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QUANTITATIVE DATA ANALYSIS

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QUANTITATIVE DATA ANALYSIS

From18-04-2019 Locationna Hoursna Educationna

2. Description of the project being studied

The overall objective of the SaHA-2 project is ‘improved social cohesion through sports and play to support peaceful co-existence and youth development in vulnerable communities’.

The project’s conceptual framework, which can be seen as a theory of change for the project, is based on the premise that structured activities implemented in a safe ‘relational’ space and in a supportive environment, can develop essential life skills that will enable children and youth to develop attitudes supportive of social cohesion and collaborative behaviors. When practiced in the teams, these behaviors and attitudes will help the emergence of social capital, which underpins cohesive inter- and intra-group relations.

A Proof of Concept (PoC) study has been designed for this project to assess the outcome of SaHA’s integrated football and life skills sessions in relation to increased social cohesion among children and youth in vulnerable communities in Lebanon. Within the context of the Proof of Concept research, a baseline and endline studies have been designed, using a quasi-experimental design with intervention and control groups.  

The Proof of Concept aims to respond to the following research questions:

Q1. Do project beneficiaries display significant differences in attitudes and behaviours as a result of the intervention compared to peers who did not participate in the project activities? (Individual level)

-          Are there significant differences in attitudes and behaviours of children and youth across locations, with regards to rural/ urban environment, and local leadership (actions and statements of local leaders on social cohesion)?

-          Are there significant differences in the intervention impact on attitudes and behaviours of Lebanese, Syrian and Palestinian children?

-          Which of the coaches’ skills and attitudes are most essential in bringing about change in children?

Q2. Do project beneficiaries demonstrate a significant difference in social capital before and after the intervention/ compared to peers who did not participate in the project activities? (Group level)

-          Are there significant differences in social capital across locations, with regards to rural/urban environment, and local leadership?

-          Are there significant differences in the intervention impact on social capital of Lebanese, Syrian and Palestinian children, and on Lebanese, Syrian and Palestinian parents?

-          Which activities and approaches applied by coaches are most essential in building social capital, and particularly bridging social capital?

Q3. Is there significant evidence of change in social cohesion in the target communities as a result of the intervention? (Community level)

-          Is there correlation between increased social capital and increased social cohesion in the target communities?

-          To what extent can the intervention contribute to social cohesion in different contexts (i.e. areas with higher tensions vs. areas with lower tensions, areas with higher concentration of refugees vs. lower concentration, areas with ITSs vs areas with urban displacement only)?

-          Which aspects of the programme are most effective in strengthening social cohesion?

 

 

 

3. Consultancy Purpose

A data analyst/statistician is needed for quantitative data analysis of the data collected with 756 boys and girls (Aged 12 to 17 years old) in Beirut-Mt. Lebanon, North and South Areas, using the SAHA PoC Children Survey tool as part of the PoC Baseline study. The data analyst will also be required to conduct quantitative data analysis for the children surveys to be collected at endline (expected deadline August 2019) with the same sample. The data analyst is expected to develop a full quantitative analysis plan based on the preliminary plan in Annex A, conduct data cleaning and analysis, and draft quantitative data analysis reports (one for baseline data and one for endline data) based on a pre-determined template. All analyses need to be carried out on IBM SPSS Statistics software.

Note: Data collection, data entry and qualitative data analysis are being carried out by a separate consultancy entity, and are not required within the current TORs.

 

4. Responsibilities, tasks and deliverables

The consultancy will include 2 phases of data analysis. Phase 1 is relevant to the baseline study, and extends from May 15 to May 25, 2019 and phase 2 pertains to the endline study, and extends from August 15 to August 31, 2019*.

*As a note, the dates included in the current TORs include the overall timeframe for the quantitative analysis but do not assume full working days. Also, some dates are subject to change based on field data collection plans.

The overall tasks and deliverables for the data analyst/statistician can be summarized in the table below:

Responsibilities and tasks Deliverables Expected deadline
  1. Review necessary project documentation and proof of concept key documents including:
-          Proof of Concept Methodology and Conceptual Framework document,
-          Proof of Concept Baseline draft document
-          PoC Children Survey Tool
-          PoC Mastersheet for Children
-          PoC Preliminary Data Analysis Plan (Annex A)
-          Life Skills tool and score key
 
  May 21, 2019
  1. Develop a comprehensive quantitative data analysis plan, based on the preliminary plan in Annex A and discussions with the consortium M&E working group
Final quantitative data analysis plan May 21, 2019
  1. Conduct data cleaning and transferring datasets from Excel to SPSS
Clean datasets on SPSS Baseline:
May 22, 2019
Endline:
August 31, 2019
  1. Conduct data analysis as per the final comprehensive data analysis plan based on Annex A on baseline and endline data
Analysis outputs on SPSS Baseline:
May 22, 2019
Endline:
August 31, 2019
  1. Present data in tables and other graphical representations as relevant and as discussed in the analysis plan
Relevant tables and graphs included in the baseline and endline reports  
  1. Draft quantitative analysis section of the baseline and endline reports based on a pre-determined template, which includes tables and graphs
Draft Quant analysis section – baseline report Baseline:
May 23, 2019
 
Draft Quant analysis section – endline report Endline:
August 31, 2019
  1. Meet with Proof of Concept researchers (consultants) and Consortium working group to discuss the analysis accordingly
 
   
  1. Finalize quantitative section of the baseline and endline report based on feedback received from the Consortium Working Group
 
Final Quant analysis section – baseline report Baseline:
May 25, 2019
 
Final Quant analysis section – endline report Endline:
August 31, 2019

 

5. Qualifications of the consultant

The data analyst should have the following competencies and experience:

  • Advanced degree in relevant field (e.g. Public Health, Epidemiology or any related technical field) with a background in epidemiology and/or biostatistics
  • Proficiency in statistical analysis using SPSS and Microsoft Excel
  • At least 3 years of progressive proven experience in similar studies and in using quantitative research methodologies and data analysis;
  • Ability to present quantitative data and findings in tables and other graphical presentations which are suitable to technical and non-technical audiences
  • Knowledge of life skills education and social cohesion programming and evaluation is preferable
  • Good analytical and critical thinking;
  • Good writing and reporting skills (English)
  • Ability to deliver with quality, rigour and accuracy in a timely manner
  • Good work ethics

 

6. Proposal submission

Interested Individuals/consultancy teams are requested to submit the following documents:

  • Cover letter/expression of interest
  • CV of the applicant
  • Financial bid (quotation) including the rate per working day for the above-mentioned tasks and the total number of expected days of consultancy work
  • A written sample of a quantitative data analysis report completed by the applicant (or excerpts from it based on authorship rights or copyrights)

 

The proposal must be submitted no later than May 03, 2019. Incomplete proposals will not be considered. Quotations should be included within the range of 1,600-2,600 USD. Competitive budgets will be considered. The following should be clearly stated in the email heading: “SAHA Data Analyst”. Early submissions are encouraged and appreciated. While we thank all applicants for their interest, only short-listed candidates will be contacted.

 

 

 

 

Annex A:

Preliminary Quantitative Data Analysis Plan for SAHA Proof of Concept Study

 

 

 

  1. Data collection and data entry (conducted by Consortium researchers i.e. not requested by data analyst): All data will be collected using the SAHA PoC Children Survey for adolescent boys and girls aged 12-17 [BJ1] [JH2] years old. Data will be entered onto Microsoft Excel (however analysis of data collected will need to be run by the data analyst on IBM SPSS).

 

  1. Data cleaning: Data needs to be cleaned and organized in a way that allows statistical analysis (to be transferred from Excel onto IBM SPSS) (i.e. values assigned to variables, recoding or computation where necessary, recoding of missing answers, etc.). Outcome variables need to be clearly defined and computed based on survey questions, and thresholds/scoring need to be set in place, through discussion with the Consortium M&E Working Group and using the PoC Mastersheet for Children.

 

  1. Data analysis plan and methodology: A comprehensive data analysis plan will need to be developed based on the current preliminary plan. It should be clear and detailed in order to respond to each research questions, while specifying which are the variables being studied, and which are predictor, outcome and covariate variables. It also needs to specify which statistical tests need to be conducted. Data analysis needs to be conducted on IBM SPSS, using a recent software version.

 

  1. Descriptive analysis: Frequencies (n), percentages (%) and confidence intervals, means & standard deviations (where applicable for continuous variables), and for the computed 7 outcome variables:

 

  1. Social Cohesion (with the following sub-constructs: network & contact, perceived threat, acceptance and trust, participation, sense of safety & security)
  2. Behavior (with the following sub-constructs: lack of anti-social behavior, problem solving and cooperation)
  3. Attitude (with the following sub-constructs: attitude on equality and inclusion, parental care & support, acceptance of non-traditional social roles of girls)
  4. Social Capital*
  5. Life Skills (Life skills scores need to be computed based on the Life Skills tool score key).
  6. Safe Space
  7. Positive Role Models & Supportive Environments

* Data on social capital was not collected through the Children Survey at baseline due to a technical issue but will be collected at endline.

  1. Bivariate analysis:

Bivariate analysis for each of the 7 outcome variables listed under D, testing the association with the following predictor variables, at baseline and at endline:

  1. Intervention vs. control
  2. Area (North, South, Beirut/Mt.Lb)
  3. Sex (Female, Male)
  4. Nationality (Lebanese, Syrian, Palestinian)
  5. Urban vs. rural (**at endline only)
  6. High tension vs. low tension areas (** at endline only)

 

Statistical significance tests need to be carried out on a bivariate level (i.e. using crosstabs, t-test or Z-test or ANOVA as relevant), and p-values and chi-square coefficients need to be specified as relevant.

 

  1. Multivariate analysis: multivariate (regression or other as relevant) analysis needs to be conducted to control for co-variates and/or confounding factors such as age and exposure to intervention at baseline (participation in phase 2 sessions prior to baseline data collection).

 

  1. Data presentation and visualization: Narrative quantitative analysis reports for baseline and endline data will need to be developed summarizing data analysis findings, including relevant data tables and graphs.

 

  1. Data interpretation, discussion and conclusion: interpretation of findings and triangulation with qualitative data from the baseline and interpretation study will be conducted by Consortium researchers i.e. not requested by data analyst.

 [BJ1]On page 5 it states 13-17.

 [JH2]

   
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