Quasi-Experimental Design for Medical Studies with the Method of the Fuzzy Pseudo-Control Group
(1) Background: Let the continuous parameter <i>X</i> be a proxy variable for the outcome of an intervention <i>R.</i> Quasi-experimental studies are designed to evaluate the effect of <i>R</i> over <i>X</i> when forming a randomized control group (wit...
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2025-01-01
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| author | Kiril Tenekedjiev Daniela Panayotova Mohamed Daboos Snejana Ivanova Mark Symes Plamen Panayotov Natalia Nikolova |
| author_facet | Kiril Tenekedjiev Daniela Panayotova Mohamed Daboos Snejana Ivanova Mark Symes Plamen Panayotov Natalia Nikolova |
| author_sort | Kiril Tenekedjiev |
| collection | DOAJ |
| description | (1) Background: Let the continuous parameter <i>X</i> be a proxy variable for the outcome of an intervention <i>R.</i> Quasi-experimental studies are designed to evaluate the effect of <i>R</i> over <i>X</i> when forming a randomized control group (without the intervention) is impractical or/and unethical. The most popular quasi-experimental design, the difference-in-differences (DID) method, uses four samples of <i>X</i> values (pre- and post-intervention experimental and pseudo-control groups). DID always quantitatively evaluates the effect of <i>R</i> over <i>X</i>. However, its practical significance is restricted by several (often unprovable) assumptions and by the monotonic preference requirement over <i>X</i>. We propose a novel fuzzy quasi-experimental computational approach that addresses those limitations. (2) Methods: A novel method of the fuzzy pseudo-control group (MFPCG) is introduced and formalized. It uses four fuzzy samples as input, exactly the same as DID. We practically determine and statistically compare the favorability of the differences in X before and after the intervention for the experimental and the pseudo-control groups in case of the more general hill preferences over <i>X</i>. MFPCG applies four modifications of fuzzy Bootstrap procedures to perform each of the nine statistical tests used. The new method does not use the assumptions of DID, but it does not always produce a positive or a negative answer, as MFPCG results are qualitative. It is not a competing methodology; as such, it should be used alongside DID. (3) Results: We assess the effect of annuloplasty that acts in conjunction with revascularization over two continuous parameters that characterize the condition of patients with ischemic heart disease complicated by moderate and moderate-to-severe ischemic mitral regurgitation. (4) Conclusions: The statistical results proved the favorable effect of annuloplasty on two parameters, both for patients with a relatively preserved medical state and patients with a relatively deteriorated medical state. We validate the MFPCG solution of the case study by comparing them with those from the fuzzy DID. We discuss the limitations and adaptability of MFPCG, which should warrant its use in other case studies and domains. |
| format | Article |
| id | doaj-art-0385b28774eb4a859bbf05db8fb577f1 |
| institution | OA Journals |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-0385b28774eb4a859bbf05db8fb577f12025-08-20T02:12:38ZengMDPI AGApplied Sciences2076-34172025-01-01153137010.3390/app15031370Quasi-Experimental Design for Medical Studies with the Method of the Fuzzy Pseudo-Control GroupKiril Tenekedjiev0Daniela Panayotova1Mohamed Daboos2Snejana Ivanova3Mark Symes4Plamen Panayotov5Natalia Nikolova6Department of Computer Sciences, Varna Free University, 9007 Varna, BulgariaDepartment of Cardiovascular Surgery and Angiology, Faculty of Medicine, Medical University—Varna “Prof. Dr. Paraskev Stoyanov”, 9002 Varna, BulgariaDepartment of Computer Sciences, Varna Free University, 9007 Varna, BulgariaDepartment of Information Technology, Nikola Vaptsarov Naval Academy, 9002 Varna, BulgariaAustralian Maritime College, University of Tasmania, Newnham, TAS 7248, AustraliaDepartment of Cardiovascular Surgery and Angiology, Faculty of Medicine, Medical University—Varna “Prof. Dr. Paraskev Stoyanov”, 9002 Varna, BulgariaDepartment of Information Technology, Nikola Vaptsarov Naval Academy, 9002 Varna, Bulgaria(1) Background: Let the continuous parameter <i>X</i> be a proxy variable for the outcome of an intervention <i>R.</i> Quasi-experimental studies are designed to evaluate the effect of <i>R</i> over <i>X</i> when forming a randomized control group (without the intervention) is impractical or/and unethical. The most popular quasi-experimental design, the difference-in-differences (DID) method, uses four samples of <i>X</i> values (pre- and post-intervention experimental and pseudo-control groups). DID always quantitatively evaluates the effect of <i>R</i> over <i>X</i>. However, its practical significance is restricted by several (often unprovable) assumptions and by the monotonic preference requirement over <i>X</i>. We propose a novel fuzzy quasi-experimental computational approach that addresses those limitations. (2) Methods: A novel method of the fuzzy pseudo-control group (MFPCG) is introduced and formalized. It uses four fuzzy samples as input, exactly the same as DID. We practically determine and statistically compare the favorability of the differences in X before and after the intervention for the experimental and the pseudo-control groups in case of the more general hill preferences over <i>X</i>. MFPCG applies four modifications of fuzzy Bootstrap procedures to perform each of the nine statistical tests used. The new method does not use the assumptions of DID, but it does not always produce a positive or a negative answer, as MFPCG results are qualitative. It is not a competing methodology; as such, it should be used alongside DID. (3) Results: We assess the effect of annuloplasty that acts in conjunction with revascularization over two continuous parameters that characterize the condition of patients with ischemic heart disease complicated by moderate and moderate-to-severe ischemic mitral regurgitation. (4) Conclusions: The statistical results proved the favorable effect of annuloplasty on two parameters, both for patients with a relatively preserved medical state and patients with a relatively deteriorated medical state. We validate the MFPCG solution of the case study by comparing them with those from the fuzzy DID. We discuss the limitations and adaptability of MFPCG, which should warrant its use in other case studies and domains.https://www.mdpi.com/2076-3417/15/3/1370fuzzy samplesfuzzy Bootstrap procedures for statistical testsmedical data analysiscluster of tests |
| spellingShingle | Kiril Tenekedjiev Daniela Panayotova Mohamed Daboos Snejana Ivanova Mark Symes Plamen Panayotov Natalia Nikolova Quasi-Experimental Design for Medical Studies with the Method of the Fuzzy Pseudo-Control Group Applied Sciences fuzzy samples fuzzy Bootstrap procedures for statistical tests medical data analysis cluster of tests |
| title | Quasi-Experimental Design for Medical Studies with the Method of the Fuzzy Pseudo-Control Group |
| title_full | Quasi-Experimental Design for Medical Studies with the Method of the Fuzzy Pseudo-Control Group |
| title_fullStr | Quasi-Experimental Design for Medical Studies with the Method of the Fuzzy Pseudo-Control Group |
| title_full_unstemmed | Quasi-Experimental Design for Medical Studies with the Method of the Fuzzy Pseudo-Control Group |
| title_short | Quasi-Experimental Design for Medical Studies with the Method of the Fuzzy Pseudo-Control Group |
| title_sort | quasi experimental design for medical studies with the method of the fuzzy pseudo control group |
| topic | fuzzy samples fuzzy Bootstrap procedures for statistical tests medical data analysis cluster of tests |
| url | https://www.mdpi.com/2076-3417/15/3/1370 |
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