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  1. M&E Library/
  2. Topics/
  3. Analysis
Topic Hub

Analysis

Quantitative and qualitative analysis for M&E programs. Cleaning, coding, descriptive and inferential statistics, thematic analysis, mixed methods, and how to turn collected data into defensible findings.

How Do I Choose?· 3

Side-by-side comparisons, decision trees, and practical guidance for common M&E decisions.

How Do I Choose?

Side-by-side comparisons, decision trees, and practical guidance for common M&E decisions.

How to Clean Your Dataset Before Analysis
A step-by-step checklist for cleaning M&E data after collection. Duplicate detection, outlier identification, skip logic validation, consistency checks, and cleaning log documentation.
How to Choose
Qualitative vs Quantitative vs Mixed Methods
Qualitative, quantitative, and mixed methods are not a quality ranking. They answer different questions. Here's when to use each, how to combine them, and what integration actually looks like.
Comparison
Surveys vs Interviews vs Focus Groups
The three most common M&E data collection methods, compared. Surveys tell you how many, interviews tell you why, focus groups tell you what people agree on.
Comparison

Reference Library· 11

Overviews (1)

Data Management
The systematic processes for collecting, storing, securing, and maintaining data quality throughout the data lifecycle to ensure information is accurate, accessible, and usable for decision-making.

Quick Reference (10)

BiasCausal InferenceConfounding VariablesContent AnalysisCounterfactualQualitative DataQuantitative DataReliabilityTriangulationValidity (Internal & External)

Explore Other Topics

Evaluation
Design, commission, and manage evaluations
29 entries · 11 guides
Design
Theories of change, logframes, MEL plans, proposals, and design artifacts
24 entries · 8 guides
Data Collection & Quality
Methods, tools, DQAs, cleaning, and validation for field data
17 entries · 5 guides
Indicators
Select, design, track, and report on indicators
13 entries · 2 guides
Sampling
Sample size, sampling methods, design effect, and common mistakes
7 entries · 4 guides