Module 1: Foundational Concepts in Programme Evaluation

• Definitions: Monitoring, Evaluation, Impact, and Outcome
• The role and timing of different evaluation types (formative, process, summative, impact)
• Causality and attribution: understanding the Counterfactual challenge
• Introduction to the core principles of the D-I-E methodology (Design, Implement, Evaluate)
• Ethical considerations in program evaluation and data collection

Practical session: Reviewing an existing programme and drafting three key evaluation questions (Process, Outcome, and Impact).

Module 2: Logic Models, Theory of Change, and Evaluation Questions

• Developing a comprehensive Theory of Change (ToC) model
• Differentiating between inputs, activities, outputs, outcomes, and impact
• Identifying causal pathways, assumptions, and critical external factors
• Translating the ToC into measurable indicators and metrics

• Refining evaluation questions to align with the proposed ToC

Practical session: Designing a full Logic Model and Theory of Change for a hypothetical development intervention.

Module 3: Choosing the Right Impact Evaluation Design and Counterfactuals

• Overview of Experimental Designs (RCTs) and their requirements
• Overview of Quasi-Experimental Designs (DiD, RDD) and their use cases
• Overview of Non-Experimental Designs (PSM, simple comparisons) and limitations

• The importance of baseline and endline data collection timing

• Assessing the Feasibility of different designs based on budget and context constraints

Practical session: Analyzing three case studies and justifying the most appropriate impact evaluation design for each, based on its context.

Module 4: Data Collection, Quality Assurance, and Introduction to Statistical Software

• Designing quantitative instruments: survey structure and cognitive load
• Developing a robust Data Quality Assurance (DQA) plan
• Data entry, cleaning, and preparation principles for IE analysis
• Introduction to Stata (or R): basic commands, data import, and descriptive statistics

• Data handling: merging, appending, and reshaping longitudinal data

Practical session: Cleaning, labeling, and merging simulated baseline and endline survey data using Stata or R, followed by generating descriptive statistics.

Module 5: Non-Experimental Methods: Propensity Score Matching (PSM)

• The concept of Selection Bias and why simple comparisons fail
• The statistical purpose and underlying assumptions of PSM
• Steps in PSM implementation: propensity score estimation, matching algorithms, and balance checking
• Identifying the Common Support Region and trimming observations
• Interpreting the Average Treatment Effect on the Treated (ATT)

Practical session: Implementing Propensity Score Matching (PSM) in Stata/R on a dataset and assessing covariate balance before and after matching.

Module 6: Quasi-Experimental Methods: Difference-in-Differences (DiD)

• The fundamental concept of the DiD design and its requirement for panel data

• The crucial Parallel Trends Assumption and methods to test it
• Setting up the DiD regression model with interaction terms
• Staggered adoption DiD designs and handling multiple treatment groups

• Advantages and limitations of DiD over simpler comparison methods

Practical session: Applying the Difference-in-Differences (DiD) regression method to a two-period panel data set and interpreting the causal coefficient.

Module 7: Experimental Methods: Randomized Control Trials (RCTs)

• Principles of randomization: individual vs. cluster randomization

• Calculating Statistical Power and determining required sample size
• Addressing practical challenges: ethical considerations, attrition, and contamination
• Analysis of RCT data using simple OLS regression with fixed effects
• Introduction to Encouragement Designs and Instrumental Variables (IV)

Practical session: Calculating the Required Sample Size for a cluster-randomized trial using given parameters (Minimum Detectable Effect, significance, and power).

Module 8: Advanced Data Analysis: Regression Analysis and Treatment Heterogeneity

• Ordinary Least Squares (OLS) regression for causal impact estimation
• Addressing endogeneity and omitted variable bias through control variables
• Analyzing Treatment Heterogeneity: examining differential impacts across subgroups (e.g., gender, location)

• Handling clustered and non-independent observations (Clustered Standard Errors)
• Interpreting the results of complex interaction terms

Practical session: Running a multivariate regression model to estimate programme impact and testing for significant Treatment Heterogeneity across two key subgroups.

Module 9: Integrating Qualitative Data and Mixed-Methods Evaluation

• The complementary role of qualitative data in impact evaluation (process tracing, context)
• Designing qualitative data collection tools (In-depth Interviews, Focus Group Discussions)
• Strategies for integrating QL and QN data (triangulation, embedded design)

• Basic principles of Qualitative Data Analysis (coding and thematic analysis)
• Using qualitative findings to explain the "why" behind quantitative impact results

Practical session: Developing a structured coding framework for a set of sample interview transcripts and linking qualitative themes to quantitative findings.

Module 10: Reporting, Dissemination, and Utilization of Evaluation Findings

• Structuring the final Impact Evaluation Report (technical and executive summary)
• Developing clear, evidence-based recommendations for policy and programming
• Best practices for visualizing complex statistical results effectively
• Strategies for presenting and communicating findings to technical and non-technical stakeholders
• Planning for evaluation Utilization and ensuring findings inform future design

Practical session: Drafting an Executive Summary and key policy recommendations based on a simulated set of final impact evaluation results.

Requirements:

• Participants should be reasonably proficient in English.
• Applicants must live up to Armstrong Global Institute admission criteria.

Terms and Conditions

1. Discounts: Organizations sponsoring Four Participants will have the 5th attend Free

2. What is catered for by the Course Fees: Fees cater for all requirements for the training – Learning materials, Lunches, Teas, Snacks and Certification. All participants will additionally cater for their travel and accommodation expenses, visa application, insurance, and other personal expenses.

3. Certificate Awarded: Participants are awarded Certificates of Participation at the end of the training.

4. The program content shown here is for guidance purposes only. Our continuous course improvement process may lead to changes in topics and course structure.

5. Approval of Course: Our Programs are NITA Approved. Participating organizations can therefore claim reimbursement on fees paid in accordance with NITA Rules.

Booking for Training

Simply send an email to the Training Officer on training@armstrongglobalinstitute.com and we will send you a registration form. We advise you to book early to avoid missing a seat to this training.

Or call us on +254720272325 / +254725012095 / +254724452588

Payment Options

We provide 3 payment options, choose one for your convenience, and kindly make payments at least 5 days before the Training start date to reserve your seat:

1. Groups of 5 People and Above – Cheque Payments to: Armstrong Global Training & Development Center Limited should be paid in advance, 5 days to the training.

2. Invoice: We can send a bill directly to you or your company.

3. Deposit directly into Bank Account (Account details provided upon request)

Cancellation Policy

1. Payment for all courses includes a registration fee, which is non-refundable, and equals 15% of the total sum of the course fee.

2. Participants may cancel attendance 14 days or more prior to the training commencement date.

3. No refunds will be made 14 days or less before the training commencement date. However, participants who are unable to attend may opt to attend a similar training course at a later date or send a substitute participant provided the participation criteria have been met.

Tailor Made Courses

This training course can also be customized for your institution upon request for a minimum of 5 participants. You can have it conducted at our Training Centre or at a convenient location. For further inquiries, please contact us on Tel: +254720272325 / +254725012095 / +254724452588 or Email training@armstrongglobalinstitute.com

Accommodation and Airport Transfer

Accommodation and Airport Transfer is arranged upon request and at extra cost. For reservations contact the Training Officer on Email: training@armstrongglobalinstitute.com or on Tel: +254720272325 / +254725012095 / +254724452588

Vvv