Increasing Early Childhood Care and Development through Community Preschools in Cambodia 2016, Baseline Survey
Cambodia, 2016
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Reference ID
KHM_2016_ECCD-BL_v01_M
Producer(s)
Deon Filmer, Adrien Bouguen
Collection(s)
Metadata
Created on
Apr 27, 2021
Last modified
Apr 27, 2021
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Identification
Survey ID Number
KHM_2016_ECCD-BL_v01_M
Title
Increasing Early Childhood Care and Development through Community Preschools in Cambodia 2016, Baseline Survey
Subtitle
Baseline Survey
Country/Economy
| Name | Country code |
|---|---|
| Cambodia | KHM |
Study type
Other Household Survey [hh/oth]
Series Information
This impact evaluation study consists of a baseline (2016), midline (planned for 2017) and Endline (planned for 2018) data collection.
Abstract
The objectives of the evaluated intervention are to expand access to quality Early Childhood Education (ECE) for 3-5-year-olds (through the construction of facilities, provision of materials, training of staff), as well as to build the demand for Early Childhood Care and Development ECCD services among families from disadvantaged backgrounds.
The study aims to find out whether the provision of simple community preschools increases enrollment and retention rates in ECCD services. Particularly with an eye towards primary school readiness, effects on the cognitive and socio-emotional development of young children are measured. Using longitudinal data, it is tested whether complementary demand-side interventions increased enrollment, especially among the poorest households, and if demand-side interventions have an effect on the impact of the intervention.
The study aims to find out whether the provision of simple community preschools increases enrollment and retention rates in ECCD services. Particularly with an eye towards primary school readiness, effects on the cognitive and socio-emotional development of young children are measured. Using longitudinal data, it is tested whether complementary demand-side interventions increased enrollment, especially among the poorest households, and if demand-side interventions have an effect on the impact of the intervention.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
The ECCD describes children and caregivers, households and villages.
Version
Version Description
- v01, basic raw data, obtained from the data collection firm.
Version Notes
Data is a slightly modified version of raw data files from data entry. It was slightly modified to account for comments by enumerators which could not be accounted for during tablet based data collection and to merge multi-level information into one data set. Private information (names, phone numbers, GPS, addresses, pictures) have been removed in order to comply with the informed consent.
Scope
Notes
The scope of the ECCD includes:
- CHILD TEST ADMINISTERED TO THE CHILD: Mathematics (MELQO), Literacy (MELQO), Cognition (MELQO + draw a person test + Receptive Vocabulary Test), fine motor (MELQO), Gross Motor (MDAT), Non-cognitive (Cancellation task, MELQO), Anthropometrics (height and weight)
- CHILD TEST ADMINISTERED TO THE MOTHER: Non-cognitive (MDAT), SDQ, health-related questions
- CAREGIVER QUESTIONNAIRE: Child health, school enrollment, parental involvement, anthropometrics (height and weight)
- HOUSEHOLD QUESTIONNAIRE: SES household (income, assets, education, house quality, etc.)
- VILLAGE CHEF QUESTIONNAIRE: school quality measures, infrastructure, etc.
- CHILD TEST ADMINISTERED TO THE CHILD: Mathematics (MELQO), Literacy (MELQO), Cognition (MELQO + draw a person test + Receptive Vocabulary Test), fine motor (MELQO), Gross Motor (MDAT), Non-cognitive (Cancellation task, MELQO), Anthropometrics (height and weight)
- CHILD TEST ADMINISTERED TO THE MOTHER: Non-cognitive (MDAT), SDQ, health-related questions
- CAREGIVER QUESTIONNAIRE: Child health, school enrollment, parental involvement, anthropometrics (height and weight)
- HOUSEHOLD QUESTIONNAIRE: SES household (income, assets, education, house quality, etc.)
- VILLAGE CHEF QUESTIONNAIRE: school quality measures, infrastructure, etc.
Coverage
Geographic Coverage
Rural villages in 13 provinces:
- Kampong Chhnang
- Kampong Speu
- Kampot
- Kandal
- Koh Kong
- Kratie
- Mondulkiri
- Preah Sihanuk
- Prey Veng
- Ratanakiri
- Steung Treng
- Svay Rieng
- Takeo
- Kampong Chhnang
- Kampong Speu
- Kampot
- Kandal
- Koh Kong
- Kratie
- Mondulkiri
- Preah Sihanuk
- Prey Veng
- Ratanakiri
- Steung Treng
- Svay Rieng
- Takeo
Universe
Households with at least one child of age 2 - 4 at baseline.
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| Deon Filmer | World Bank |
| Adrien Bouguen | University of Mannheim |
Producers
| Name | Affiliation | Role |
|---|---|---|
| Jan Berkes | DIW Berlin | Technical assistance in questionnaire design, sampling methodology, data collection, data processing and data analysis |
| Tsuyoshi Fukao | World Bank | Task Team Leader |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| Strategic Impact Evaluation Fund | SIEF | |
| Global Partnership for Education | GPE | Program funds for mid-line survey and other tasks |
| World Bank | WB | Supervision Budget to support the IE tasks |
Other Identifications/Acknowledgments
| Name | Affiliation | Role |
|---|---|---|
| Ministry of Education, Youth and Sport | Kingdom of Cambodia | Implementation Partner |
Sampling
Sampling Procedure
The goal was to sample 26 eligible households in each of the 305 assigned villages. Eligibility criterion: at least one child of age 2-4 (at baseline) lives in the household.
Because the household listings held by local authorities are unreliable and often outdated, the data collection firm conducted a complete listing of all households in each village. Before interviewing households, the staff conducted a village mapping exercise. With the cooperation of the local authorities (village chief), the field staff have drawn a map of the village, showing all roads/intersections and households within the village and on its boundaries. Using this list, they managed to calculate the sampling interval (SI).
Field staff then followed a modified version of the EPI-walk methodology to select households: starting from a randomly selected village intersection, the interviewer:
1) Implemented the sampling interval to select the first household
2) Assessed the household eligibility (household includes at least one child aged 2 - 4 years) and
3) Conducted the household and child surveys.
If the household is not eligible for this study, the interviewer will implement a systematic sampling strategy until he/she finds an eligible household. In other words, a sampling interval of “1” was implemented until an eligible household was selected. Whenever an interview was completed with an eligible household, the interviewer implemented the previously calculated SI to reach the next household.
A maximum of 26 eligible households was selected in each targeted village. Interviewers kept following the sampling methodology described here previously until they reached the sample target (26 eligible households) or until all households were approached. If all households in the village were approached but less than 26 of them were found to be eligible, then the field team moved to the next target village.
Because the household listings held by local authorities are unreliable and often outdated, the data collection firm conducted a complete listing of all households in each village. Before interviewing households, the staff conducted a village mapping exercise. With the cooperation of the local authorities (village chief), the field staff have drawn a map of the village, showing all roads/intersections and households within the village and on its boundaries. Using this list, they managed to calculate the sampling interval (SI).
Field staff then followed a modified version of the EPI-walk methodology to select households: starting from a randomly selected village intersection, the interviewer:
1) Implemented the sampling interval to select the first household
2) Assessed the household eligibility (household includes at least one child aged 2 - 4 years) and
3) Conducted the household and child surveys.
If the household is not eligible for this study, the interviewer will implement a systematic sampling strategy until he/she finds an eligible household. In other words, a sampling interval of “1” was implemented until an eligible household was selected. Whenever an interview was completed with an eligible household, the interviewer implemented the previously calculated SI to reach the next household.
A maximum of 26 eligible households was selected in each targeted village. Interviewers kept following the sampling methodology described here previously until they reached the sample target (26 eligible households) or until all households were approached. If all households in the village were approached but less than 26 of them were found to be eligible, then the field team moved to the next target village.
Deviations from the Sample Design
In some village, less than 26 eligible households could be found. The goal of 26 households per village was reached in 67% of the villages. The average number of sampled households per village is 23.1.
Response Rate
Within the 305 villages targeted for the baseline study, a total of 7,058 households were selected using the EPI walk and interviews attempted, containing a total of 7,642 children within the target age range (2 - 4 years old). Of these interviews, a total of 6,972 interviews were successfully completed (a completion rate of 98.8%). An additional 78 interviews were reported as “complete with some missing values” by the interviewers (because the respondent did not know how to answer a given question, or refused to answer, etc.).
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2016-05-12 | 2016-07-14 |
Data Collection Mode
Computer Assisted Personal Interview [capi]
Supervision
Field Supervisors: The Field Supervisors were responsible for assisting in instrument pre-tests and interviewer training, survey logistical planning, and managing the implementation of the sampling design and data collection methodology with the Fieldwork Director in the target provinces. They ensured that interviewers collected data of the highest quality by reviewing all questionnaires in the field and conducting spot checks, re-interviews, and observations of at least 20% of all interviews in each village.
Data Collection Notes
All field staff attended training for seven days in May 2016 (from 02-05-2016 to 09-05-2016). The training was provided to field staff on survey objectives, research methodology, ethical research, interview role play, survey team roles and responsibilities, field procedure, questionnaire revision, teamwork and the fieldwork plan. In addition, all field staff was trained at anthropometric measurement (height and weight measurements). On the fourth and fifth days of training, the field staff conducted the sampling and instrument pre-tests in a community close to Phnom Penh with similar conditions to the target villages (but not a treatment-control village).
Data was collected with the use of tablets (computer-assisted personal interviewing; CAPI), using mobile data collection package Survey CTO v2.10. Throughout this stage, regular communication with World Bank staff about fieldwork progress, including daily fieldwork updates via SMS/email as relevant was maintained. All interviews were held in Khmer.
24 interviewers and three reserve interviewers were recruited and trained (the reserve interviewers joined the training, took part in the pre-test and were available to replace interviewers on the field in case of accident or incapacity). During recruitment, preference was given to interviewers with previous experience working with children, to ensure that respondents are comfortable with the interviewers and data collection process. Interviewers were responsible for participating in training, conducting survey instrument pre-testing and revision, and interviewing target household members (caregiver interview and child testing) in the selected eligible households of the target villages.
Data was collected with the use of tablets (computer-assisted personal interviewing; CAPI), using mobile data collection package Survey CTO v2.10. Throughout this stage, regular communication with World Bank staff about fieldwork progress, including daily fieldwork updates via SMS/email as relevant was maintained. All interviews were held in Khmer.
24 interviewers and three reserve interviewers were recruited and trained (the reserve interviewers joined the training, took part in the pre-test and were available to replace interviewers on the field in case of accident or incapacity). During recruitment, preference was given to interviewers with previous experience working with children, to ensure that respondents are comfortable with the interviewers and data collection process. Interviewers were responsible for participating in training, conducting survey instrument pre-testing and revision, and interviewing target household members (caregiver interview and child testing) in the selected eligible households of the target villages.
Data Collectors
| Name |
|---|
| Angkor Research and Consulting Ltd. |
Questionnaires
Questionnaires
Structured household interviews included the:
- Household and caregiver instrument
- Child testing
- Caregiver and child anthropometric data measurement
- Village chief interviews: During the administration of the household survey, the interview with the village chief was conducted.
- Household and caregiver instrument
- Child testing
- Caregiver and child anthropometric data measurement
- Village chief interviews: During the administration of the household survey, the interview with the village chief was conducted.
Data Processing
Data Editing
Data management procedures for this study included:
- Testing of all instruments on Survey CTO v2.10. This included checking all of the items validity and logic patterns (skips, relevance rules, etc.). This stage also ensured that items used as key identifiers (for future merging of datasets) are clearly defined.
- Setting up on-field and in-office QC procedures (re-interviews, comparison of key items in different datasets, etc.). Implementing in-office procedures in order to identify and correct data inconsistencies and errors. Error reports were produced to this end.
- Setting up daily upload/download procedures and making sure that data is well received every day. Field work progress reports were produced to this end.
- Cleaning/labeling final dataset
Data validation and quality control took place during every step of the survey process, with mechanisms built into the survey design itself, data collection and data reporting processes. Thus, a range of tools was built into the data entry system to enable validation of data both at point of entry and during reporting stage. Unique identifiers were developed for each questionnaire in advance, to assist with datasets merging and longitudinal tracking.
Quality control procedures: During data collection, frequent checks of the data entry system were undertaken, as well as ongoing comparison of re-interviews, to ensure that data is accurately recorded by interviewers and the system is functioning as designed. After completion of data collection, the complete database was “cleaned” to check for inconsistent or missing values, incorrect skips, and validation errors. In addition to the in-system validation rules mentioned here before, the following QC procedures were implemented:
- Interview Summary: A summary of critically important items was displayed as in-system feature at the end of the interview. These items were mostly used for the dataset merging and needed to be exactly identical between the household/caregiver and the child systems. Interviewers and Field Editors made sure that the same merging information was recorded for both systems.
- Interview observations: The Field Editor or the Field Supervisor randomly selected an Interviewer in their team and joined the interview at any random point. They observed whether the Interviewer actually implemented the interview techniques agreed upon during the training: respect of the question exact and accurate wording, following conversational or standardized techniques on the relevant items (defining or not difficult notions/words to help the respondent answering the question), accurately recording respondent answers into the tablet system (Survey CTO v2.10), following ethical policies, etc.
- Re-interviews: The Field Editor randomly selected a household, from those with who an interview was completed. He/she then re-interviewed this household, asking once again a selection of 15-20 items (chosen because of their critical importance: items used for merging, items used to assess household eligibility, filter questions, etc.) for a maximum of five minutes. Stored in a separate dataset, this data was then compared against the actual initial interview data, back in office, by the Data QC Supervisor. Discrepancies were inquired into and the Data QC Supervisor called the respondent back to obtain the final correct answer. Observations and re-interviews concerned a minimum of 20% of the cases (around 5 households per village).
- Time stamps: In-system section time stamps were analyzed. They allowed the Data QC Supervisor and the Data Manager to identify potential issues (if a section/interview took seemingly significantly more time than the average) and to help assessing fieldwork progress and forecast fieldwork completion.
At completion of the data collection, (potential) data entry of paper forms and reconciliation processes, a draft database was produced, accompanied by a codebook and will be cleaned and labelled using Stata 13.1 do-files. The database was finalized based on feedback from the WB research team.
Qualitative data (as necessary: Concurrent with the quantitative data processing, any qualitative data (open-ended data from household and individual interviews) was translated into English by experienced Khmer-English translators.
- Testing of all instruments on Survey CTO v2.10. This included checking all of the items validity and logic patterns (skips, relevance rules, etc.). This stage also ensured that items used as key identifiers (for future merging of datasets) are clearly defined.
- Setting up on-field and in-office QC procedures (re-interviews, comparison of key items in different datasets, etc.). Implementing in-office procedures in order to identify and correct data inconsistencies and errors. Error reports were produced to this end.
- Setting up daily upload/download procedures and making sure that data is well received every day. Field work progress reports were produced to this end.
- Cleaning/labeling final dataset
Data validation and quality control took place during every step of the survey process, with mechanisms built into the survey design itself, data collection and data reporting processes. Thus, a range of tools was built into the data entry system to enable validation of data both at point of entry and during reporting stage. Unique identifiers were developed for each questionnaire in advance, to assist with datasets merging and longitudinal tracking.
Quality control procedures: During data collection, frequent checks of the data entry system were undertaken, as well as ongoing comparison of re-interviews, to ensure that data is accurately recorded by interviewers and the system is functioning as designed. After completion of data collection, the complete database was “cleaned” to check for inconsistent or missing values, incorrect skips, and validation errors. In addition to the in-system validation rules mentioned here before, the following QC procedures were implemented:
- Interview Summary: A summary of critically important items was displayed as in-system feature at the end of the interview. These items were mostly used for the dataset merging and needed to be exactly identical between the household/caregiver and the child systems. Interviewers and Field Editors made sure that the same merging information was recorded for both systems.
- Interview observations: The Field Editor or the Field Supervisor randomly selected an Interviewer in their team and joined the interview at any random point. They observed whether the Interviewer actually implemented the interview techniques agreed upon during the training: respect of the question exact and accurate wording, following conversational or standardized techniques on the relevant items (defining or not difficult notions/words to help the respondent answering the question), accurately recording respondent answers into the tablet system (Survey CTO v2.10), following ethical policies, etc.
- Re-interviews: The Field Editor randomly selected a household, from those with who an interview was completed. He/she then re-interviewed this household, asking once again a selection of 15-20 items (chosen because of their critical importance: items used for merging, items used to assess household eligibility, filter questions, etc.) for a maximum of five minutes. Stored in a separate dataset, this data was then compared against the actual initial interview data, back in office, by the Data QC Supervisor. Discrepancies were inquired into and the Data QC Supervisor called the respondent back to obtain the final correct answer. Observations and re-interviews concerned a minimum of 20% of the cases (around 5 households per village).
- Time stamps: In-system section time stamps were analyzed. They allowed the Data QC Supervisor and the Data Manager to identify potential issues (if a section/interview took seemingly significantly more time than the average) and to help assessing fieldwork progress and forecast fieldwork completion.
At completion of the data collection, (potential) data entry of paper forms and reconciliation processes, a draft database was produced, accompanied by a codebook and will be cleaned and labelled using Stata 13.1 do-files. The database was finalized based on feedback from the WB research team.
Qualitative data (as necessary: Concurrent with the quantitative data processing, any qualitative data (open-ended data from household and individual interviews) was translated into English by experienced Khmer-English translators.
Access policy
Contacts
| Name | Affiliation | |
|---|---|---|
| Deon Filmer | World Bank | dfilmer@worldbank.org |
| Adrien Bouguen | University of Mannheim | bouguen@uni-mannheim.de |
Disclaimer and copyrights
Disclaimer
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Copyright
(c) 2016, The World Bank
Metadata production
DDI Document ID
DDI_KHM_2016_ECCD-BL_v01_M_WB
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Economics Data Group | DECDG | The World Bank | Documentation of the study |
Date of Metadata Production
2017-05-25
DDI Document version
Version 01 (May 2017).