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Graduate Course Proposal Form Submission Detail - PHC6092

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Current Status: -
Campus: Tampa
Submission Type: New
Course Change Information (for course changes only):
Comments:


  1. Department and Contact Information

    Tracking Number Date & Time Submitted
    5109 2014-10-20
     
    Department College Budget Account Number
    Epidemiology and Biostatistics PH 640300-10000-PUB001-0000000
     
    Contact Person Phone Email
    Wei Wang 8139746978 wwang@health.usf.edu

  2. Course Information

    Prefix Number Full Title
    PHC 6092 Applications of Advanced Biostatistical Methods

    Is the course title variable? N
    Is a permit required for registration? N
    Are the credit hours variable? N
    Is this course repeatable? Y
    If repeatable, how many times? 2

    Credit Hours Section Type Grading Option
    3 C - Class Lecture (Primarily) -
     
    Abbreviated Title (30 characters maximum)
    Appl of Adv Biostat Methods
     
    Course Online? Percentage Online
    C - Face-to-face (0% online) 100

    Prerequisites

    PHC 6050

    Corequisites

    None

    Course Description

    This course introduces advanced biostatistical modeling approaches for continuous, categorical and time to event outcome data with emphasis on their applications in the field public health.


  3. Justification

    A. Please briefly explain why it is necessary and/or desirable to add this course.

    Offered as enrichment course (not part of program/concentration/certificate)

    B. What is the need or demand for this course? (Indicate if this course is part of a required sequence in the major.) What other programs would this course service?

    The course is designed for non-epidemiology and biostatistics graduate students of Public Health as well as and other students who have an interest in improving their analytical skills beyond t-tests.

    The department of Epidemiology and Biostatistics current offers three separate courses that cover the proposed topics of this new course. These existing courses focus more on the technical/mathematical side of the methodologies. However, most of the non-epidemiology and biostatistics graduate students who would like to improve their analytic skills do not have time or math training to go through these existing courses. The new proposed course may fill this blank.

    This course was piloted in 2013 summer with nine doctoral students and was taught again in 2016 with twenty students.

    C. Has this course been offered as Selected Topics/Experimental Topics course? If yes, how many times?

    Yes, 2 times

    D. What qualifications for training and/or experience are necessary to teach this course? (List minimum qualifications for the instructor.)

    Minimum qualifications for the instructor: doctoral degree on statistics or biostatistics


  4. Other Course Information

    A. Objectives

    The main objective of this course is to offer training of advanced biostatistical methods including general linear regression, Poisson regression, logistic regression, proportional hazards regression, and nonparametric regression.

    B. Learning Outcomes

    Upon course completion, the student will be able to

    * Understand the reasoning behind these modeling approaches,

    * Choose appropriate analysis methods based on the research questions and characteristics of the data,

    * Build and validate statistical models with statistical criteria,

    * Interpret the analysis results in depth.

    C. Major Topics

    * Introduction to statistical modeling

    * General linear regression model: estimation, testing, model building, diagnostics and interpretation.

    * Introduction to categorical data analysis

    * Logistic regression, Poisson regression, and other generalized linear models

    * Introduction to survival analysis

    * Proportional hazards model

    * Parametric regression models for survival data

    * Selected advanced topics

    D. Textbooks

    Required Text: Applied Linear Models with SAS, by Zelterman, Daniel, Cambridge University Press, ISBN: 9780521761598

    E. Course Readings, Online Resources, and Other Purchases

    Applied Linear Regression Models (4th Edition) by Kutner, M. H., Nachtsheim, C. J, and Neter, J. Published by McGraw-Hill/Irwin, 2004. ISBN: 007310874X

    An Introduction to Categorical Data Analysis (2nd edition) by Alan Agresti. Published by John Wiley & Sons, 2007. ISBN-10: 0471226181.

    Applied Survival Analysis (2nd edition) by David Hosmer, Stanley Lemeshow, and Susanne May. Published by John Wiley & Sons, 2008. ISBN-10: 047154994.

    F. Student Expectations/Requirements and Grading Policy

    Students are expected to actively participate in all course activities including attending lectures, working on homework assignments and turning them in in time, and attending exams.

    Grading events include classroom participation (20%), homework assignments (30%), individual project (20%), group project (20%) and exam (10%)

    G. Assignments, Exams and Tests

    1. Exam/projects: Students will have one final exam, one individual project and one group project.

    2. Homework: Students will have three homework assignments on top of the projects.

    3. Participation: Students are expected to actively engage in class discussions and activities.

    H. Attendance Policy

    Course Attendance at First Class Meeting Policy for Graduate Students: For structured courses, 6000 and above, the College/Campus Dean will set the first-day class attendance requirement. Check with the College for specific information. This policy is not applicable to courses in the following categories: Educational Outreach, Open University (TV), FEEDS Program, Community Experiential Learning (CEL), Cooperative Education Training, and courses that do not have regularly scheduled meeting days/times (such as, directed reading/research or study, individual research, thesis, dissertation, internship, practica, etc.). Students are responsible for dropping undesired courses in these categories by the 5th day of classes to avoid fee liability and academic penalty. (See USF Regulation Registration - 4.0101,

    http://usfweb2.usf.edu/usfgc/ogc%20web/currentreg.htm)

    Attendance Policy for the Observance of Religious Days by Students: In accordance with Sections 1006.53 and 1001.74(10)(g) Florida Statutes and Board of Governors Regulation 6C-6.0115, the University of South Florida (University/USF) has established the following policy regarding religious observances: (http://usfweb2.usf.edu/usfgc/gc_pp/acadaf/gc10-045.htm)

    In the event of an emergency, it may be necessary for USF to suspend normal operations. During this time, USF may opt to continue delivery of instruction through methods that include but are not limited to: Blackboard, Elluminate, Skype, and email messaging and/or an alternate schedule. Itís the responsibility of the student to monitor Blackboard site for each class for course specific communication, and the main USF, College, and department websites, emails, and MoBull messages for important general information.

    I. Policy on Make-up Work

    Homework: All homework is to be solely the work of the student. Late homework submission within 3 days of the due time will receive 50% point deduction. Homework submission passes the 3 days line will not be accepted.

    Exam: Students who miss any exam, without providing information with 3 days of the missed exam, will receive a 0 grade for that examination.

    J. Program This Course Supports

    MPH, MSPH and PHD programs of Public Health


  5. Course Concurrence Information

    Graduate programs of Aging Studies, Applied Anthropology, Biology Biomedical Engineering, Biotechnology, Child and Adolescent Behavioral Health, Criminology, Environmental Engineering, Environmental Science and Policy, Integrative Biology, Marine Science, Medical Sciences and Nursing.



- if you have questions about any of these fields, please contact chinescobb@grad.usf.edu or joe@grad.usf.edu.