In last week’s #EvalTuesdayTip we discussed the SUN LE 2022 Midline Survey Report, which includes a Qualitative Comparative Analysis (QCA) analyzing the factors associated with changes in childhood stunting (an outcome of poor nutrition) prevalence at district level in Zambia. We followed up with a blog post taking a closer look at QCA, and how the SUN LE team used QCA in combination with Regression Analysis to explain relationships between various nutrition-related variables and the prevalence of stunting in young children.
The SUN LE team used both QCA, which analyzes qualitative and categorical data, and Regression Analysis, which deals with quantitative data, to determine which Zambian households are most at risk for childhood stunting and the specific factors that contribute to an improvement in stunting over time at the district level.
Sometimes analyzing complex datasets requires a creative combination of analytical methods to produce the desired results. To learn more about this particular combination of qualitative and quantitative analytical methods, read the full blog post.
