# Department/Academic Unit: Public Health Sciences Degree Program: Biostatistics Collaborative Program

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1 Department/Academic Unit: Public Health Sciences Degree Program: Biostatistics Collaborative Program Department of Mathematics and Statistics Degree Level Expectations, Learning Outcomes, Indicators of Achievement and the Program Requirements that Support the Learning Outcomes Degree Level Expectations Depth and Breadth of Knowledge Learning Outcomes (program specific) This degree is awarded to students who demonstrate: A critical understanding of theory of statistical inference Knowledge about most current biostatistical methods and regression models for different types of outcome data, and their possible applications Knowledge of implementation of these methods using statistical programs such as SAS or R. A developed understanding of the related discipline of epidemiology, clinical trials and their study designs; and how biostatistics, epidemiology and health research interrelate. A relevant knowledge outside the disciplines of biostatistics and epidemiology, including the disciplines in health services and policy, health economics and program evaluation etc. Relevant Courses, Academic Requirement (requirements that contribute to the achievement of learning outcomes and degree expectations To fulfill depth requirements: EPID 823 Advanced Biostatistics MATH 895 (or STAT 853) STAT 862 STAT 886 To fulfill breadth requirements: EPID 801 Introductory Epidemiology EPID 804 Advanced Epidemiologic Methods Two graduate level elective courses to broaden the knowledge in other disciplines Indicators of Achievement As evidenced by: of the required statistical inference course (MATH 895 (STAT 853). of assignments in EPID 823 and STAT 886, and special biostatistics topic presentation in EPID 823 of STAT 862 of mid-term and final examinations (as appropriate) in EPID 801 and EPID 804. of two elective courses.

2 Research and Scholarship Comprehension of statistical theory and the assumptions behind those commonly used biostatistical methods/models in health-related research Critical evaluation of different approaches to solving research problems using well established biostatistical techniques. Ability to critically read and appraise the statistical and epidemiological use in research literature. Six required graduate level courses plus two elective courses Four month practicum of assignments and projects given in the four course courses in statistics/biostatistics. Special biostatistics topic presentation in EPID 823 EPID 804 assignments (Critical Appraisal) Application of Knowledge Competency in simple research proposal writing (including study design, and a statistical plan in data collection/management and analysis), which meets the requirements for ethical approval Competence in evaluating and applying the existing biostatistical and epidemiological methods/models relevant to the study design and the types of data, and arriving at valid conclusions Competence in reviewing and synthesizing literature critically from a biostatistical and epidemiological viewpoint EPID 823 Advanced Biostatistics STAT 886 STAT 862 EPID 801 Introductory Epidemiology EPID 804 Advanced Epidemiologic Methods Four month practicum EPID 804 protocol assignments of practicum of assignments and course projects in EPID 823, STAT 886 and STAT 862 EPID 804 protocol assignments of practicum Professional capacity/autonomy The ability to use SAS/R to perform data management and statistical analysis The ability to work as a biostatistician in a research team on health-related research projects Six required graduate level courses plus two elective courses Four month practicum of practicum Evaluation from

3 The ability to pursue further study (PhD) in biostatistics or epidemiology or other related discipline The ability to collaborate with other biostatisticians to engage in the development of new biostatistical methodology practicum supervisor and academic supervisor Successful placement of students in academic and other jobs, which apply skills learned in program Research manuscripts for possible publication Level of communication skill Awareness of limits of knowledge The ability to: Communicate statistical concepts to researchers in other disciplines Use the Statistical Analysis Software (SAS) or R to process and analyze data, interpret and summarize the results of analysis, and convey the research findings in written or oral work effectively to non-statistical audience Cognizance of the complexity of real data and the limitations and assumptions of statistical methods applied to analyze real data Understand the limits of one s own knowledge Six required courses plus two elective courses Four month practicum EPID 823 (804) special biostatistics topic presentation Limitations of statistical and epidemiologic methods or techniques are addressed in all courses Admission to doctoral degree programs Special biostatistics topic presentation in EPID 823 (804). of practicum presentation Manuscript writing Evaluation from practicum supervisor and academic supervisor of assignments and projects (including the identification of strength and limitations

4 and ability, how they might influence analyses and interpretation; and be aware of the possibility of better alternative methods Four month practicum of the methods used) given in all the core and elective courses of practicum Evaluation from academic supervisor

5 Department/Academic Unit: Public Health Sciences Degree Program: PhD Program Degree Level Expectations, Learning Outcomes, Indicators of Achievement and the Program Requirements that Support the Learning Outcomes Degree Learning Expectations Depth and breadth of knowledge Learning Outcomes (program specific) This degree is awarded to students who demonstrate: 1. Understanding and mastery of basic through advanced biostatistics methods and concepts, as applied to the field of epidemiology Descriptive statistics, measures of occurrence, measures of effect, attributable risk, standard error and confidence interval estimation, significance tests, diagnostic tests, power and sample size determination, samplings methods, categorical analysis, stratified analyses, matched analyses, clustering, analysis of variance, survival analysis, regression models for different types of outcome data (Multiple, logistic, negative binomial, Poisson, Cox), selected advanced analytical topics (eg. Bayesian statistics, theory of statistical model development, assessment of confounding and interaction, mediation analyses, bias analysis, missing data analysis and imputations, structural equation modelling, factor analysis, multi-level modelling) Relevant Courses, Academic Requirement (requirements that contribute to the achievement of learning outcomes and degree expectations EPID 901 Advanced Epidemiology EPID 823 Advanced Biostatistics, Plus course electives advised by supervisory committee EPID 999 Thesis, including outline, protocol, and final dissertation Regular participation in departmental seminar series and thesis proposals and defences Indicators of Achievement As evidenced by: of assignments, quizzes, projects and examinations in advanced biostatistics (eg. EPID 823) and the statistical components of advanced epidemiology courses (eg. EPID 901) Demonstration of mastery of core concepts during the comprehensive examination, the writing and presentation of the PhD thesis outline and proposal and conduct of the thesis. This can include acceptance of quantitative manuscripts in peer reviewed journals associated with the thesis

6 2. Understanding and mastery of basic through advanced methods of descriptive and analytical epidemiological study designs Appropriate study designs to describe health problems and phenomena; to investigate causal and prognostic factors (personal, social or environmental); and to evaluate the interventions and outcomes of treatment/interventions Includes: descriptive and surveillance designs; analytic designs (ecologic, case-control and nested case-control; retrospective and prospective cohort); experimental designs (randomized trials, randomized community trials), meta-analyses, and new and emerging designs (eg. Case-cohort) 3. Understanding and mastery of concepts surrounding the design of epidemiological studies Core epidemiological concepts, including but not limited to: three major types of bias affecting study validity (selection, information and confounding); precision and the role of chance; statistical significance vs public health/clinical significance; matched vs unmatched designs; mediation, interactions and effect modification; external validity, study power and efficiency; models of disease causation; conceptual and theoretical frameworks applied to the design of of assignments, quizzes, projects and examinations in intermediate and advanced epidemiology courses (eg. EPID 901) Demonstration of mastery of core concepts during the comprehensive examination, the writing and presentation of the PhD thesis outline and proposal, and conduct of the thesis Further demonstration of this mastery in teaching opportunities

7 epidemiological studies 4. Detailed and comprehensive knowledge of content as well as the specialized methods used within the thesis speciality area Includes core mastery of the substantive epidemiology of topic area for thesis; theoretical frameworks that underlie analyses in this field; as well as specialized statistical and non-statistical methods that support the thesis in this field 5. Appreciation of the importance of nonepidemiological methods (eg. Psychometrics, qualitative enquiry, mixed methods ) that have potential application to epidemiology Understanding of the role and appropriate application of non-epidemiological designs, to complement traditional epidemiological methods (lectures, seminars, teaching assistantship), written and oral scientific communications and associated knowledge translation activities of assignments, quizzes, projects and examinations in intermediate and advanced epidemiology courses (eg. EPID 901) Demonstration of mastery of core concepts during the comprehensive examination, the writing and presentation of the PhD thesis outline and proposal,and conduct of the thesis Further demonstration of this mastery in teaching opportunities (lectures, seminars, teaching assistantships), written and oral scientific communications and associated knowledge translation activities Demonstrated mastery of

8 substantive areas of interest in the comprehensive exam, as well as the written thesis protocol, the final thesis document and the oral defence of these documents Ability to communicate this role and application, as applicable, in a cogent scientific manner Research and Scholarship 6. Ability to critically read and appraise the epidemiological research literature, based upon core descriptive, analytic and experimental designs EPID 901 Advanced Epidemiology EPID 823 Advanced Biostatistics Plus course electives advised by supervisory committee Demonstration of abilities to conduct peer review of scientific manuscripts based upon various epidemiological study designs Demonstration of abilities to appraise the merits and weaknesses of bodies of literature related to the core thesis topic EPID 899, including outline, protocol and

9 7. Capability to define and refine epidemiological research questions and hypotheses 8. Use of appropriate techniques in data collection and associated field methods 9. Use of appropriate techniques and software for data management 10. Use of appropriate technique and final dissertation Regular participation in departmental seminar series, and thesis proposals and defences SGS 804 Certification in ethics for research involving human subjects (School of Graduate Studies online course) Development of scientific protocols for courses, granting agencies and the PhD thesis Completion of course components devoted to sampling, data abstraction, and data collection of comprehensive exam, especially components related to such methods Demonstration of mastery of these techniques in the thesis outline, proposal and final dissertation of course assignments involving computerized data management

10 software for epidemiological/ biostatistical analyses of all data management tasks in PhD thesis of course assignments involving such analyses 11. Competency in oral and written presentations for a peer review scientific audience of design and conduct of data analyses in PhD thesis of written assignments for advanced epidemiology and biostatistical courses 12. Competency in grant proposal construction for a peer review scientific audience 13. Competency in principles underlying the conduct of research involving human subjects 14. Competency in peer review of scientific grants, manuscripts and other epidemiological products 15. Competency in design and conduct of an Submission and oral defence of thesis outline, protocol, and final dissertation. May involve submission of grant(s) and scientific manuscripts to peer review agencies and journals Participation in internal and external scientific presentations Successful submission and defence of PhD protocol of human subjects (ethics) training required of all graduate students Consideration of ethical principles in the thesis proposal and final

11 advanced research project using epidemiologic methods dissertation Completion of assignments in advanced epidemiology course (eg EPID 901) Application of Knowledge 1. Specific abilities to apply basic through advanced biostatistical methods Describing categorical and continuous data Comparison of two or more groups (independent or matched) where the measurements are categorical, ordinal, continuous, or censored survival data Examine the effects of one or more explanatory variables on a categorical, discrete, continuous or censored dependent variable Examine the appropriateness of underlying assumptions taking corrective actions where indicated and interpreting the fitted model in relation to the objectives of the analysis EPID 901 Advanced Epidemiology EPID 823 Advanced Biostatistics, plus course electives advised by supervisory committee EPID 999 Thesis, including outline, protocol and final dissertation Regular participation in departmental seminars, and thesis proposal/defences and defence of PhD thesis protocol and dissertation EPID 823 assignments and exam, as applicable Biostatistical components of the comprehensive exam Demonstrated mastery of concepts in the thesis protocol and final dissertation Calculate sample size or power for a given study design involving one or two more groups Advanced skills using statistical packages, including importing/exporting data, selecting appropriate forms of analysis, performing

12 analysis and interpreting the output in order to demonstrate the other learning outcomes 2. The ability to calculate epidemiological measures Measures of disease occurrence (eg. Incidence) and other population health indicators (infant versus perinatal mortality rate, life expectancy), measures of association between exposures and disease (eg. relative risk) and measures of public health impact (eg. Population attributable risk), patterns of disease occurrence (eg. trends, variations) Age-adjusted mortality and morbidity rates using the direct and indirect methods Validity of a screening and/or diagnostic test (sensitivity, specificity, positive predictive value, likelihood ratio etc.) 3 The ability to apply appropriate study designs for descriptive and analytical epidemiology See above under learning outcomes EPID 901 assignments and seminars, as applicable Epidemiological components of the comprehensive exam Demonstrated mastery of concepts in the thesis protocol and final dissertation As above

13 Professional Capacity/autonomy 1. Teaching skills through seminar, class and other presentations EPID 901 Advanced Epidemiology Course requirements for core and elective courses 2. Mentoring skills through collaboration with other students and research project personnel 3. Awareness of ethics in research EPID 823 Advanced Biostatistics, plus course electives advised by supervisor committee EPID 999 Thesis, including outline, protocol, and final dissertation Participation in department seminars TA evaluation reports (where applicable) Evaluation from thesis supervisors 4. Ability to disseminate research findings through publications in credible scholarly journals 5. Ability to facilitate group/team work and operate effectively as a member of a group or team Elicit problems and issues, frame problems in scientific terms, advise on appropriate research methods, advise on methods of data collection and analysis (including statistical analyses), interpret findings 6 Decision-making skills (through analytical, critical thinking and problem-solving) Regular participation in departmental seminar series, and thesis proposals and defences Ethics approval obtained for thesis Certification of ethics training from School of Graduate Studies Manuscripts submitted for publication as part of a manuscriptbased thesis (as applicable) of core and elective courses requiring group work Ongoing participation in research laboratory (or equivalent) for thesisbased research (as applicable) Evaluation from thesis supervisor(s) and course instructors

14 Communication Skills The ability to describe theories and methods of knowledge translation and dissemination of core and elective courses with modules/classes in knowledge translation Development of a plan for knowledge transfer and dissemination as part of the PhD thesis (as applicable)

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