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21 - 30 of 59 results for: HRP

HRP 238: Genes and Environment in Disease Causation: Implications for Medicine and Public Health (HUMBIO 159)

The historical, contemporary, and future research and practice among genetics, epidemiology, clinical medicine, and public health as a source of insight for medicine and public health. Genetic and environmental contributions to multifactorial diseases; multidisciplinary approach to enhancing detection and diagnosis. The impact of the Human Genome Project on analysis of cardiovascular and neurological diseases, and cancer. Ethical and social issues in the use of genetic information. Prerequisite: basic course in genetics; for undergraduates, Human Biology core or equivalent or consent of instructor.
Terms: Win | Units: 2-3
Instructors: Popat, R. (PI)

HRP 239: Statistical Methods for Group Comparisons and Causal Inference (EDUC 260X, STATS 209)

Critical examination of statistical methods in social science applications, especially for cause and effect determinations. Topics: path analysis, multilevel models, matching and propensity score methods, analysis of covariance, instrumental variables, compliance, longitudinal data, mediating and moderating variables. See http://web.stanford.edu/~rag/stat209/. Prerequisite: intermediate-level statistical methods.
Terms: Win | Units: 3

HRP 241: Measuring Global Health (HUMBIO 129M, MED 231)

Open to MD, graduate, and undergraduate students. Assessing the global burden of disease, its distribution among and within countries, its causes, and appropriate interventions requires rigorous quantitative approaches. This course develops skills in these areas by critically examining questions like: How do we know who is sick and where? How are risk factors incorporated into our projections of future disease trends? How do we combine mortality and morbidity in a meaningful way? What works for improving health efficiently? Workshops build familiarity with relevant data and their analysis. Prerequisite: coursework in statistics, biostatistics, quantitative epidemiology, econometrics, or equivalent.
Last offered: Spring 2013 | Repeatable for credit

HRP 251: Design and Conduct of Clinical Trials

The rationale for phases 1-3 clinical trials, the recruitment of subjects, techniques for randomization, data collection and endpoints, interim monitoring, and reporting of results. Emphasis is on the theoretical underpinnings of clinical research and the practical aspects of conducting clinical trials.
Terms: Spr | Units: 3

HRP 252: Outcomes Analysis (BIOMEDIN 251, MED 252)

Methods of conducting empirical studies which use large existing medical, survey, and other databases to ask both clinical and policy questions. Econometric and statistical models used to conduct medical outcomes research. How research is conducted on medical and health economics questions when a randomized trial is impossible. Problem sets emphasize hands-on data analysis and application of methods, including re-analyses of well-known studies. Prerequisites: one or more courses in probability, and statistics or biostatistics.
Terms: Spr | Units: 4

HRP 256: Economics of Health and Medical Care (BIOMEDIN 156, BIOMEDIN 256, ECON 126)

Institutional, theoretical, and empirical analysis of the problems of health and medical care. Topics: demand for medical care and medical insurance; institutions in the health sector; economics of information applied to the market for health insurance and for health care; measurement and valuation of health; competition in health care delivery. Graduate students with research interests should take ECON 249. Prerequisites: ECON 50 and either ECON 102A or STATS 116 or the equivalent. Recommended: ECON 51.
Terms: Aut, Win | Units: 5

HRP 258: Introduction to Probability and Statistics for Clinical Research

Open to medical and graduate students; required of medical students in the Clinical Research Scholarly Concentration. Tools to evaluate medical literature. Topics include random variables, expectation, variance, probability distributions, the central limit theorem, sampling theory, hypothesis testing, confidence intervals, correlation, regression, analysis of variance, and survival analysis.
Terms: Spr | Units: 3
Instructors: Sainani, K. (PI)

HRP 259: Introduction to Probability and Statistics for Epidemiology

Topics: random variables, expectation, variance, probability distributions, the central limit theorem, sampling theory, hypothesis testing, confidence intervals. Correlation, regression, analysis of variance, and nonparametric tests. Introduction to least squares and maximum likelihood estimation. Emphasis is on medical applications. Differential between 3 and 4 units is the amount of out-of-class work required.
Terms: Aut | Units: 3-4
Instructors: Sainani, K. (PI)

HRP 260A: Workshop in Biostatistics (STATS 260A)

Applications of statistical techniques to current problems in medical science. To receive credit for one or two units, a student must attend every workshop. To receive two units, in addition to attending every workshop, the student is required to write an acceptable one page summary of two of the workshops, with choices made by the student.
Terms: Aut | Units: 1-2 | Repeatable for credit

HRP 260B: Workshop in Biostatistics (STATS 260B)

Applications of statistical techniques to current problems in medical science. To receive credit for one or two units, a student must attend every workshop. To receive two units, in addition to attending every workshop, the student is required to write an acceptable one page summary of two of the workshops, with choices made by the student.
Terms: Win | Units: 1-2 | Repeatable for credit
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