Data integration is a way of merging these data from different sources through mixed methods. In this article, we discuss how qualitative and quantitative data can be integrated at the study design level, methods, or analysis level.

For those interested in calculating sample sizes by hand, or getting a better understanding of the math behind many sample size calculators, we outline the formulae used to calculate sample sizes.

In this article, we briefly define sample sizes, their importance, and how to calculate them (or how to use a tool to calculate them).

In the evaluation world, scheduling can be a nightmare. This article describes how to use Calendly to schedule interviews in three simple steps.

In this article, we describe what assumptions are in evaluation, explain why you should document assumptions, and describe how to reflect on your assumptions when collecting and analyzing evaluation results. We also provide some practical examples of how to include assumptions in your own evaluations!

This evaluation facilitation series will highlight some of these facilitation activities and how I have applied them over the years. This article focuses on their “Making Metaphors” activity, along with some step-by-step instructions you can use to try it in your own evaluations.

A look at how using different evaluation strategies or frameworks can help you to craft perfect evaluation questions.

A book review of Michael Quinn Patton’s Developmental Evaluation: Applying Complexity Concepts to Enhance Innovation and Use (2011).

So you've successfully gathered the data you need to evaluate your program. But how do you engage stakeholders and partners to ensure a thorough understanding of the results? A data party could be part of the answer!

If you work with data in Excel, whether frequently or infrequently, learning the basics of PivotTables will improve your ability to quickly explore and analyze raw data.

Part of the job of an evaluator is to identify and define metrics for our clients. But what about you? Are you as disciplined when it comes to defining and tracking metrics for your own business?

Recognizing that equitable evaluation is an emerging area of work, this article aims to add to the growing discussion. While it does not include an exhaustive list of issues and strategies, it will help you introduce some changes to your evaluation practice.

The end goal of collecting data is to eventually draw meaningful insights from said data. However, the transition from raw data to meaningful insights is not always a linear path. Data are prone to human-error and this guide will help you correct those errors, as well as provide tips on how to minimize these errors in the future.

As evaluators, we are rarely organizational decision-makers; it is our job to provide those decision-makers with actionable insights. In this article we highlight how you can translate data into meaningful findings, or insights, so you can support decision-makers to drive action within their organizations.

What is the scope of an evaluator’s role: should an evaluator make recommendations? Do we tell programs how to improve? Or do we simply share the data with them and let them draw their own conclusions?

A few years ago, we completed an evaluation for a breast cancer clinic. In honour of Breast Cancer Awareness month, we thought we would highlight some excerpts from that report to help inspire your next evaluation report!

Ideally, our evaluation projects would proceed as planned. But as all project managers know, sometimes things change. Actually, most of the time, things change! In some situations, our evaluation approach can be modified to adapt to the changing context, but in others, we have to say no to scope creep.

It is ideal to have a data dictionary whenever you have quantitative data that will be used and shared by multiple people or groups. Without precise definitions, it is very easy to arrive at different results while using the same dataset. In this article, we focus on how evaluators can (and should) clarify details about the data being used for evaluation. In other words, how and why build an evaluation-specific data dictionary.

In this article, Bonnie shares her account of how to use the RE-AIM framework in your evaluation planning, implementation, and reporting.

I am now finally working on an evaluation that I believe to be true developmental evaluation. The initiative and evaluation is in its early days. Yet, I have already had a very different experience than previous DE (and so-called DE) experiences and learned a number of lessons I’d like to share. In this article, I outline six lessons from my DE experience, including why I think it is true DE.