Program in Clinical Research Design and Statistical Analysis MS in Clinical Research Design and Statistical Analysis (MS-CRDSA) Program provides a way for physicians, dentists, pharmacists, pharmacologists, and others who are involved in clinical research to develop expertise in research design and statistical analysis while continuing their professional employment. The MS-CRDSA program is specifically designed to improve the quality of clinical research and to address the shortage of persons with clinical expertise who are trained in research methods. These aims reflect the increasing complexity of clinical research, the increasing value of that clinical research, and the limited training of health care professionals in research design and statistical analysis. Because only a small number of students will become researchers, most clinical training programs include only minimal statistics and research design. MS-CRDSA program is especially designed to teach the skills and knowledge necessary for conducting clinical research.
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Computer Introduction |
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Clinical Research Seminar |
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Clinical Trials and Study Design |
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Data Collection and Threats to Validity |
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Methods of Epidemiology |
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Biostatistics |
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Computer Packages |
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Lab for Computer Packages |
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Legal Rules and Ethical Issues |
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Cost Utility and Decision Analysis |
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Statistical Methods for Epidemiology |
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Planning and Funding of CR |
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Survey Sampling |
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Statistical Analysis and Presentation of Topics |
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Longitudinal Models and Repeated Measures |
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Research Seminar |
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Clinical Research Symposia |
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Special Populations |
Content of the program
Can be defined in a number of ways: the purposes of research, research design concepts, data collection methods, and statistical or analytical methods. The program provides concepts and methods that relate to the purposes of clinical research, clinical epidemiology, clinical trials, program evaluation, and technology assessment. Research design concepts include the traditional approaches to the scientific method; the concepts of validity, reliability, causal relationships, role of randomization, standards for comparison, and sampling; as well as other recently developed methods of approaching decisions about research outcomes, such as decision analysis and cost-utility analysis. The data collection methods deal with instrumentation, questionnaire construction, non reactive measures, survey techniques, qualitative data, measurement and standardization problems, concepts and criteria of normalcy, and disease and diagnostic criteria. Statistical techniques for estimation and hypothesis testing, including comparison of proportions, chi-square test, comparison of means, analysis of variance and covariance, multiple regression analysis, logistic regression, and survival analysis, are presented. In addition to a comprehensive curriculum in research design and statistical analysis, other content relevant to clinical researchers is included: ethical and legal issues in clinical research, technical writing skills and proposal/report writing, management of research, and behavioral factors in clinical research. Students learn computer skills and concepts, including data file management, data organization, and use of statistical packages. Visiting faculty with experience in specialized research subjects meet with the students to discuss current problems in clinical research.
Practical Research Application of Course Methods
The methods taught in the Master of Science Program in Clinical Research Design and Statistical Analysis are applicable in many areas of research, including the following: Clinical Studies, Clinical Investigation, and Clinical Epidemiology. These studies concentrate on identifying the natural history of a disease, causal factors in disease, or treatment effects. The purposes of such studies include the definition of new syndromes or disease entities (case definition); describing normal organ function; developing new diagnostic methods or new diagnostic criteria, describing the distribution of a syndrome or entity in time, place, or person; and developing hypotheses about new therapies or etiology. The studies are usually observational or descriptive in nature and use quasi-experimental designs such as a before/after design. They sometimes involve stratification but almost never randomization.
Institutional Epidemiology and Post-Marketing Surveillance
These studies consider ways of monitoring rare events for the purposes of identifying possible new disease entities or syndromes and side effects of treatment modalities. They generally involve concomitant data collection for the purpose of identifying deviation from an expected value.
Computer Packages
An introduction to statistical computer packages in both network and microcomputer environments. Data organization and file management are also discussed.
Survey Sampling for Clinical Research
The main sampling methods used for surveys in clinical research are discussed, including probability sampling, simple random sampling, stratified sampling, systematic sampling, multi-stage sampling, sampling with probability proportional to size, cost factors, sampling errors, non response, sampling frame problems, non sampling errors, and practical designs and procedures.
Biostatistics for Clinical Researchers
Basic probability theory and statistical methods used by biostatisticians. These include design of experiments, point and interval estimation, and hypothesis testing. New topics include simple and multiple regression methods, and analysis of variance and covariance.
Statistical Methods for Epidemiology
Statistical methods commonly used in clinical research, with an emphasis on choosing appropriate procedures and subsequent interpretation. 2 x 2 tables, Mantel-Haenszel, tests for trend in risk, methods for matched designs, logistic regression, and Cox models.
Biostatistical Modeling in Clinical Research
This is about statistical modeling, with an emphasis on models for correlated data that arise when subjects are repeatedly measured or are clustered. These models, called mixed models, are extensions of linear and nonlinear regression and analysis of variance. Examples will be drawn from clinical studies, such as multi-arm biomarker studies and crossover trials. Analyses of population pharmacokinetics and longitudinal data will also be discussed. Hands-on data analysis and presentation using standard computer software for linear and nonlinear analysis will be emphasized. Course goals include the ability to formulate and evaluate a model, read the scientific literature that employs these models, interact fruitfully with data modeling specialists, and present the results of these models mathematically and graphically.
Statistical Analysis and Presentation of Research Topics
This course is intended to integrate and apply biostatistical and epidemiologic methods presented in other OJ/OC courses to clinical research data. Students will identify the scientific objectives of a clinical research study and develop a statistical analysis strategy appropriate for those objectives; plan strategies for statistical design and analysis and implement these strategies; learn to be aware of problems that arise in data collection; learn to communicate through presentation of oral and written reports and through student and faculty critiques of these reports; learn to communicate results of clinical research projects in clear, accurate, concise language; learn appropriate writing styles and formats for clinical research articles; and apply writing skills to research papers.
Clinical Research Seminar
A series of seminars that illustrate the definitions, functions and utility of clinical research; design of clinical research; and the application of statistics to clinical research, presented by visiting faculty experienced in clinical research.
Clinical Trials and Study Design
A review of the ways clinical trials are used as a research tool: design of clinical trials, randomization, sample size, compliance, masking, analysis of clinical trials data and stopping rules. The course also considers advantages and limitations of alternative types of quasi-experimental designs, nonequivalent control group designs, interrupted time-series designs, case series, cross-over designs, meta-analysis.
Planning and Funding Clinical Research
This course encompasses four main areas of exploration
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The preparation of a written document whose focus is on an integrated research plan, including specific aims, background and significance, design, methods, logistical implementation and statistical analysis, and fiscal requirements |
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The evaluation of clinical research plans |
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Identification of funding sources and their requirements |
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Identification of the role of the research administrator in facilitating clinical research |
Methods of Epidemiology: Measure and Measurement
An overview and introduction to the measure of association used in epidemiologic studies, as well as a description of the nature and characteristics of major epidemiologic study designs.
Psychosocial Aspects of Research
Data Collection and Threats to Validity
Conceptual and operational issues in psychosocial research are discussed. Topics include: quality of life measurement, models of health decision-making, measuring attitudes and beliefs, and behavioral threats to validity, such as patient adherence and patient-provider relationships. Designing a survey instrument, writing items, and selecting a method of data collection are also emphasized.
Legal Rules and Ethical Issues for Clinical Research
The course is organized in two parts: Part I studies the history of research regulations, requirements for ethical research, informed consent, institutional review boards, protection of special at-risk populations, deception in research, and future directions of regulations on research. Each participant presents a research design and the class analyzes its legal aspects. Part II is a series of lecture discussions on current ethical issues in clinical research.
Cost Utility Analysis and Clinical Research Economic issues and analytical techniques relevant to the performance and evaluation of clinical research are investigated. Special emphasis is placed on the theory, practice, usefulness and limitations of cost-benefit and cost-effectiveness analysis.
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