a map of the area will be prepared, using either natural boundaries like roads or rivers or already exiting subunits in that community. This should be done in such a way that each section has not less than about 40-60 households. Now one section will be selected randomly either by using small pieces of paper or asking a person not involved in the selection process. This selection can be done before the field visit or as the first thing when the team arrives in the cluster. The supervisor now allocates a defined area within the community (or selected section) to each interviewer (plus local guide) and ensures that they have the household listing forms.

Listing of households Within the settlement (or selected section) all households where people live are listed and given a household number Excluded are office buildings Schools, health facilities markets, trading centers prisons, orphanages, barracks any uninhabited other building Each interviewer visits all the inhabited households (i.e. where people live and some slept in the previous night) in the area he is allocated and lists name of head of household. Exclusions will follow the rules used in the net distribution campaign, i.e. office buildings, schools, markets, health facilities, prisons, orphanages, and any uninhabited other building.

Listing of households Each interviewer is allocated a part of the settlement (section) for listing Each eligible household is given a unique number The number has two parts One digit for the interviewer (1-9) Team 1: 1-3, team 2: 4-6, team 3: 7-9 Two digits for the household (01-99) e.g. 101, 312, 645 The supervisor will allocate interviwers to specific sections of the cluster (or the selected section of the cluster) making sure that borders of each interviewer’s area are clear and neither are houses missed nor are they double listed Each interviewer has his/her own listing sheets and allocates the unique household numbers as follows: The household ID number has three digits in total The first digit is the interviewer’s number that has been allocated to him by the supervisor (1 to 9 for the three teams of three interviewers each) The next two digits are a running number of the houses this interviewer has listed starting with 01 and going up to a maximum of 99. This means that each interviewer should have less than 100 houses to list The total household number is then the three digit number as shown in the example

Listing of households Here an example is given for the first 9 houses listed by the first interviewer

Listing of households And this would be the list for the third interviewer

Listing of households Once all interviewers have completed their lists the supervisor merges them In the column “supervisor (#)” of the household listing sheet he/she creates a running number including all households listed The last number then is the total number of households listed The points of this slide are demonstrated in the next slide

Listing of households Supervisor will “merge” the lists as follows: the supervisor sorts the lists by interviewer starting with interviewer one, then two etc. He/she fills a number in column "#" starting with "1" until he reaches the last entry of interviewer one. These numbers for the first interviewer are the same as the consecutive number in the unmarked column of the listing form. For the second interviewer, the supervisor continues the numbering, i.e if interviewer one ended with 46, then the first number for interviewer two is 47 in column "#". This means that the last number for the last interviewer is n, the total number of households listed.

Selection of households The supervisor now looks up the number of listed households in the “random number list” under the column “listed hh” The first 10 numbers in that row – columns 1-10 – are the selected households The supervisor marks these on the listing form Again, the example in the next slide demonstrates the points made here

Selection of households The last number entered (n) is looked up in the first column of the random number table provided to the supervisor under "listed hh" which is the total number of households listed. Let’s say that number is “36". Now you go across the row “36" and there are 15 columns labeled at the top as 1-15 which are the households to be sampled: 1, 3, 6, 8, 10, .... etc. This refers to the cumulative list of households of column "#" in the listing form. So the supervisor marks that number with an "X" in the "selected" column of the listing form and those are the sampled households. Note: This example is from an earlier study and, therefore, has 15 selected households. In our study we have 10!!!!

Selection of households Here we see the completed list with selected households marked with the X in the “selected” column. Imprtant: the ID number for the household to be entered into the questionnaire is NOT the running number in the supervisor/# column, but the number originally given by the interviewer during listing and entered in the “HH-ID” column (here marked with the red circle) All selected households are visited by the team using the number under “HH-ID” as the household number on the questionnaire

ID numbers of households The household ID entered on the questionnaire is the ID number given by the interviewer in the listing form. It is important that on each questionnaire also the interviewer code is entered in order to distinguish potential duplicate HH-ID numbers within a cluster. You see here that four digits are allowed for the household number. This is because due to replacements of interviewers, interviewer code may be 10 or higher. If the household number only has three digits, it is preceeded by a 0 as shown here.

Replacement of households Selected households that are found not to be eligible because they did not receive any campaign nets are marked on the listing form by the interviewer (circle ID number) After all 10 households are visited the supervisor selects the required number of households from the replacements R1-R6 from the random number list

Replacement of households The row with the 36 total households in the “listed hh” column is used again, but this time only the replacements are used

Replacement of households Replacement numbers are used in the order of ineligible households from left to right If a replacement household is not eligible, it is NOT replaced Not more than 10 replacements in total For example: if there is need for 5 replacements, the first five numbers (R1 to R5) from the random number table are used. They are allocated to the three interviewer teams and visited for interview.

Summary of cluster results After a cluster is finished the supervisor summarizes the results After the interviews are complete, the supervisor fills the Supervisor Cluster Monitoring Sheet with the details of that cluster. It is very important, that the number of replacements used is noted.