1989
DOI: 10.2307/2579563
|View full text |Cite
|
Sign up to set email alerts
|

The Comparative Method: Moving beyond Qualitative and Quantitative Strategies.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
4
1

Citation Types

1
143
0
8

Year Published

2007
2007
2024
2024

Publication Types

Select...
6

Relationship

0
6

Authors

Journals

citations
Cited by 104 publications
(152 citation statements)
references
References 0 publications
1
143
0
8
Order By: Relevance
“…The use of qualitative comparative analysis (QCA) as part of an evidence synthesis for complex health‐related interventions is an emerging area of development 1,4,6 . QCA is a case‐oriented analytic method that uses mathematical set theory to identify complex causal relationships 7–13 . It is particularly useful for configural research questions, which are research questions designed to elucidate under what circumstances a phenomenon is found (or not found).…”
Section: Introductionmentioning
confidence: 99%
See 3 more Smart Citations
“…The use of qualitative comparative analysis (QCA) as part of an evidence synthesis for complex health‐related interventions is an emerging area of development 1,4,6 . QCA is a case‐oriented analytic method that uses mathematical set theory to identify complex causal relationships 7–13 . It is particularly useful for configural research questions, which are research questions designed to elucidate under what circumstances a phenomenon is found (or not found).…”
Section: Introductionmentioning
confidence: 99%
“…Traditional methods of quantitative evidence synthesis (e.g., meta‐analysis) and quantitative approaches to explaining heterogeneity (e.g., meta‐regression) across a body of evidence are limited in complex interventions because heterogeneity in population, setting, or outcomes often preclude producing a summary effect estimate, 1 and assumptions about linear and additive effects of multiple intervention components may not be valid 2 . Thus, QCA can be useful for identifying complex (i.e., nonlinear and nonadditive) relationships that variable‐oriented methods may miss 7–9,14 …”
Section: Introductionmentioning
confidence: 99%
See 2 more Smart Citations
“…QCA does not require a high sample size. It can use 15-80 sample sizes and has a greater advantage in the study of small and medium-sized samples whose variables are composed mainly of binary forms (Ragin, 1987). According to Marx et al (2013), 5% was set as the threshold.…”
Section: Selection Of Typical Casesmentioning
confidence: 99%