2020-2021 2021-2022 2022-2023 2023-2024 2024-2025
Browse
by subject... 		    Schedule
view... 		 

1 - 10 of 23 results for: EPI ; Currently searching winter courses. You can expand your search to include all quarters

print preview printer friendly page

EPI 199: Undergraduate Research

Students undertake investigations sponsored by individual faculty members. Prerequisite: consent of instructor.
Terms: Aut, Win, Spr, Sum | Units: 1-18 | Repeatable for credit (up to 99 units total)

EPI 202: R Fundamentals for Health Research (CHPR 202)

This introductory course is a practicum in which students will learn the basics of R, a free, open-source statistical analysis software program, and use the programming language to analyze health datasets by application of classical statistical methods. A familiarity with basic descriptive and inferential statistics is required (completion of HRP 258/259, or concurrent enrollment in an appropriate statistics/biostatistics course). It is assumed that students will have no (or very little) prior experience with R. This course is a flipped classroom, where lecture content will be viewed at home before in-class meetings with hands-on coding practice by each student on their own computers. Priority for enrollment given to CHPR masters students, who must enroll for a letter grade.
Terms: Win | Units: 1-2
Instructors: Jaros, S. (PI) ; Nguyen, A. (PI) ; Park, L. (PI) ; Diamond, E. (TA)

EPI 206: Meta-research: Appraising Research Findings, Bias, and Meta-analysis (CHPR 206, MED 206, STATS 211)

Open to graduate, medical, and undergraduate students. Appraisal of the quality and credibility of research findings; evaluation of sources of bias. Meta-analysis as a quantitative (statistical) method for combining results of independent studies. Examples from medicine, epidemiology, genomics, ecology, social/behavioral sciences, education. Collaborative analyses. Project involving generation of a meta-research project or reworking and evaluation of an existing published meta-analysis. Prerequisite: knowledge of basic statistics.
Terms: Win | Units: 3
Instructors: Ioannidis, J. (PI) ; Kvarven, A. (PI)

EPI 219: Evaluating Technologies for Diagnosis, Prediction and Screening

New technologies designed to monitor and improve health outcomes are constantly emerging, but most fail in the clinic and in the marketplace because relatively few are supported by reliable, reproducible evidence that they produce a health benefit. This course covers the designs and methods that should be used to evaluate technologies to diagnose patients, predict prognosis or other health events, or screen for disease. These technologies can include devices, statistical prediction rules, biomarkers, gene panels, algorithms, imaging, or any information used to predict a future or a previously unknown health state. Specific topics to be covered include the phases of test development, how to frame a proper evaluation question, measures of test accuracy, Bayes theorem, internal and external validation, prediction evaluation criteria, decision analysis, net-utility, ROC curves, c-statistics, net reclassification index, decision curves and reporting standards. Examples of technology assessm more »
New technologies designed to monitor and improve health outcomes are constantly emerging, but most fail in the clinic and in the marketplace because relatively few are supported by reliable, reproducible evidence that they produce a health benefit. This course covers the designs and methods that should be used to evaluate technologies to diagnose patients, predict prognosis or other health events, or screen for disease. These technologies can include devices, statistical prediction rules, biomarkers, gene panels, algorithms, imaging, or any information used to predict a future or a previously unknown health state. Specific topics to be covered include the phases of test development, how to frame a proper evaluation question, measures of test accuracy, Bayes theorem, internal and external validation, prediction evaluation criteria, decision analysis, net-utility, ROC curves, c-statistics, net reclassification index, decision curves and reporting standards. Examples of technology assessments and original methods papers are used. Knowledge of statistical software is not required, although facility with at least Excel for basic calculations is needed. Open to students with an understanding of introductory biostatistics, epidemiologic and clinical research study design. Undergraduates may enroll with consent of instructor.
Terms: Win | Units: 3
Instructors: Goodman, S. (PI)

EPI 224: Genetic Epidemiology (GENE 230)

This course presents fundamental concepts and methods in genetic epidemiology, with examples from genetic studies of common, complex diseases (e.g., cancer). It will provide an overview of various study designs and covers fundamental analyses, inferences, and their strengths and limitations. The course will cover the following topics: assessing genetic influences on disease (e.g., heritability); family- and population-based association study designs; candidate gene and genome-wide association studies of common and rare genetic variants; transcriptome-wide association studies; polygenic risk scores; bias due to population stratification; gene-environment interactions and epistasis; studies of diverse populations; software and web-based data resources; ethical issues in genetic epidemiology; and applications of genetic epidemiology to clinical practice and public health. Guest speakers will discuss these concepts through the lens of various diseases. The course will include a project proposal based on student's research interests. Prerequisite: introductory biostatistics, epidemiology, and/or genetics (or by permission of the instructor).
Terms: Win | Units: 3
Instructors: Kachuri, L. (PI) ; Witte, J. (PI)

EPI 226: Intermediate Epidemiologic and Clinical Research Methods

The principles of study design, measurement, confounding, effect modification, and strategies for minimizing bias in clinical and epidemiologic studies. Prerequisite: EPI 225 or consent of instructor.
Terms: Win | Units: 3
Instructors: Benjamin-Chung, J. (PI) ; Parikh, R. (TA)

EPI 229: Stanford CTSA Scholars Seminar

Preference to trainees awarded Stanford internal KL2, TL1 grants. Focus is on students and junior faculty who have received a CTSA KL2 or TL1 Award. Discussions include progress and challenges involved in starting and conducting clinical research, current courses, time management and resources; support from peers; education and professional development. All scholars are required to attend a weekly seminar series meeting throughout the year that will cover an array of cross-cutting methodological topics with published examples of implementation. Prerequisite: Awarded a CTSA KL2, TL1 Grant or Spectrum UL1
Terms: Aut, Win, Spr | Units: 1 | Repeatable 8 times (up to 8 units total)
Instructors: Asch, S. (PI) ; Linos, E. (PI)

EPI 231: Epidemiology of Infectious Diseases

Principles of the transmission of the infectious agents (viruses, bacteria, rickettsiae, mycoplasma, fungi, and protozoan and helminth parasites). The role of vectors, reservoirs, and environmental factors. Pathogen and host characteristics that determine the spectrum of infection and disease. Endemicity, outbreaks, and epidemics of selected infectious diseases. Principles of control and surveillance.
Terms: Win | Units: 3
Instructors: Andrews, J. (PI) ; Maldonado, Y. (PI) ; Parsonnet, J. (PI)

EPI 236: Epidemiology Research Seminar

Weekly forum for ongoing epidemiologic research by faculty, staff, guests, and students, emphasizing research issues relevant to disease causation, prevention, and treatment. May be repeated for credit.
Terms: Aut, Win, Spr | Units: 1 | Repeatable 15 times (up to 15 units total)

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

Prerequisite: Any 3 of 2A 2B 3A 3B 4A 4B or Bio 82 or Bio 84 or HumBio major/minor. 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. This course must be taken for a minimum of 3 units and a letter grade to be eligible for Ways credit. Basic knowledge of genetics and human physiology to better understand chronic diseases. Preferably have taken the statistics core or concurrently enrolled in it.
Terms: Win | Units: 2-3
Instructors: Popat, R. (PI) ; Pesantez, S. (TA)
Filter Results:
term offered
updating results...
teaching presence
updating results...
number of units
updating results...
time offered
updating results...
days
updating results...
UG Requirements (GERs)
updating results...
component
updating results...
career
updating results...
© Stanford University | Terms of Use | Copyright Complaints