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Journal articles on the topic 'Case control design'

Author: Grafiati
Published: 9 March 2023
Last updated: 22 June 2025

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1

POLIVKA, BARBARA J., and JENNIE T. NICKEL. "Case-Control Design." Nursing Research 41, no. 4 (1992): 250???254. http://dx.doi.org/10.1097/00006199-199207000-00013.

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2

Støer, NC, A. Salim, K. Bokenberger, I. Karlsson, and M. Reilly. "Is the matched extreme case–control design more powerful than the nested case–control design?" Statistical Methods in Medical Research 28, no. 6 (2018): 1911–23. http://dx.doi.org/10.1177/0962280218778624.

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For time-to-event data, the study sample is commonly selected using the nested case–control design in which controls are selected at the event time of each case. An alternative sampling strategy is to sample all controls at the same (pre-specified) time, which can either be at the last event time or further out in time. Such controls are the long-term survivors and may therefore constitute a more ‘extreme’ comparison group and be more informative than controls from the nested case–control design. We investigate this potential information gain by comparing the power of various ‘extreme’ case–control designs with that of the nested case–control design using simulation studies. We derive an expression for the theoretical average information in a nested and extreme case–control pair for the situation of a single binary exposure. Comparisons reveal that the efficiency of the extreme case–control design increases when the controls are sampled further out in time. In an application to a study of dementia, we identified Apolipoprotein E as a risk factor using a 1:1 extreme case–control design, which provided a hazard ratio estimate with a smaller standard error than that of a 2:1 nested case–control design.
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3

Fletcher, Astrid E. "Case-Control Design: Making the Case." American Journal of Ophthalmology 149, no. 4 (2010): 540–42. http://dx.doi.org/10.1016/j.ajo.2009.08.019.

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4

Bangdiwala, Shrikant I. "Basic epidemiology research designs II: case-control design." International Journal of Injury Control and Safety Promotion 26, no. 2 (2019): 200–202. http://dx.doi.org/10.1080/17457300.2019.1591663.

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5

Suissa, Samy. "THE CASE-TIME-CONTROL DESIGN." Epidemiology 6, no. 3 (1995): 248–53. http://dx.doi.org/10.1097/00001648-199505000-00010.

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6

Suissa, Samy. "The Case-Time-Control Design." Epidemiology 9, no. 4 (1998): 441–45. http://dx.doi.org/10.1097/00001648-199807000-00016.

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7

Salton, Aurélio T., Zhiyong Chen, and Minyue Fu. "Improved Servomechanism Control Design – Nonswitching Case." IFAC Proceedings Volumes 44, no. 1 (2011): 8614–19. http://dx.doi.org/10.3182/20110828-6-it-1002.00453.

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8

Wacholder, Sholom. "Design issues in case-control studies." Statistical Methods in Medical Research 4, no. 4 (1995): 293–309. http://dx.doi.org/10.1177/096228029500400403.

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9

Levin, Kate Ann. "Study design V. Case–control studies." Evidence-Based Dentistry 7, no. 3 (2006): 83–84. http://dx.doi.org/10.1038/sj.ebd.6400436.

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10

Pfeiffer, Ruth M., and Nilanjan Chatterjee. "On a Supplemented Case-Control Design." Biometrics 61, no. 2 (2005): 584–90. http://dx.doi.org/10.1111/j.1541-0420.2005.00319.x.

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11

Wacholder, Sholom, Debra T. Silverman, Joseph K. McLaughlin, and Jack S. Mandel. "Selection of Controls in Case-Control Studies: III. Design Options." American Journal of Epidemiology 135, no. 9 (1992): 1042–50. http://dx.doi.org/10.1093/oxfordjournals.aje.a116398.

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12

Ramos, Analía, Lilian Cristina Mendoza, Fernanda Rabasa, Ignasi Bolíbar, Teresa Puig, and Rosa Corcoy. "Case–control studies in diabetes. Do they really use a case–control design?" Acta Diabetologica 54, no. 7 (2017): 631–34. http://dx.doi.org/10.1007/s00592-016-0957-7.

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13

Kicielinski, Kimberly P. "Case-Control Study Design in Neurological Surgery." World Neurosurgery 161 (May 2022): 275–79. http://dx.doi.org/10.1016/j.wneu.2022.03.001.

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14

Santos, Venétia, and Maria Cristina Palmer Lima Zamberlan. "Control Room Ergonomic Design: Brazilian Case Studies." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 44, no. 22 (2000): 530–33. http://dx.doi.org/10.1177/154193120004402208.

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This article intends to present the role of Ergonomics as a support to automation processes on companies by presenting ten ergonomic studies for control rooms in public and private Brazilian companies (Hydroelectric, Petrochemical, Steel, Subway Trains and Cellulose industries). These projects were developed within the last ten years by ERGON Projects involved the diagnoses of the existing situation up to the ergonomic design of the future work situation. The first study was in 1987 and was restricted to the ergonomic work analyses in a hydroelectric plant control room. It was then part of a pioneer ergonomic design activity in our industry. Furthermore, the other studies involved designing for work activity transformation. In this article we will debate on the context of such studies, the boundaries of ergonomic design, the ergonomic methodology evolution and the obtained results.
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15

Harvey, L. A. "Case-control studies: an efficient study design." Spinal Cord 57, no. 1 (2019): 1–2. http://dx.doi.org/10.1038/s41393-018-0234-4.

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16

Miller, A. B. "Dissent A valid nested case-control design?" Journal of Clinical Epidemiology 44, no. 7 (1991): 627–28. http://dx.doi.org/10.1016/0895-4356(91)90022-2.

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17

Liang, Kung-Yee, and Ann E. Pulver. "Analysis of case-control/family sampling design." Genetic Epidemiology 13, no. 3 (1996): 253–70. http://dx.doi.org/10.1002/(sici)1098-2272(1996)13:3<253::aid-gepi3>3.0.co;2-7.

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18

Patel, Rakesh B. "Centralized Control Room Design Using Loop Controller and Supervisory Control & Data Acquisition System (Scada): A Case Study." Indian Journal of Applied Research 4, no. 7 (2011): 200–202. http://dx.doi.org/10.15373/2249555x/july2014/61.

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19

Omair, Aamir. "Selecting the appropriate study design: Case–control and cohort study designs." Journal of Health Specialties 4, no. 1 (2016): 37. http://dx.doi.org/10.4103/1658-600x.173842.

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20

Breslow, N. "Design and Analysis of Case-Control and Case Cohort Studies." American Journal of Epidemiology 163, suppl_11 (2006): S170. http://dx.doi.org/10.1093/aje/163.suppl_11.s170-a.

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21

Doerken, Sam, Maja Mockenhaupt, Martin Schumacher, and Peggy Sekula. "Assessment of the “Case-Chaos” Design as an Adjunct to the Case-Control Design." American Journal of Epidemiology 179, no. 6 (2014): 775–80. http://dx.doi.org/10.1093/aje/kwt310.

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22

Kim, Young Min, and Jongho Im. "Cost-Effective Extreme Case-Control Design Using a Resampling Method." Evolutionary Bioinformatics 15 (January 2019): 117693431983882. http://dx.doi.org/10.1177/1176934319838821.

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Nested case-control sampling design is a popular method in a cohort study whose events are often rare. The controls are randomly selected with or without the matching variable fully observed across all cohort samples to control confounding factors. In this article, we propose a new nested case-control sampling design incorporating both extreme case-control design and a resampling technique. This new algorithm has two main advantages with respect to the conventional nested case-control design. First, it inherits the strength of extreme case-control design such that it does not require the risk sets in each event time to be specified. Second, the target number of controls can only be determined by the budget and time constraints and the resampling method allows an under sampling design, which means that the total number of sampled controls can be smaller than the number of cases. A simulation study demonstrated that the proposed algorithm performs well even when we have a smaller number of controls compared with the number of cases. The proposed sampling algorithm is applied to a public data collected for “Thorotrast Study.”
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23

Alekseev, A. S., S. V. Zamyatin, and V. A. Rudnicki. "Multi-loop control system design." Bulletin of the Polish Academy of Sciences: Technical Sciences 60, no. 3 (2012): 627–30. http://dx.doi.org/10.2478/v10175-012-0074-x.

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Abstract The approach based on a special case of the Laplace transform, which allows to design multi-loop system is considered. The tuning regulators program on the base of this approach is developed. The numerical example is shown.
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24

Wolkewitz, M., J. Beyersmann, M. Palomar-Martinez, et al. "Analysis of Clinical Cohort Data Using Nested Case-control and Case-cohort Sampling Designs." Methods of Information in Medicine 54, no. 06 (2015): 505–14. http://dx.doi.org/10.3414/me14-01-0113.

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SummaryBackground: Sampling from a large cohort in order to derive a subsample that would be sufficient for statistical analysis is a frequently used method for handling large data sets in epidemiological studies with limited resources for exposure measurement. For clinical studies however, when interest is in the influence of a potential risk factor, cohort studies are often the first choice with all individuals entering the analysis.Objectives: Our aim is to close the gap between epidemiological and clinical studies with respect to design and power considerations. Schoenfeld’s formula for the number of events required for a Cox’ proportional hazards model is fundamental. Our objective is to compare the power of analyzing the full cohort and the power of a nested case- control and a case-cohort design.Methods: We compare formulas for power for sampling designs and cohort studies. In our data example we simultaneously apply a nested case-control design with a varying number of controls matched to each case, a case cohort design with varying subcohort size, a random subsample and a full cohort analysis. For each design we calculate the standard error for estimated regression coefficients and the mean number of distinct persons, for whom covariate information is required.Results: The formula for the power of a nested case-control design and the power of a case-cohort design is directly connected to the power of a cohort study using the well known Schoenfeld formula. The loss in precision of parameter estimates is relatively small compared to the saving in resources.Conclusions: Nested case-control and case-cohort studies, but not random subsamples yield an attractive alternative for analyzing clinical studies in the situation of a low event rate. Power calculations can be conducted straightforwardly to quantify the loss of power compared to the savings in the number of patients using a sampling design instead of analyzing the full cohort.
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25

Nylén, Anders, Maria Henningsson, Anton Cervin, and Per Tunestål. "Control Design Based on FMI: a Diesel Engine Control Case Study." IFAC-PapersOnLine 49, no. 11 (2016): 231–38. http://dx.doi.org/10.1016/j.ifacol.2016.08.035.

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26

Wang, Xuan, Yingye Zheng, Majken Karoline Jensen, Zeling He, and Tianxi Cai. "Biomarker evaluation under imperfect nested case‐control design." Statistics in Medicine 40, no. 18 (2021): 4035–52. http://dx.doi.org/10.1002/sim.9012.

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27

Prentice, Ross L. "On the Design of Synthetic Case-Control Studies." Biometrics 42, no. 2 (1986): 301. http://dx.doi.org/10.2307/2531051.

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28

Mcneil, J. J., K. J. Ronaldson, P. B. Fitzgerald, A. J. Taylor, D. J. Topliss, and R. Wolfe. "Clozapine-induced myocarditis: characterisation using case-control design." European Heart Journal 34, suppl 1 (2013): P3863. http://dx.doi.org/10.1093/eurheartj/eht309.p3863.

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29

Mirchandani. "Case—Process Control and Design of Experiments/ANOVA." INFORMS Transactions on Education 10, no. 2 (2010): 74–97. http://dx.doi.org/10.1287/ited.1090.0041.

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30

Schildcrout, Jonathan S., Enrique F. Schisterman, Nathaniel D. Mercaldo, Paul J. Rathouz, and Patrick J. Heagerty. "Extending the Case–Control Design to Longitudinal Data." Epidemiology 29, no. 1 (2018): 67–75. http://dx.doi.org/10.1097/ede.0000000000000764.

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31

Cassar, May. "Case design and climate control: a typological analysis." Museum International 37, no. 2 (1985): 104–7. http://dx.doi.org/10.1111/j.1468-0033.1985.tb00562.x.

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32

Perne, Rainer, and Andreas Endesfelder. "Process analysis, design, and control — a case study -." Computers & Chemical Engineering 22 (March 1998): S1071. http://dx.doi.org/10.1016/s0098-1354(98)00212-9.

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33

BIEDERMANN, STEFANIE, EVA NAGEL, AXEL MUNK, HAJO HOLZMANN, and ANSGAR STELAND. "Tests in a Case?control Design Including Relatives." Scandinavian Journal of Statistics 33, no. 4 (2006): 621–35. http://dx.doi.org/10.1111/j.1467-9469.2006.00500.x.

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34

Mandrekar, Jayawant N., and Sumithra J. Mandrekar. "Case-Control Study Design: What, when, and why?" Journal of Thoracic Oncology 3, no. 12 (2008): 1371–72. http://dx.doi.org/10.1097/jto.0b013e31818dd97b.

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35

Goodman, Richard A., James A. Mercy, Peter M. Layde, and Stephen B. Thacker. "Case-control studies: Design issues for criminological applications." Journal of Quantitative Criminology 4, no. 1 (1988): 71–84. http://dx.doi.org/10.1007/bf01066885.

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36

Wacholder, Sholom, Raymond J. Carroll, David Pee, and Mitchell H. Gail. "The partial questionnaire design for case-control studies." Statistics in Medicine 13, no. 5-7 (1994): 623–34. http://dx.doi.org/10.1002/sim.4780130523.

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37

URUSHIHARA, Hisashi. "Case-control Design and Real-world Database Studies." Japanese Journal of Pharmacoepidemiology/Yakuzai ekigaku 28, no. 2 (2023): 57–72. http://dx.doi.org/10.3820/jjpe.28.57.

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38

LIU, Chun, Wei ZHANG, Hai-Yan ZHAO, and Zhi JIN. "“Use Case+Control Case” Driven Approach for Software Analysis and Design." Journal of Software 24, no. 4 (2014): 675–95. http://dx.doi.org/10.3724/sp.j.1001.2013.04275.

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39

Lacy, Michael G. "Efficiently Studying Rare Events: Case-Control Methods for Sociologists." Sociological Perspectives 40, no. 1 (1997): 129–54. http://dx.doi.org/10.2307/1389496.

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Case-control designs involve samples stratified disproportionately on a binary dependent variable. This design, though infrequently used by sociologists, offers tremendous logistical efficiency in the study of rare events, such as divorce, joining a religious cult, or committing a crime. This paper attempts to sensitize sociologists to the many situations in which this design is useful, and offers general and accessible guidance on the practice of case-control research. Using the epidemiologic literature, I explain the underlying logic of case-control design, discuss how to conduct case-control sampling, and briefly cover data analysis issues. I conclude with an empirical illustration of a case-control study examining factors associated with the change of chief administrative officers at post-secondary educational institutions.
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40

Kaye, Keith S., Anthony D. Harris, Matthew Samore, and Yehuda Carmeli. "The Case-Case-Control Study Design: Addressing the Limitations of Risk Factor Studies for Antimicrobial Resistance." Infection Control & Hospital Epidemiology 26, no. 4 (2005): 346–51. http://dx.doi.org/10.1086/502550.

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AbstractObjective:There are significant limitations of the standard case-control study design for identifying risk factors for resistant organisms. The objective of this study was to develop a study design to overcome these limitations.Design:Theoretical analysis of different types of study designs that can be used in risk factor studies for resistant organisms.Results:We developed the case-case-control study design, which uses two separate case-control analyses within a single study. The first analysis compares patients infected with resistant bacteria (resistant cases) with control-patients without infection caused by the target organism, who are therefore representative of the source population; and the second analysis compares patients infected with the susceptible phenotype of the target organism (susceptible cases) with the same controlpatients without infection caused by the target organism. These two analyses provide risk models for (1) isolation of the resistant phenotype of the target organism as compared with the source population and (2) isolation of the susceptible phenotype of the organism as compared with the source population. When these two risk models are compared and contrasted, risk factors specifically associated with isolation of the resistant phenotype can be identified.Conclusions:The case-case-control study design is an effective method for identifying risk factors for antimicrobial-resistant pathogens. Although the case-case-control study design has limitations, it is, in our opinion, more informative and less flawed than the standard case-control study design.
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41

Kicielinski, Kimberly P., Esther B. Dupépé, Amber S. Gordon, Nancy E. Mayo, and Beverly C. Walters. "What Isn’t a Case-Control Study?" Neurosurgery 84, no. 5 (2018): 993–99. http://dx.doi.org/10.1093/neuros/nyy591.

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Abstract BACKGROUND Confusion exists among neurosurgeons when choosing and implementing an appropriate study design and statistical methods when conducting research. We noticed particular difficulty with mislabeled and inappropriate case-control studies in the neurosurgical literature. OBJECTIVE To quantify and to rigorously review this issue for appropriateness in publication and to establish quality of the manuscripts using a rigorous technique. METHODS Following a literature search, pairs drawn from 5 independent reviewers evaluated a complete sample of 125 manuscripts claiming to be case-control studies with respect to basic case-control criteria. Seventy-five papers were then subjected to a more rigorous appraisal for quality using the SIGN Methodology Checklist for case-control studies. RESULTS Fifty publications were rejected based on basic criteria used to identify case-control design. Of the 75 subjected to quality analysis, 46 were felt to be acceptable for publication. Only 11 papers (9%) achieved the designation of high quality. Of the original 125 papers evaluated, 79 (63%) were inappropriately labeled case-control studies. CONCLUSION Mislabeling and use of inappropriate study design are common in the neurosurgical literature. Manuscripts should be evaluated rigorously by reviewers and readers, and neurosurgical training programs should include instruction on choice of appropriate study design and critical appraisal of the literature.
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42

Mascha, Maureen Francis, and Cathleen L. Miller. "Applying Internal Control Concepts Using Database Design: An Educational Case." AIS Educator Journal 19, no. 1 (2024): 1–16. https://doi.org/10.3194/1935-8156-19.1.1.

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Abstract This paper discusses a project that incorporates internal controls concepts and Access database design. The project consists of two parts—a written exercise and the database table creation. In part one (the written exercise), students match fields, threats, data entry controls, and Access property controls for the sales order entry activity from the revenue cycle using the sales order as the transaction. In part two, students create two data file tables designed to prevent and detect errors and threats at the field level of internal controls for the sales order entry transaction. The written exercise significantly improved the overall project scores. The linking of fields, threats, data entry controls, and Access property controls led to better Access table development. We also measured the students' internal control knowledge before and after the project, finding that students' knowledge of general and specific internal controls improved after completing the project. They also improved their database knowledge of Access.
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43

Dijkers, M. "Case-control studies false and true: Mislabeled study designs in rehabilitation research, and a master class in case-control study design." Journal of Rehabilitation Medicine 41, no. 4 (2009): 289–90. http://dx.doi.org/10.2340/16501977-0342.

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44

Kong, Yi Nan. "Adaptive Temperature Control Systems Design." Advanced Materials Research 538-541 (June 2012): 3149–53. http://dx.doi.org/10.4028/www.scientific.net/amr.538-541.3149.

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This paper presents an advanced low-cost temperature control system. The system takes the highest performance-cost ratio as its aim. It uses the low-cost 8-bit MCS-51 MCU and integrated temperature sensor to achieve the on-site control. A lower cost remote host computer can be used in this system. In the case of a relatively larger application, it can be expanded to a control system of master-slave distribution and utilize the computing and storage resources of the microcontroller. It realizes a wider range of temperature adjustment, and then put the state of the system into a database of the microcontroller to be ascertained later.
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45

Alomi, Yousef Ahmed, Amal Hassan Al-Najjar, Maha Hussein Almadany, Fakhar Al-Ayoubi, Ghudair Tashan Alanazi, and Abeer Hussin Almasoudi. "Research Policy on Case-control and Cohort Study Design in Pharmaceutical Care." International Journal of Pharmacology and Clinical Sciences 11, no. 1 (2022): 25–30. http://dx.doi.org/10.5530/ijpcs.2022.11.6.

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46

Avedon, R. E., and B. A. Francis. "Digital Control Design Via Convex Optimization." Journal of Dynamic Systems, Measurement, and Control 115, no. 4 (1993): 579–86. http://dx.doi.org/10.1115/1.2899183.

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A design method for sampled-data systems is presented incorporating robust control theory and convex optimization techniques. The technique is developed using operator theory applied to the relevant input-output operators for both performance and stability robustness. Numerical algorithms and an example for the SISO case are presented to explore some traditional sampled-data design heuristics.
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47

Bonnett, Jonathan, Carmel Cuschieri, and Joseph M. Cuschieri. "Noise Control design for a Ventilation Fan - Case Study." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 263, no. 1 (2021): 5731–39. http://dx.doi.org/10.3397/in-2021-3238.

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A ventilation system was design and installed for a multi story garage. The ventilation system system had a vertical concrete shaft with the ventilation fan located on the top floor at street level. The ventilation fan is separated from the outside by a set of metal louvers. Adjacent to the louvers is an open pedestrian area. The exhaust fan as installed had an inline duct silencer but this was insufficient in terms of providing the desired noise mitigation. The project desire was not to make changes to the fan or its inline silencer or the external louvers so an alternative noise mitigation option had to be explored. Based on the provided sound power characteristics of the fan, the exterior noise levels as calculated matched the expected levels coming out of the metal louvers. The interior of the ventilation shaft is bare concrete with the fan installed though a hole in the concrete top floor. The predominate noise was the very high reverberation inside the ventilation shaft. The owner of the property made an attempt at installing noise absorption but this was not sufficient. Based on the field data the sound levels with the preliminary absorption solution matched expectation, but further noise reduction was required. A complete sound absorption on the walls of the concrete ventilation shaft noise mitigation solution was design, and the expected levels predicted to show that significant noise reductions can be obtained by a comprehensive noise absorption solution. The noise mitigation solution was implemented and exterior sound level measurements performed at the completion of the project. The measured sound levels outside of the metal louvers were in very good agreement with the predicted levels. Based on the success of this first noise mitigation solution, noise mitigation for a second ventilation system is not being considered.
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48

Wacholder, Sholom. "The Case-Control Study as Data Missing by Design." Epidemiology 7, no. 2 (1996): 144–50. http://dx.doi.org/10.1097/00001648-199603000-00007.

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49

Thrift, Amanda G. "Case-Control Studies: The Importance of Design and Conduct." Neuroepidemiology 34, no. 4 (2010): 264–66. http://dx.doi.org/10.1159/000297757.

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50

Hajjar, Salam, Emil Dumitrescu, and Eric Niel. "Safe design method of embedded control systems. Case study." Journal Européen des Systèmes Automatisés 47, no. 4-8 (2013): 403–21. http://dx.doi.org/10.3166/jesa.47.403-421.

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