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Journal articles on the topic 'Epidemiology and Biostatistics'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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1

Gill, David. "Biostatistics and epidemiology." Journal of Psychosomatic Research 41, no. 4 (October 1996): 385. http://dx.doi.org/10.1016/s0022-3999(96)00094-3.

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2

Minassian, Vatche A., and Mitesh Parekh. "Epidemiology and Biostatistics." Journal of Pelvic Medicine and Surgery 13, no. 1 (January 2007): 1–12. http://dx.doi.org/10.1097/01.spv.0000256865.80242.8d.

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3

Lash, T. L. "Epidemiology and Biostatistics." American Journal of Epidemiology 176, no. 7 (September 18, 2012): 656–57. http://dx.doi.org/10.1093/aje/kws339.

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4

Kocher, Mininder S., and David Zurakowski. "Clinical Epidemiology and Biostatistics." Journal of Bone & Joint Surgery 86, no. 3 (March 2004): 607–20. http://dx.doi.org/10.2106/00004623-200403000-00024.

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5

Goldberg, M. F. "Ophthalmic Epidemiology and Biostatistics." Archives of Ophthalmology 106, no. 6 (June 1, 1988): 737–38. http://dx.doi.org/10.1001/archopht.1988.01060130807026.

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6

Burden, A. C. "Clinical Epidemiology and Biostatistics." Postgraduate Medical Journal 66, no. 775 (May 1, 1990): 415. http://dx.doi.org/10.1136/pgmj.66.775.415.

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7

Chu, Joseph. "Active learning in epidemiology and biostatistics." Teaching and Learning in Medicine 6, no. 3 (June 1994): 191–93. http://dx.doi.org/10.1080/10401339409539674.

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8

Gurka, Matthew J. "Basic Concepts in Biostatistics and Epidemiology." Journal of the Royal Statistical Society: Series A (Statistics in Society) 171, no. 2 (April 2008): 506–7. http://dx.doi.org/10.1111/j.1467-985x.2007.00528_6.x.

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9

Curnow, R. N., N. E. Morton, D. C. Rao, and J. M. Lalouel. "Methods in Genetic Epidemiology (Contributions to Epidemiology and Biostatistics)." Biometrics 41, no. 2 (June 1985): 595. http://dx.doi.org/10.2307/2530890.

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10

Hilden, J. "Effect measures in biostatistics." Journal of Clinical Epidemiology 56, no. 4 (April 2003): 391–92. http://dx.doi.org/10.1016/s0895-4356(02)00540-1.

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11

Kapoor, Aanchal. "Biostatistics and epidemiology lecture series, part 1." Cleveland Clinic Journal of Medicine 84, no. 9 suppl 2 (September 2017): e1-e1. http://dx.doi.org/10.3949/ccjm.84.s2.01.

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12

Kleinbaum, David G. "Teaching Short Courses in Biostatistics and Epidemiology." American Statistician 49, no. 2 (May 1995): 200. http://dx.doi.org/10.2307/2684639.

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13

Lampkins, Gwendolyn T. "A Study Guide to Epidemiology and Biostatistics." AORN Journal 64, no. 4 (October 1996): 634. http://dx.doi.org/10.1016/s0001-2092(06)63637-5.

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14

Kleinbaum, David G. "Teaching Short Courses in Biostatistics and Epidemiology." American Statistician 49, no. 2 (May 1995): 200–203. http://dx.doi.org/10.1080/00031305.1995.10476143.

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15

Paul, Keltie. "A Study Guide to Epidemiology and Biostatistics." Family & Community Health 20, no. 2 (July 1997): 80–81. http://dx.doi.org/10.1097/00003727-199707000-00010.

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16

Morton, Richard F., Richard J. Hebel, and Robert J. McCarter. "A Study Guide to Epidemiology and Biostatistics." Journal For Healthcare Quality 13, no. 2 (March 1991): 38. http://dx.doi.org/10.1097/01445442-199103000-00024.

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17

Bhuyan, Dhrubajyoti, Neha Dua, and Tejal Kothari. "Epidemiology and biostatistics: fundamentals of research methodology." Open Journal of Psychiatry & Allied Sciences 7, no. 1 (2016): 87. http://dx.doi.org/10.5958/2394-2061.2015.00022.1.

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18

Beisel, William R. "Nutritional Epidemiology. Monographs in Epidemiology and Biostatistics, Volume 15.Walter Willett." Quarterly Review of Biology 65, no. 3 (September 1990): 391. http://dx.doi.org/10.1086/416932.

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19

K., M., and Sylvia Wassertheil-Smoller. "Biostatistics and Epidemiology: A Primer for Health Professionals." Population (French Edition) 46, no. 5 (September 1991): 1302. http://dx.doi.org/10.2307/1533477.

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20

Dutton, Cynthia, Paul Wing, and Charles Eaton. "Teaching epidemiology and biostatistics through interactive problem solving." Journal of Cancer Education 6, no. 3 (1991): 129–32. http://dx.doi.org/10.1080/08858199109528108.

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21

Lanska, Douglas J. "Epidemiology and Biostatistics: An Introduction to Clinical Research." JAMA 303, no. 18 (May 12, 2010): 1866. http://dx.doi.org/10.1001/jama.2010.604.

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22

Dialsingh, Isaac. "Biostatistics and Epidemiology: a Primer for Biomedical Professionals." Journal of the Royal Statistical Society: Series A (Statistics in Society) 168, no. 1 (January 2005): 262. http://dx.doi.org/10.1111/j.1467-985x.2004.00347_19.x.

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23

Pickering, R. M. "Biostatistics and Epidemiology: A primer for Health Professionals." Journal of Epidemiology & Community Health 45, no. 2 (June 1, 1991): 174. http://dx.doi.org/10.1136/jech.45.2.174-b.

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24

Summer, David S. "Biostatistics and epidemiology: A primer for health professionals." Journal of Vascular Surgery 18, no. 2 (August 1993): 330. http://dx.doi.org/10.1016/0741-5214(93)90648-6.

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25

Schlesselman, James J. "Biostatistics in epidemiology: A view from the faultline." Journal of Clinical Epidemiology 49, no. 6 (June 1996): 627–29. http://dx.doi.org/10.1016/0895-4356(96)00036-4.

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26

Paulus, Jessica K., Angie Rodday, and Farzad Noubary. "2134." Journal of Clinical and Translational Science 1, S1 (September 2017): 44. http://dx.doi.org/10.1017/cts.2017.160.

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OBJECTIVES/SPECIFIC AIMS: Biostatistics and Epidemiology courses within clinical research or public health training programs are typically developed and taught separately. As a result, students may have trouble in their research outside the classroom, where biostatistical and epidemiological concepts must be well integrated. Case method teaching is a participant- and discussion-centered pedagogical approach that has been used in business and law schools for more than 50 years to improve student learning, yet has taken longer to be adopted in health professional schools. The case method is distinguished by presenting learners with a real-world problem without a single unique solution. Designed to mimic the constraints and incomplete information found in real life, it is an ideal approach for integrating multiple related disciplines. A team of Clinical and Translational Science (CTS) faculty from the Tufts CTSI collaborated to develop a new course that integrates epidemiology and biostatistics disciplines using the case method. METHODS/STUDY POPULATION: We developed an intermediate-level, case-based course integrating epidemiology and biostatistics topics using modern, real-world clinical examples. Recognizing the importance of technical skill building, this intermediate-level Tufts CTS course adopted a hybrid approach, incorporating lecture and in-class laboratory exercises, alongside cases. We surveyed CTS faculty to identify a set of core methodological competencies. These included randomized trials, case-control and cohort studies, confounding, effect modification, propensity scores, linear and logistic regression, and survival analysis. Faculty provided us with clinical questions and deidentified data sets corresponding to these competencies; we also reviewed publicly available data sets. RESULTS/ANTICIPATED RESULTS: CTS faculty collaborated to develop 10 cases (with accompanying data sets) from modern clinical research examples that illustrate the connections between epidemiology and biostatistical concepts. Each case contains a background section, a statement of the core problem, a data set with data dictionary, articles from the primary literature (often the publication of the data set) with discussion questions and in-class lab exercises (R programming). One case presents students with the challenge of whether acupuncture may be an effective therapy for pain associated with chronic headache. Through case activities, students gain experience weighing observational Versus experimental evidence, apply directed acyclic graph theory, and analyze clinical trial data. Qualitative evaluations in 2015 (pilot year) and 2016 indicate students preferred the integrated approach to separate courses, and found the integration facilitated application of methods to their independent research projects. Significant rewards for faculty include cross-disciplinary collaboration, sharpened teaching skills, and engaging with learners in a dynamic classroom environment. DISCUSSION/SIGNIFICANCE OF IMPACT: Despite administrative and pedagogical challenges, a case-based, integrated curriculum offers rewards for faculty and students. The case method may be a useful pedagogical strategy to integrate other closely related topics or courses in translational science to better prepare scholars for the challenges of independent research.
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27

Sevgi, L. "Biostatistics and Epidemiology: Hypothetical Tests on Cell Phone Users." IEEE Antennas and Propagation Magazine 52, no. 1 (February 2010): 267–73. http://dx.doi.org/10.1109/map.2010.5466470.

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28

Hampl, Jeffrey S. "A Study Guide to Epidemiology and Biostatistics (5th Ed)." Family & Community Health 24, no. 4 (January 2002): 56–57. http://dx.doi.org/10.1097/00003727-200201000-00015.

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29

LeGrady, Dan C. "Experience with a Postdoctoral Fellowship in Epidemiology and Biostatistics." American Journal of Health-System Pharmacy 45, no. 7 (July 1, 1988): 1496–97. http://dx.doi.org/10.1093/ajhp/45.7.1496a.

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30

Gail, M. H., and J. Benichou. "Epidemiology and Biostatistics Program of the National Cancer Institute." JNCI Journal of the National Cancer Institute 86, no. 8 (April 20, 1994): 573–75. http://dx.doi.org/10.1093/jnci/86.8.573.

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31

Gryparis, A., C. J. Paciorek, A. Zeka, J. Schwartz, and B. A. Coull. "Measurement error caused by spatial misalignment in environmental epidemiology." Biostatistics 10, no. 2 (October 16, 2008): 258–74. http://dx.doi.org/10.1093/biostatistics/kxn033.

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32

Healy, Bernadine. "NIH and the birth of biostatistics." Statistics in Medicine 13, no. 5-7 (March 15, 1994): 403. http://dx.doi.org/10.1002/sim.4780130504.

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33

Donnison, Sharn, Peter Dunn, Rachel Cole, Michael Bulmer, Anne Roiko, and Frank Muller. "Enhancing Curriculum in Epidemiology and Biostatistics through Simulation-Based Learning." International Research in Education 4, no. 1 (November 13, 2015): 11. http://dx.doi.org/10.5296/ire.v4i1.8064.

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A course in epidemiology and biostatistics, taken by students in health promotion and other public health disciplines, is evaluated and assessed in light of a recent university directive to incorporate blended learning, and the projected increase of online students into the course. A formal curriculum evaluation was informed by qualitative data from academic staff teaching into the course and students enrolled in the course. Five areas of challenge are identified: the volume of content; the authenticity of content; the course scheduling; the disconnection between the two course components; and the authenticity of the assessment. Some potential solutions have been identified, and the use of a virtual human population proposed as an avenue for introducing these solutions in a blended learning context. The process of conducting a formal curriculum evaluation in the context of introducing blended learning may prove useful in higher education courses looking to introduce blended learning, especially in disciplines that require students to interact with people.
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34

Dunn, Peter K., Sharn Donnison, Rachel Cole, and Michael Bulmer. "Using a virtual population to authentically teach epidemiology and biostatistics." International Journal of Mathematical Education in Science and Technology 48, no. 2 (September 23, 2016): 185–201. http://dx.doi.org/10.1080/0020739x.2016.1228015.

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35

Marantz, Paul R., William Burton, and Penny Steiner-Grossman. "Using the Case-discussion Method to Teach Epidemiology and Biostatistics." Academic Medicine 78, no. 4 (April 2003): 365–71. http://dx.doi.org/10.1097/00001888-200304000-00008.

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36

&NA;. "Jekel’s Epidemiology, Biostatistics, Preventive Medicine, and Public Health, 4th Edition." Medicine & Science in Sports & Exercise 46, no. 11 (November 2014): 2191. http://dx.doi.org/10.1249/mss.0000000000000484.

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37

Evans, Kambria H., Atalie C. Thompson, Colin O’Brien, Madika Bryant, Preetha Basaviah, Charles Prober, and Rita A. Popat. "An Innovative Blended Preclinical Curriculum in Clinical Epidemiology and Biostatistics." Academic Medicine 91, no. 5 (May 2016): 696–700. http://dx.doi.org/10.1097/acm.0000000000001085.

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38

Casals, Martí, and Caroline F. Finch. "Sports Biostatistician: a critical member of all sports science and medicine teams for injury prevention." British Journal of Sports Medicine 52, no. 22 (November 2018): 1457–61. http://dx.doi.org/10.1136/bjsports-2016-042211rep.

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Sports science and medicine need specialists to solve the challenges that arise with injury data. In the sports injury field, it is important to be able to optimise injury data to quantify injury occurrences, understand their aetiology and most importantly, prevent them. One of these specialty professions is that of Sports Biostatistician. The aim of this paper is to describe the emergent field of Sports Biostatistics and its relevance to injury prevention. A number of important issues regarding this profession and the science of sports injury prevention are highlighted. There is a clear need for more multidisciplinary teams that incorporate biostatistics, epidemiology and public health in the sports injury area.
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39

Barraza, Felipe, Marcelo Arancibia, Eva Madrid, and Cristian Papuzinski. "General concepts in biostatistics and clinical epidemiology: Random error and systematic error." Medwave 19, no. 07 (August 30, 2019): e7687-e7687. http://dx.doi.org/10.5867/medwave.2019.07.7687.

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40

Antonelli, Joseph, Matthew Cefalu, and Luke Bornn. "The positive effects of population-based preferential sampling in environmental epidemiology." Biostatistics 17, no. 4 (June 1, 2016): 764–78. http://dx.doi.org/10.1093/biostatistics/kxw026.

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Summary In environmental epidemiology, exposures are not always available at subject locations and must be predicted using monitoring data. The monitor locations are often outside the control of researchers, and previous studies have shown that “preferential sampling” of monitoring locations can adversely affect exposure prediction and subsequent health effect estimation. We adopt a slightly different definition of preferential sampling than is typically seen in the literature, which we call population-based preferential sampling. Population-based preferential sampling occurs when the location of the monitors is dependent on the subject locations. We show the impact that population-based preferential sampling has on exposure prediction and health effect estimation using analytic results and a simulation study. A simple, one-parameter model is proposed to measure the degree to which monitors are preferentially sampled with respect to population density. We then discuss these concepts in the context of PM2.5 and the EPA Air Quality System monitoring sites, which are generally placed in areas of higher population density to capture the population's exposure.
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41

Lazcano, Gabriel, Cristian Papuzinski, Eva Madrid, and Marcelo Arancibia. "General concepts in biostatistics and clinical epidemiology: observational studies with cohort design." Medwave 19, no. 11 (December 30, 2019): e7748-e7748. http://dx.doi.org/10.5867/medwave.2019.11.7748.

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42

Van Houwelingen, Hans C. "The future of biostatistics: expecting the unexpected." Statistics in Medicine 16, no. 24 (December 30, 1997): 2773–84. http://dx.doi.org/10.1002/(sici)1097-0258(19971230)16:24<2773::aid-sim761>3.0.co;2-q.

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43

Erickson, Grace P. "Epidemiology and Biostatistics Content in Baccalaureate Education for Community Health Nursing." Public Health Nursing 9, no. 1 (March 1992): 45–52. http://dx.doi.org/10.1111/j.1525-1446.1992.tb00071.x.

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44

Skrastins, E., M. Cunningham, P. Jindal, R. Fitzpatrick, O. Oneko, J. Carpenter, C. Booth, et al. "The Canadian Society for Epidemiology and Biostatistics 2013 National Student Conference." American Journal of Epidemiology 178, no. 10 (October 20, 2013): 1588–90. http://dx.doi.org/10.1093/aje/kwt259.

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45

Lu, Y., and S. L. Zeger. "On the equivalence of case-crossover and time series methods in environmental epidemiology." Biostatistics 8, no. 2 (June 29, 2006): 337–44. http://dx.doi.org/10.1093/biostatistics/kxl013.

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46

Núñez-Antón, Vicente. "Book Review: Biostatistics: a Bayesian introduction." Statistical Methods in Medical Research 14, no. 4 (August 2005): 441–42. http://dx.doi.org/10.1177/096228020501400416.

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47

Freedman, L. S. "The next 10 years of biostatistics." Statistical Methods in Medical Research 9, no. 1 (February 1, 2000): 25–30. http://dx.doi.org/10.1191/096228000677143997.

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48

Raychaudhuri, Aparna. "Book Review: Biostatistics in Clinical Trials." Statistical Methods in Medical Research 12, no. 4 (August 2003): 369–70. http://dx.doi.org/10.1191/0962280203sm336xx.

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49

WELLEK, S. "CLINICAL BIOSTATISTICS. AN INTRODUCTION TO EVIDENCE BASED MEDICINE." Statistics in Medicine 15, no. 19 (October 15, 1996): 2121–23. http://dx.doi.org/10.1002/(sici)1097-0258(19961015)15:19<2121::aid-sim346>3.0.co;2-m.

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50

LESSER, MARTIN L. "GUIDELINES FOR BUDGETING BIOSTATISTICS INVOLVEMENT IN RESEARCH PROJECTS." Statistics in Medicine 15, no. 20 (October 30, 1996): 2127–33. http://dx.doi.org/10.1002/(sici)1097-0258(19961030)15:20<2127::aid-sim356>3.0.co;2-8.

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