TY - JOUR
T1 - Testing mechanisms in large-N realistic evaluations
AU - Ravn, Rasmus
PY - 2019
Y1 - 2019
N2 - The concept of generative mechanisms is central to the realistic evaluation approach. They are seen as the drivers of change. Qualitative evidence is especially well suited to unearthing how mechanisms work. However, when evaluating a large-N programme, a realist evaluation might benefit from quantitative tests of the mechanisms hypothesized in the programme theory. Despite this, quantitative tests of mechanisms are rarely applied in realistic evaluation. The purpose of this article is therefore to illustrate how widely used quantitative social science methods can be utilized to test mechanisms in realistic evaluation when evaluating large-N programmes. The proposed methods focus on intra-programme comparison based on the strength of a quantitatively measured mechanism. The article illustrates how simple statistical methods in the form of descriptive statistics and logistic regression can be used to test the influence of mechanisms in generating outcomes.
AB - The concept of generative mechanisms is central to the realistic evaluation approach. They are seen as the drivers of change. Qualitative evidence is especially well suited to unearthing how mechanisms work. However, when evaluating a large-N programme, a realist evaluation might benefit from quantitative tests of the mechanisms hypothesized in the programme theory. Despite this, quantitative tests of mechanisms are rarely applied in realistic evaluation. The purpose of this article is therefore to illustrate how widely used quantitative social science methods can be utilized to test mechanisms in realistic evaluation when evaluating large-N programmes. The proposed methods focus on intra-programme comparison based on the strength of a quantitatively measured mechanism. The article illustrates how simple statistical methods in the form of descriptive statistics and logistic regression can be used to test the influence of mechanisms in generating outcomes.
KW - descriptive statistics
KW - generative mechanisms
KW - intra-programme comparison
KW - logistic regression
KW - mechanisms
KW - realistic evaluation
UR - https://journals.sagepub.com/doi/full/10.1177/1356389019829164
U2 - 10.1177/1356389019829164
DO - 10.1177/1356389019829164
M3 - Journal article
SN - 1356-3890
VL - 25
SP - 171
EP - 188
JO - Evaluation: The International Journal of Theory, Research and Practice
JF - Evaluation: The International Journal of Theory, Research and Practice
IS - 2
ER -