Simon Fraser University
Engaging the World

Course Outlines

Fall 2017 - GERO 803 G100

Analytical Techniques for Gerontological Research (4)

Class Number: 4662

Delivery Method: In Person

Overview

  • Course Times + Location:

    Sep 5 – Dec 4, 2017: Mon, 9:30 a.m.–12:20 p.m.
    Vancouver

Description

CALENDAR DESCRIPTION:

This course has been specifically designed to provide training in quantitative data analysis using SPSSx Programming Language with a focus on behavioral research problems in gerontology.

COURSE DETAILS:

This course has been specifically designed to provide training in quantitative statistics for graduate students within the context of SPSS programming language. A selection of analytical techniques that are most appropriate for analysis of behavioural data related to aging issues will be highlighted. In addition to theoretical principles within statistical modelling, the course will emphasize applications of actual data and interpretation of those data. Access to the 2008 Canadian Community Health Survey 4.2 Healthy Aging Module will be used for instruction and will be made available to students. Additional data sets will also be available for students interested in  research questions not answerable using the CCHS. These include: other CCHSs; all cycles of the General Social Survey;  the cross-sectional and longitudinal panels of the National Population Health Surveys, the 1991 and 1996 panels of the Canadian Study of Health and Aging; and any data set available through the SFU Data Repository. Students will have an opportunity to select one of these data sets, or may choose to work on one of their own population or evaluation study data sets, for their assignments. The techniques to be covered include: descriptive statistics, factor analysis, reliability analysis, bivariate analyses, ordinary least squares regression, logistic regression, path analysis and LISREL, event history/survival analysis, and graphical interaction modeling. Assignments will be conducted on a subset of the techniques, due to limited time. Classes will be comprised of combinations of lecture material, computer modules, and seminar presentations.

Grading

  • Four computer assignments 80%
  • Seminar presentation of final assignment 20%

Materials

REQUIRED READING:

SPSS (2017) IBM SPSS Statistics Documentation Manual (http://www-01.ibm.com/support/docview.wss?uid=swg27047033#en)
SPSS Statistics Standard GradPack 24.0 (http://www.onthehub.com/spss/)
Abu-Bader, S. (2010). "Advanced & Multivariate Statistical Methods for Social Science Research: With a Complete SPSS Guide". Chicago. (Lyceum)

RECOMMENDED READING:

Tabachnick, B. & Fidell, L. (2007). "Using Multivariate Statistics" (5th Edition) Toronto. Allyn & Brown.

Graduate Studies Notes:

Important dates and deadlines for graduate students are found here: http://www.sfu.ca/dean-gradstudies/current/important_dates/guidelines.html. The deadline to drop a course with a 100% refund is the end of week 2. The deadline to drop with no notation on your transcript is the end of week 3.

Registrar Notes:

SFU’s Academic Integrity web site http://students.sfu.ca/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating.  Check out the site for more information and videos that help explain the issues in plain English.

Each student is responsible for his or her conduct as it affects the University community.  Academic dishonesty, in whatever form, is ultimately destructive of the values of the University. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the University. http://www.sfu.ca/policies/gazette/student/s10-01.html

ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS