Coincidence Analysis (CNA)

Coincidence Analysis (CNA) is a configurational comparative method (CCM) of causal inference and data analysis that is custom-built for multi-outcome structures.

This page presents some relevant literature on CNA and will inform about new developments, seminars, workshops etc. For more see the official CNA website at the University of Bergen.

Training

Chicago (in-person), May 20 - 23, 2024 Introduction to Causal Data Analysis and Modeling with Coincidence Analysis
Prague (in-person), May 15 - 18, 2023, Introduction to Causal Data Analysis and Modeling with Coincidence Analysis
Bergen (in-person), May 30 - June 2, 2022, Introduction to Causal Data Analysis and Modeling with Coincidence Analysis
Indianapolis (via Zoom), Aug. 3-5, 2021, Introduction to Causal Modeling with Coincidence Analysis
Indianapolis (via Zoom), 2020, Advanced Topics in Configurational Causal Data Analysis
Indianapolis (via Zoom), 2020, Beginners’ Introduction to Configurational Causal Data Analysis
Arlington, 2019: Coincidence Analysis (CNA) Workshop at the D&I Conference
Indianapolis, 2017: Configurational Research with QCA and CNA
Konstanz, 2016: Configurational Research with QCA and CNA
Geneva, 2015: Configurational Research with QCA and CNA

Software

Base package cna

The cna package provides all the base functionalities required to analyze data by means of CNA.

On 06/07/2024, update 3.6.0 of the cna R-package has been released on CRAN.
On 12/21/2023, update 3.5.6 of the cna R-package has been released on CRAN.
On 08/10/2023, update 3.5.4 of the cna R-package has been released on CRAN.
On 03/09/2023, update 3.5.1 of the cna R-package has been released on CRAN.
On 02/17/2023, version 3.5.0 of the cna R-package has been released on CRAN.
On 08/07/2022, version 3.4.0 of the cna R-package has been released on CRAN.
On 12/17/2021, version 3.3.0 of the cna R-package has been released on CRAN.
On 06/14/2021, version 3.2.0 of the cna R-package has been released on CRAN.
On 05/28/2021, version 3.1.0 of the cna R-package has been released on CRAN.
On 11/06/2020, update 3.0.1 has been released on CRAN.
On 09/13/2020, version 3.0.0 of the cna R-package has been released on CRAN.
On 05/20/2020, update 2.2.3 has been released on CRAN.
On 06/12/2019, update 2.2.2 has been released on CRAN.
On 08/09/2019, update 2.2.1 has been released on CRAN.
On 04/13/2019, update 2.2.0 has been released on CRAN.
On 06/13/2018, update 2.1.1 has been released on CRAN.
On 06/01/2018, version 2.1.0 of the cna R-package has been released on CRAN.

Add-on package cnaOpt

The cnaOpt package provides various functions for optimizing consistency and coverage scores of models of configurational comparative methods as CNA and QCA.

On 07/08/2022, update 0.5.2 has been released on CRAN.
On 12/17/2021, update 0.5.0 has been released on CRAN.
On 09/14/2020, update 0.2.0 has been released on CRAN.
On 09/12/2019, update 0.1.1 has been released on CRAN.
On 21/10/2019, version 0.1.0 of the cnaOpt R-package has been released on CRAN.

Add-on package frscore

The frscore package provides functions for calculating the robustness of CNA/CCM models.

On 06/11/2024, update 0.4.1 has been released on CRAN.
On 04/25/2024, update 0.4.0 has been released on CRAN.
On 04/28/2023, update 0.3.1 has been released on CRAN.
On 05/20/2022, update 0.2.0 has been released on CRAN.
On 01/10/2022, update 0.1.1 has been released on CRAN.
On 07/22/2021, version 0.1.0 of the frscore R-package has been released on CRAN.

Add-on package causalHyperGraph

The causalHyperGraph package provides functions for graphically visualizing CNA/CCM models.

On 03/21/2024, version 0.1.0 of the frscore R-package has been released on CRAN.

Literature

Methodological

The details of the most recent version of CNA, which is implemented in the cna package, are described here:

M. Baumgartner and M. Ambühl (2021), cna: An R Package for Configurational Causal Inference and Modeling. R package vignette: The Comprehensive R Archive Network. https://cran.r-project.org/web/packages/cna/vignettes/cna_vignette.pdf.
M. Baumgartner and M. Ambühl (2020), Causal Modeling with Multi-Value and Fuzzy-Set Coincidence Analysis, Political Science Research and Methods 8, 526-542, doi: 10.1017/psrm.2018.45. Replication material at https://doi.org/10.7910/DVN/YIEAF1; [penultimate draft]

Short and informal introductions to configurational causal modeling are provided in the following papers:

von Thiele Schwarz, U., Sørensen, O. H., Tafvelin, S., & Roczniewska, M. (2024), Complexity embraced: a new perspective on the evaluation of organisational interventions, Work & Stress, 1–7, doi:10.1080/02678373.2024.2349000
Whitaker, R.G., N. Sperber, M. Baumgartner, et al. (2020), Coincidence analysis: a new method for causal inference in implementation science, Implementation Science 15, 108. doi: 10.1186/s13012-020-01070-3

The following paper provides a theoretical introduction the functions of the cnaOpt package:

M. Baumgartner and M. Ambühl (2021), Optimizing Consistency and Coverage in Configurational Causal Modeling, Sociological Methods & Research. [penultimate draft]; Replication material.

The following paper introduces the robustness measure implemented in the frscore package:

V.P. Parkkinen and M. Baumgartner (2023), Robustness and Model Selection in Configurational Causal Modeling, Sociological Methods & Research 52(1), 176–208. doi: 10.1177/0049124120986200 [penultimate draft]

This paper uncovers shortcomings of consistency and coverage and introduces two additional evaluation measures:

L. De Souter (2024), Evaluating Boolean relationships in Configurational Comparative Methods, Journal of Causal Inference, vol. 12, no. 1, 2024.

This paper investigates the impact of data imbalances on CNA’s performance:

M. Swiatczak and M. Baumgartner (2024), Data Imbalances in Coincidence Analysis: A Simulation Study, Sociological Methods & Research, doi: 10.1177/00491241241227039.

These papers compare CNA and QCA:

M. Swiatczak (2022), Different Algorithms, Different Models, Quality & Quantity, 56:1913–1937
T. Haesebrouck and E. Thomann (2022), Introduction: Causation, Inferences, and Solution Types in Configurational Comparative Methods, Quality & Quantity, 56:1867–1888.

This paper compares CNA and Logic Regression:

M. Baumgartner and C. Falk (2023), Configurational Causal Modeling and Logic Regression, Multivariate Behavioral Research 58:2, 292-310. [penultimate draft]; [replication material]

Older CNA versions are introduced/discussed here:

M. Baumgartner and A. Thiem (2015), Identifying Complex Causal Dependencies in Configurational Data with Coincidence Analysis, The R Journal 7, 176-184. [penultimate draft]
M. Baumgartner (2013), Detecting Causal Chains in Small-N Data, Field Methods 25, 3-24. [penultimate draft]
M. Baumgartner (2009), Uncovering Deterministic Causal Structures: A Boolean Approach, Synthese 170, 71-96. [Springer Nature SharedIt] [penultimate draft]
M. Baumgartner (2009), Inferring Causal Complexity, Sociological Methods & Research 38, 71-101. [penultimate draft]

Applied

Kelley, A.T., M.A. Incze, M. Baumgartner, A.N.C. Campbell, E.V. Nunes , D.O. Scharfstein (2024), Predictors of urine toxicology and other biological specimen missingness in randomized trials of substance use disorders, Drug and Alcohol Dependence, Volume 260, doi: 10.1016/j.drugalcdep.2024.111368.
Duan, Y., Wang, J., Lanham, H.J. et al. (2024), How context links to best practice use in long-term care homes: a mixed methods study, Implement Sci Commun 5, 63, doi:10.1186/s43058-024-00600-0
Barroso, M. B. C., & Moraes, S. M. (2024), Influencing factors of the purchase intention of virtual cosmetic goods in online games. Brazilian Journal of Marketing, 23(2), 580-602, doi:10.5585/remark.v23i2.23369
Haesebrouck, T. (2024), EU Member State Support to Ukraine, Foreign Policy Analysis, Volume 20, Issue 2, orae005, doi: 10.1093/fpa/orae005
Kaye, S., Hood, S., Cragun, D. et al. (2024), Maintaining Family Engagement During Home Visitor Turnover: a Mixed Methods Study of Best Practices, Prevention Science, doi: 10.1007/s11121-024-01669-8
Akerstrom, M., J. Severin, E.J. Miech, E. Wikström, and M. Roczniewska (2024), Reducing sickness absence among public-sector healthcare employees: The difference-making roles of managerial and employee participation, Int Arch Occup Environ Health, doi: 10.1007/s00420-024-02048-0
Johnson, C, AlRasheed, R, Gray, C, Triplett, N, Mbwayo, A, Weinhold, A, Whetten, K, Dorsey, S. (2024), Uncovering determinants of perceived feasibility of TF-CBT through Coincidence Analysis, Implementation Research and Practice, 5, doi:10.1177/26334895231220277.
Chava Pollak, Joe Verghese, Helena M Blumen (2024), Difference-Making Pathways to Frailty Through Social Factors: A Configurational Analysis, The Gerontologist, Volume 64, Issue 6, gnad173, doi:10.1093/geront/gnad173
Roczniewska M, Tafvelin S, Nielsen K, von Thiele Schwarz U, Miech EJ, Hasson H, Edwards K, Abildgaard JS, Sorensen OH. (2023), Simple Roads to Failure, Complex Paths to Success: An Evaluation of Conditions Explaining Perceived Fit of an Organizational Occupational Health Intervention, Applied Psychology, doi: 10.1111/apps.12502.
Dean, M, Tezak, A, Johnson, S, Weidner, A, Almanza, D, Pal, T, Cragun, D. (2023), Factors that Differentiate Cancer Risk Management Decisions Among Females with Pathogenic/Likely Pathogenic Variants in PALB2, CHEK2, and ATM, Genetics in Medicine, 25, 100945, doi: 10.1016/j.gim.2023.100945.
Dodge, J.R., Youles, B., Caldararo, J. et al. (2023), Engaging Operational Partners Is Critical for Successful Implementation of Research Products: a Coincidence Analysis of Access-Related Projects in the Veterans Affairs Healthcare System, Journal of General Internal Medicine, doi: 10.1007/s11606-023-08115-5
Salvati ZM, Rahm AK, Williams MS….Cragun D. (2023), A picture Is worth a thousand words: advancing the use of visualization tools in implementation science through process mapping and matrix heat mapping, Implementation Science Communications 4 (2023): 43, doi: 10.1186/s43058-023-00424-4
Knott CL, Miech EJ, Woodward N, Huq M. (2023), The role of organizational capacity in intervention efficacy in a church‑based cancer education program: a configurational analysis, Global Implementation Research and Applications, doi: 10.1007/s43477-023-00089-0
Haesebrouck T. (2023), The populist radical right and military intervention: A coincidence analysis of military deployment votes, International Interactions, doi: 10.1080/03050629.2023.2184815
Adams KK, Miech EJ, Sobieraj DM. (2022), Factors that distinguish opioid withdrawal during induction with buprenorphine microdosing: a configurational analysis, Addiction Science & Clinical Practice, 17(1):55. doi: 10.1186/s13722-022-00336-z.
- This is the second study ever to apply CNA in the field of pharmacy, and draws upon a subset of data from an earlier systematic review.
Rich JA, Miech EJ, Semenza DC, Corbin TJ. (2022), How combinations of state firearm laws link to low firearm suicide and homicide rates: A configurational analysis, Preventive Medicine, doi: 10.1016/j.ypmed.2022.107262.
- The 2nd “geoconfigurational” analysis integrating CNA solutions with maps.
Charns MP, Lerner B , Yakovchenko V, MS, Urech TH, Shin MH, Kim B, Engle RL, Vashi AA. (2022), Achieving transformation to Lean Management Systems in health care, Health Services Research, doi: 10.1111/1475-6773.14072.
- The 1st CNA analysis to be published in HSR, an AcademyHealth journal.
Sperber NR, Miech EJ, Clary AS, Perry K, Edwards-Orr M, Rudolph JL, Van Houtven CH, Thomas KS. (2022), Determinants of inter-organizational implementation success: A mixed-methods evaluation of Veteran Directed Care, Healthcare 10(4), 100653. doi: 10.1016/j.hjdsi.2022.100653.
- First multi-level cna analysis to be published in the literatures for health services research and implementation science.
Womack DM, Miech EJ, Fox NJ, Silvey LC, Somerville AM, Eldredge DH, Steege LM. (2022), Coincidence Analysis: A Novel Approach to Modeling Nurses’ Workplace Experience, Applied Clinical Informatics, (4):794-802. doi: 10.1055/s-0042-1756368.
- First published CNA analysis in medical informatics.
Gwayi-Chore, MC., Aruldas, K., Avokpaho, E. et al. (2022), Defining optimal implementation packages for delivering community-wide mass drug administration for soil-transmitted helminths with high coverage. BMC Health Serv Res 22, 792. doi: 10.1186/s12913-022-08080-5
Miech EJ, Perkins AJ, Zhang Y, Myers LJ, Sico JJ, Daggy J, Bravata DM (2022), Pairing regression and configurational analysis in health services research: modelling outcomes in an observational cohort using a split-sample design. BMJ Open; 12:e061469. doi: 10.1136/bmjopen-2022-061469
Rich JA, Miech EJ, Bilal U, Corbin TJ (2022), How education and racial segregation intersect in neighborhoods with persistently low COVID-19 vaccination rates in Philadelphia, BMC Public Health 22, 1044, doi: 10.1186/s12889-022-13414-3
Mulrooney M, Smith M, Sobieraj D, Shipley B, Miech E. (2022), Factors Influencing Primary Care Organization Commitment to Technical Assistance Services for Clinical Pharmacist Integration Using Configurational Comparative Methods. Journal of the American Pharmacists Association, doi: 10.1016/j.japh.2022.03.019.
Davis MM, Schneider JL, Petrik AF, Miech EJ, Younger B, Escaron AL, Rivelli JS, Thompson JH, Nyongesa D, Coronado GD (2022), Clinic Factors Associated With Mailed Fecal Immunochemical Test (FIT) Completion: The Difference-Making Role of Support Staff. Ann Fam Med. 20(2):123-129. doi: 10.1370/afm.2772.
Rattray, Nicholas, Edward J. Miech, Gala True, Diana Natividad, Brian Laws, Richard M. Frankel, and Marina Kukla (2022), Modeling Contingency in Veteran Community: A Mixed Approach, Journal of Mixed Methods Research, doi: 10.1177/15586898211059616.
Edianto, Achmed, Gregory Trencher, and Kazuyo Matsubae (2022), Why Do Some Countries Receive More International Financing for Coal-Fired Power Plants than Renewables? Influencing Factors in 23 Countries, Energy for Sustainable Development, 66: 177–88, doi: 10.1016/j.esd.2021.12.004.
Winchester, B., Cragun, D., Redlinger-Grosse, K., et al., Zierhut, H. (2022), Application of motivational interviewingstrategies with the extended parallel process model to improve risk communication for parents of children with familial hypercholesterolemia, Journal of Genetic Counseling, doi: 10.1002/jgc4.1554.
Yakovchenko V, Morgan TR, Miech EJ, et al., Rogal SS. (2022) Core implementation strategies for improving cirrhosis care in the Veterans Health Administration, Hepatology, 2022 Feb 6. doi: 10.1002/hep.32395
Knott CL, Miech EJ, Slade J, Woodard N, Robinson-Shaneman BJ, Huq M. (2022) Evaluation of Organizational Capacity in the Implementation of a Church-Based Cancer Education Program. Glob Implement Res Appl. doi: 10.1007/s43477-021-00033-0
Dy SM, Acton RM, Yuan CT, Hsu YJ, Lai AY, Marsteller J, Ye FC, McGee N, Kharrazi H, Mahabare D, Kim J, Gurses AP, Bittle M, Scholle SH. (2022) Association of Implementation and Social Network Factors With Patient Safety Culture in Medical Homes. A Coincidence Analysis, The Journal of Patient Safety, Jan 1;18(1):e249-e256. doi: 10.1097/PTS.0000000000000752
Swiatczak, M.D. (2021), Towards a neo-configurational theory of intrinsic motivation. Motivation and Emotion. doi: 10.1007/s11031-021-09906-1
Miech, E.J., Freitag, M.B., Evans, R.R. et al. (2021), Facility-level conditions leading to higher reach: a configurational analysis of national VA weight management programming. BMC Health Serv Res 21, 797. doi: 10.1186/s12913-021-06774-w
- The first published example of the 7cs solution visualization.
Cohen, D.J., Shannon M. Sweeney, William L. Miller, et al., Miguel Marino (2021), Improving smoking and blood pressure outcomes: The interplay between operational changes and local context, The Annals of Family Medicine, May 2021, 19 (3) 240-248; doi: 10.1370/afm.2668
Schlick CJ, Huang R, Brajcich BC, Halverson, AL, Yang AD, Kreutzer L, et al. (2021), Unbundling bundles: Evaluating the effectiveness of individual colorectal surgical site infection reduction bundle elements in a statewide collaborative, Diseases of the Colon and Rectum, Nov 22 2021; doi: 10.1097/DCR.0000000000002223.
Coury, J., E. Miech, P. Styer et al. (2021), What’s the “secret sauce”? How implementation variation affects the success of colorectal cancer screening outreach. Implement Sci Commun 2, 5 https://doi.org/10.1186/s43058-020-00104-7
Nunes, F. A. S. F., J. S. Freitas (2021), Combination of factors for the presence of the public: a look at the lower levels of football in Minas Gerais. Revista Intercontinental de Gestão Desportiva, 11 (e1122), 1-11. doi: 10.51995/2237-3373.v11i1e110022
Petrik, A., B. Green, J. Schneider et al. (2020), Factors influencing implementation of a colorectal cancer screening improvement program in community health centers: an applied use of configurational comparative methods, Journal of General Internal Medicine, doi: 10.1007/s11606-020- 06186-2.
Hickman, S. E., E. Miech et al. (2020), Identifying the Implementation Conditions Associated With Positive Outcomes in a Successful Nursing Facility Demonstration Project , The Gerontologist, doi: 10.1093/geront/gnaa041
Yakovchenko, V., E. Miech et al. (2020), Strategy Configurations Directly Linked to Higher Hepatitis C Virus Treatment Starts. An Applied Use of Configurational Comparative Methods, Medical Care 58(5), p. e31-e38, doi: 10.1097/MLR.0000000000001319
- Paper about configurations of “implementation strategies”. It includes the first published reference to using E. Miech’s msc routine for data reduction.
Moret, W. and L. Lorenzetti (2020), Realistic expectations: exploring the sustainability of graduation outcomes in a program for children affected by HIV in Kenya’s Northern Arid Lands. Vulnerable Children and Youth Studies. doi: 10.1080/17450128.2020.1738022
Haesebrouck, T. (2019), Who follows whom? A coincidence analysis of military action, public opinion and threats, Journal of Peace Research, doi: 10.1177/0022343319854787
Epple. R. and S. Schief (2016), Fighting (for) gender equality: the roles of social movements and power resources, Interface: a journal for and about social movements, Vol. 8, No.2., 394- 432.
Baumgartner, M. and R. Epple (2014), A Coincidence Analysis of a Causal Chain: The Swiss Minaret Vote, Sociological Methods & Research 43, 280-312. [penultimate draft]

Protocol

Sperber NR, Cragun D, Roberts MC, Bendz LM, Ince P, Gonzales S, Haga SB, Wu RR, Petry NJ, Ramsey L, Uber R. (2022), A Mixed-Methods Protocol to Identify Best Practices for Implementing Pharmacogenetic Testing in Clinical Settings, Journal of Personalized Medicine 12(8), 1313. doi: 10.3390/jpm12081313.
Wasmuth S, Belkiewitz J, Bravata D, Horsford C, Harris A, Smith C, Austin C, Miech E. (2022), Protocol for evaluating external facilitation as a strategy to nationally implement a novel stigma reduction training tool for healthcare providers, Implementation Science Communications 3(1), 88. doi: 10.1186/s43058-022-00332-z.
Cragun D, Beckstead J, Farmer M, Hooker G, Dean M, Matloff E, Reid S, Tezak A, Weidner A, Whisenant JG, Pal T. (2021), IMProving care After inherited Cancer Testing (IMPACT) study: protocol of a randomized trial evaluating the efficacy of two interventions designed to improve cancer risk management and family communication of genetic test results, BMC Cancer 21(1), 1099. doi: 10.1186/s12885-021-08822-4.
Rogal SS, Yakovchenko V, Morgan T, Bajaj JS, Gonzalez R, Park A, Beste L, Miech EJ, Lamorte C, Neely B, Gibson S, Malone PS, Chartier M, Taddei T, Garcia-Tsao G, Powell BJ, Dominitz JA, Ross D, Chinman MJ. (2020), Getting to implementation: a protocol for a Hybrid III stepped wedge cluster randomized evaluation of using data-driven implementation strategies to improve cirrhosis care for Veterans, Implementation Science 15(1), 92, doi: 10.1186/s13012-020-01050-7.
Rahm AK, Cragun D, Hunter JE, Epstein MM, Lowery J, Lu CY, Pawloski PA, Sharaf RN, Liang SY, Burnett-Hartman AN, Gudgeon JM, Hao J, Snyder S, Gogoi R, Ladd I, Williams MS. (2018), Implementing universal Lynch syndrome screening (IMPULSS): protocol for a multi-site study to identify strategies to implement, adapt, and sustain genomic medicine programs in different organizational contexts, BMC Health Services Research 18(1), 824.

Book chapters

D. Cragun (2020), Configurational Comparative Methods, in: Handbook on Implementation Science, eds. P. Nilsen & S. A. Birken, Northampton, MA: Edward Elgar Publishing. doi:10.4337/9781788975995.00034.
- First textbook or handbook in implementation science or health services research to mention CNA as an analytic method.

PhD theses using or on CNA

Lauren Niles, 2022 (Johns Hopkins University, Baltimore, MD) “Effectiveness of Maryland Opioid Treatment Program Response During the COVID-19 Pandemic and National Regulatory Exemption Period.”
Claire Gwayi-Chore, 2022 (University of Washington, Seattle). “Scaling up deworming programs: implementation science approaches to guide the transition from school-based to community-wide mass drug administration for soil-transmitted helminths.” (This multi-method study included a CNA analysis to identify necessary and/or sufficient combinations of intervention delivery activities related to successful implementation of a community-wide public health intervention in three different countries: Benin, India and Malawi.)
Kelly Coates, 2021 (Portland State), “Affecting Absenteeism Through School-Based Health Services Delivery: A Configurational Comparative Methods Study of Oregon’s Public Secondary Schools.” (First standalone use of CNA in an applied analysis in any doctoral-level dissertation in any subject.)
Jessica Dodge, 2021 (USC), “Exploring the Social Determinants of Health in a Population with Similar Access to Healthcare: Experiences from United States Active-Duty Army Wives.” (First formal pairing of CNA and QCA in an applied analysis in any doctoral-level dissertation in any subject.)
Christoph Falk, 2020 (University of Geneva), “Konfigurationales kausales Modellieren. Ein theoretisches Fundament und Verfahren für Kausalanalysen mit crisp-set Konfigurationen.”
Rebecca Whitaker, 2019 (UNC-Chapel Hill), “A Study of Preventable Hospital Utilization Among Medicaid-Insured Pediatric Patients in North Carolina’s Federally Qualified Health Centers.” (First doctoral-level dissertation in the United States to prominently feature CNA in an applied analysis.)
Rui Fernando Correia Ferreira, 2018 (Universidade Federal de Minas Gerais, UFMG/Brazil), “Estratégia de influência: O ganho de vantagens competitivas de empresas em suas relações com o Estado”. [ENG: “Influence strategy: Gaining competitive advantages for companies in their relations with the State”]
Sepheen Byron, 2022 (University of North Carolina – Chapel Hill). “State Medicaid Policy Levers Related to Successful Health Information Exchange Among Providers.”