Initial External Validation of REGRESS in Public Health Graduate Students
dc.contributor.author | Kidwell, Kelley M. | en_US |
dc.contributor.author | Enders, Felicity B. | en_US |
dc.date.accessioned | 2015-01-07T15:24:44Z | |
dc.date.available | WITHHELD_12_MONTHS | en_US |
dc.date.available | 2015-01-07T15:24:44Z | |
dc.date.issued | 2014-12 | en_US |
dc.identifier.citation | Kidwell, Kelley M.; Enders, Felicity B. (2014). "Initial External Validation of REGRESS in Public Health Graduate Students." Clinical and Translational Science 7(6): 447-455. | en_US |
dc.identifier.issn | 1752-8054 | en_US |
dc.identifier.issn | 1752-8062 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/110068 | |
dc.description.abstract | Linear regression is typically taught as a second and potentially last required (bio)statistics course for Public Health and Clinical and Translational Science students. There has been much research on the attitudes of students toward basic biostatistics, but there has not been much assessing students’ understanding of critical regression topics. The REGRESS (REsearch on Global Regression Expectations in StatisticS) quiz developed at Mayo Clinic utilizes 27 questions to assess understanding for simple and multiple linear regression. We performed an initial external validation of this tool with 117 University of Michigan public health students. We compare the results of pre‐ and postcourse quiz scores from the Michigan cohort to scores of Mayo medical students and professional statisticians. University of Michigan students performed higher than Mayo students on the precourse quiz due to previous related coursework, but did not perform as high postcourse indicating the need for course modification. In the Michigan cohort, REGRESS scores improved by a mean (standard deviation) of 4.6 (3.4), p < 0.0001. Our results support the use of the REGRESS quiz as a learning tool for students and an evaluation tool to identify topics for curricular improvement for teachers, while we highlight future directions of research. | en_US |
dc.publisher | McKinsey Global Institute | en_US |
dc.publisher | Wiley Periodicals, Inc. | en_US |
dc.subject.other | Biostatistics | en_US |
dc.subject.other | Assessment | en_US |
dc.subject.other | Validation | en_US |
dc.subject.other | Graduate Level Statistics Course | en_US |
dc.subject.other | Linear Regression | en_US |
dc.title | Initial External Validation of REGRESS in Public Health Graduate Students | en_US |
dc.type | Article | en_US |
dc.rights.robots | IndexNoFollow | en_US |
dc.subject.hlbsecondlevel | Pharmacy and Pharmacology | en_US |
dc.subject.hlbtoplevel | Health Sciences | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/110068/1/cts12190.pdf | |
dc.identifier.doi | 10.1111/cts.12190 | en_US |
dc.identifier.source | Clinical and Translational Science | en_US |
dc.identifier.citedreference | von Elm E, Altman DG, Egger M, Pocock SJ, Gotzsche PC, Vandenbroucke JP. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. BMJ. 2007; 335 ( 7624 ): 806 – 808. | en_US |
dc.identifier.citedreference | Nasser FM. Structural model of the effects of cognitive and affective factors on the achievement of Arabic‐speaking pre‐service teachers in introductory statistics. J Stat Educ [Online] 2004; 12 ( 1 ), Retrieved October 3, 2013, from http://www.amstat.org/publications/jse/v12n1/nasser.html | en_US |
dc.identifier.citedreference | Cashin SE, Elmore PB. The survey of attitudes toward statistics scale: a construct validity study. Educ Psychol Meas. 2005; 65 ( 3 ): 509 – 524. | en_US |
dc.identifier.citedreference | Tempelaar DT, Schim van der Loeff S, Gijselaers WH. A structural equation model analyzing the relationship of students' attitudes toward statistics, prior reasoning abilities, and course performance. Stat Educ Res J. 2007; 6 ( 2 ): 78 – 102. | en_US |
dc.identifier.citedreference | Chiesi F, Primi C. Cognitive and non‐cognitive factors related to students' statistics achievement. Stat Educ Res J. 2010; 9 ( 1 ): 6 – 26. | en_US |
dc.identifier.citedreference | Emmiog˘lu E, Capa‐Aydin Y. Attitudes and achievement in statistics: a meta‐analysis study. Stat Educ Res J. 2012; 11 ( 2 ): 95 – 102. | en_US |
dc.identifier.citedreference | delMas R, Garfield J, Ooms A, Chance B. Assessing students' conceptual understanding after a first course in statistics. Stat Educ Res J. 2007; 6 ( 2 ): 28 – 58. http://www.stat.auckland.ac.nz/∼iase/serj/SERJ6(2)_delMas.pdf | en_US |
dc.identifier.citedreference | Windish DM, Huot SJ, Green ML. Medicine residents' understanding of the biostatistics and results in the medical literature. J Am Med Assoc. 2007; 298 ( 9 ): 1010 – 1022. | en_US |
dc.identifier.citedreference | Enders F. Evaluating mastery of biostatistics for medical researchers: need for a new assessment tool. Clin Trans Sci. 2011; 4: 448 – 454. | en_US |
dc.identifier.citedreference | Enders F. Do clinical and translational science graduate students understand linear regression? Development and early validation of the REGRESS quiz. Clin Trans Sci. 2013: doi: 10.1111/cts.12088 | en_US |
dc.identifier.citedreference | Armstrong R, Waters E, Moore L, Riggs E, Cuervo LG, Lumbiganon P, Hawe P. Improving the reporting of public health intervention research: advancing TREND and CONSORT. J Public Health. 2008; 30 ( 1 ): 103 – 109. | en_US |
dc.identifier.citedreference | Moher D, Hopewell S, Schulz KF, Montori V, Gotzche PC, Devereaux PJ, Elbourne D, Egger M, Altman DG. CONSORT 2010 Explanation and Elaboration: updated guidelines for reporting parallel group randomised trials. BMJ. 2010; 340 ( c869 ): 1 – 28. | en_US |
dc.identifier.citedreference | Des Jarlais D, Lyles C, Crepaz N, Group T. Improving the reporting quality of nonrandomized evaluations of behavioral and public health interventions: the TREND statement. Am J Public Health. 2004; 94 ( 3 ): 361 – 366. | en_US |
dc.identifier.citedreference | Vandenbroucke JP, von Elm E, Altman DG, Gotzche PC, Mulrow CD, Pocock SJ, Poole C, Schlesselman JJ, Egger M. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): explanation and elaboration. PLoS Med. 2007; 4 ( 10 ): 1628 – 1654. | en_US |
dc.identifier.citedreference | Murphy TJ, McKnight C, Richman M, Terry R. Clicker Questions. 2009, July 29: Retrieved from http://www.ou.edu/statsclickers/clickerQuestions.htm | en_US |
dc.identifier.citedreference | Peck R, Devore J. Roxy Peck's collection of classroom voting questions for statistics. 2008: Retrieved from http://mathquest.carroll.edu/resources.html | en_US |
dc.identifier.citedreference | Utts J. Statistics 110/201 Practice Regression Final Key. 2009 Retrieved from http://www.ics.uci.edu/∼jutts/110‐201‐09/PracticeRegressionFinalKey.pdf | en_US |
dc.identifier.citedreference | Lewis A. Lecture 10: regression, correlation and acceptance sampling. 2012: Retrived from http://cosmologist.info/teaching/STAT/Statistics10.pdf | en_US |
dc.identifier.citedreference | Department of Mathematics and Statistics, York University. (2005). Visualizing relations in multiple regression. Retrieved from http://www.math.yorku.ca/SCS/spida/lm/visreg.html | en_US |
dc.identifier.citedreference | European Environment Agency. (2011, September 26). Illustration of the statistical analysis using multiple linear regression. Retrieved from http://www.eea.europa.eu/data‐and‐maps/figures/illustration‐of‐the‐statistical‐analysis | en_US |
dc.identifier.citedreference | ASPH. Annual Data Report. (2010). Washington, DC: Association of Schools of Public Health, 2010. http://www.asph.org/UserFiles/DataReport2010.pdf | en_US |
dc.identifier.citedreference | Manyika J, Chui M, Bughin J, Brown B, Dobbs R, Roxburgh C, Byers AH. Big Data: The Next Frontier for Innovation, Competition, and Productivity. McKinsey Global Institute. 2011 | en_US |
dc.identifier.citedreference | Hart Research Associates. 2010. Raising the Bar: Employers' Views on College Learning in the Wake of the Economic Downturn. Washington, DC: Association of American Colleges and Universities. | en_US |
dc.identifier.citedreference | Lohr S. For Today's graduate, just one word: Statistics, August 5, 2009. New York Times. http://www.nytimes.com/2009/08/06/technology/06stats.html?_r = 0. Accessed October 3, 2013 | en_US |
dc.identifier.citedreference | Nicholson JR, Mulhern G. ( 2000 ). Conceptual challenges facing A level statistics students: Teacher and examiner perspectives. Papers on Teaching and Learning Statistics –ICME9. http://iase‐web.org/documents/papers/icme9/ICME9_03.pdf. Assessed February 26, 2014. | en_US |
dc.identifier.citedreference | Elmore P, Vasu ES. Relationship between selected variables and statistics achievement: building a theoretical model. J Educ Psychol. 1980; 72 ( 4 ): 457 – 467. | en_US |
dc.identifier.citedreference | Elmore P, Vasu ES. A model of statistics achievement using spatial ability, feminist attitudes and mathematics‐related variables as predictors. Educ Psychol Meas. 1986; 46 ( 1 ): 215 – 222. | en_US |
dc.identifier.citedreference | Schau C, Stevens J, Dauphinee TL, Del Vecchio A. The development and validation of the survey of attitudes toward statistics. Educ Psychol Meas. 1995; 55: 868 – 875. | en_US |
dc.identifier.citedreference | Schram CM. A meta‐analysis of gender differences in applied statistics achievement. J Educ Behav Stat. 1996; 21 ( 1 ): 55 – 70. | en_US |
dc.identifier.citedreference | Tremblay PF, Gardner RC, Heipel G. A model of the relationships among measures of affect, aptitude, and performance in introductory statistics, Can J Behav Sci. 2000; 32 ( 1 ): 40 – 48. | en_US |
dc.identifier.citedreference | Baloglu M. Individual differences in statistics anxiety among college students. Personal Indiv Differ. 2003; 34 ( 5 ): 855 – 865. | en_US |
dc.identifier.citedreference | Bandalos DL, Finney SJ, Geske JA. A model of statistics performance based on achievement goal theory. J Educ Psychol. 2003; 95 ( 3 ): 604 – 616. | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
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