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CHS 212
Winter 2013
CHS 212,syllabus.Winter 2013 FINAL 1
COMMUNITY HEALTH SCIENCES 212
ADVANCED SOCIAL RESEARCH METHODS IN HEALTH
Winter Quarter 2013
Classroom: A1-241 CHS
Day and Time: Monday, Wednesday, Friday 8:00-10:00 A.M.
IBM #: 840-072-200
Prerequisites: CHS 211B, Biostat 100B, Biostat 406
Instructor: Linda B. Bourque, Ph.D. [email protected]
Office: 41-230 CHS
Office Hours: Monday and Wednesday, 10:00-11:30 A.M.
Reader: Melissa Kelley
Office: 41-230 CHS
Office Hours: TBA
Web Site: http://ccle.ucla.edu
Readings
Required
1. Donald J. Treiman, Quantitative Data Analysis: Doing Social Research to Test Ideas.
John Wiley & Sons, 2009.
2. Morris Rosenberg, The Logic of Survey Analysis. NY: Basic Books, Inc., 1968. This
book is out of print, and will be available on the web site.
Other materials are referenced in the course schedule and should be considered as needed.
Many of these are available on the web site.
On Web Site:
1. Aday, L.A, Cornelius, Designing and Conducting Health Surveys, A Comprehensive
Guide, 3rd
Edition, Chapter 4, Thinking Through the Relationships Between Variables, pp.
81-99, San Francisco: Jossey-Bass, 2006.
2. The American Association for Public Opinion Research. 2009. Standard Definitions:
Final Dispositions of Case Codes and Outcome Rates for Surveys. 6th
edition. Lenexa,
Kansas: AAPOR.
3. Becker, H.S, Geer, B. Participant Observation: The Analysis of Qualitative Field Data. IN:
Adams, R.N., Preiss, J.J. Human Organization Research: Field Relations and Techniques.
Homewood, Illinois: The Dorsey Press, Inc., 1960, pp. 267-289.
4. Betson, D.M., Citro, C.F., Michael, R.T. Recent Developments for Poverty Measurement
in U.S. Official Statistics. Journal of Official Statistics 2000; 2:87-111.4.
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5. Binson, D., Canchola, J.A., Catania, J.A. Random Selection in a National Telephone
Survey: A Comparison of the Kish, Next-Birthday, and Last-Birthday Methods. Journal
of Official Statistics 2000; 16:53-59.
6. Bourque, L.B. “Coding.” In M.S. Lewis-Beck, A. Bryman, T.F. Liao, Editors, The Sage
Encyclopedia of Social Science Research Methods, Volume 1, Thousand Oaks, CA: Sage
Publications, 2003, pp. 132-136.
7. Bourque, L.B. “Coding Frame.” In M.S. Lewis-Beck, A. Bryman, T.F. Liao, Editors, The
Sage Encyclopedia of Social Science Research Methods, Volume 1, Thousand Oaks, CA:
Sage Publications, 2003, pp. 136-137.
8. Bourque, L.B. “Transformations.” In M.S. Lewis-Beck, A. Bryman, T.F. Liao, Editors,
The Sage Encyclopedia of Social Science Research Methods. Volume 3, Thousand Oaks,
CA: Sage Publications, 2003, pp. 1137-1138.
9. Davis, J.A. Elementary Survey Analysis. Englewood Cliffs, NJ: Prentice-Hall, Inc., 1971.
10. Dixon, J. K. Statistical Methods for Health Care Research , 2nd
Edition, Chapter 14,
Grouping Techniques, pp. 245-274., J.P. Lippincott, 1993.
11. Engelhart, R. The Kish Selection Procedure. Unpublished document. Institute for Social
Science Research, Survey Research Center, UCLA, no date.
12. Gaziano, C. Comparative Analysis of Within-Household Respondent Selection
Techniques. Public Opinion Quarterly 2005; 69:124-157.
13. Kalton, G. Developments in Survey Research in the Past 25 Years. Survey Methodology
2000; 26:3-10.
14. McKennell, A.C. Attitude scale construction. In O’Muircheataugh, C.A., Payne, C. (eds.),
Exploring Data Structures, Vol. I: The Analyses of Survey Data. London: John Wiley &
Sons, 1977, pp. 182-220.
15. Munro, B.H., E.B. Page. Statistical Methods for Health Care Research, 2nd
Edition,
Chapter 14, Grouping Techniques, 1993, pp. 245-274.
16. Rosenberg, M. The Logic of Survey Analysis. NY: Basic Books, Inc., 1968.
17. U.S. Department of the Interior, Geological Survey. U.S. Department of the Interior,
Geological Survey, Earthquake Report, no date.
18. Wallis, W.A., Roberts, H.V. How to read a table. In Statistics: A New Approach. The Free
Press, 1956, pp. 270-279.
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Readings—Recommended Books
1. Afifi, A.A., May, S., Clark, V.A., Practical Multivariate Analysis, 5th Edition. NY:
Chapman & Hall, 2011.
2. Bourque, L.B., Clark, V.A. Processing Data: The Survey Example. Newbury Park, CA:
Sage Publications, 1995.
3. Bourque, L.B., Fielder, E.P. How to Conduct Self-Administered and Mail Surveys, 2nd
Edition. Thousand Oaks, CA: Sage Publications, 2003.
4. Bourque, L.B., Fielder, E.P. How to Conduct Telephone Surveys, 2nd
Edition. Thousand
Oaks, CA: Sage Publications, 2003.
5. Davis, J. The Logic of Causal Order. Thousand Oaks, CA: Sage Publications, 1985.
Readings on Disasters 1. Background readings on disasters that you might want to use as resources. Most are
available in the University Research Library.
1) Alexander, D. Natural disasters: A framework for research and teaching. Disasters
15(3):209-226, 1991.
2) American Behavioral Scientist 13:323-456, 1970; Special issue on disaster.
3) Barton, A.H. Communities in Disaster. Garden City, NY: Doubleday & Co., 1969.
4) Bolin, R., Stanford, L. Shelter, housing and recovery: A comparison of U.S.
disasters. Disasters 15(1):24-34, 1991.
5) Bourque, L.B., Cherlin, A., Reeder, L.G. Agencies and the Los Angeles
earthquake. Mass Emergencies 1:217-228, 1996.
6) Bourque, L.B., Mileti, D.S., Kano, M., Wood, M. M. Who prepares for terrorism ?
Environment and Behavior 2012; 44(3): 374-409. published online 2 December
2010, DOI: 10.1177/0013916510390318.
7) Bourque LB, Regan R, Kelley MM, Wood MM, Kano M, Mileti DS. An Examination of
the Effect of Perceived Risk on Preparedness Behavior. Environment and Behavior,
Published online March 26, 2012. Available at
http://eab.sagepub.com/content/early/2012/03/21/0013916512437596.
8) Bourque, L.B., Russell, L.A., Goltz, J.D. Human behavior during and immediately
after the earthquake. The Loma Prieta, California, Earthquake of October 17,
1989--Public Response. United States Geological Service (USGS) Professional
Paper 1553-B, 1993.
9) Bourque, L.B., Shoaf, K.I., Nguyen, L.H. Survey research. International Journal
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of Mass Emergencies and Disasters 15:71-101, 1997.
10) Burby, R.J., Editor, Cooperating with Nature, Confronting Natural hazards with
Land-Use Planning for Sustainable Communities. Joseph Henry Press,
Washington, D.C., 1998.
11) Drabek, T.E., Key, W.H. The impact of disaster on primary group linkages. Mass
Emergencies 1: 89-105, 1976.
12) Fritz, C.E. Disaster. In Merton, R.K., Nisbet, R.A. (eds.), Contemporary Social
Problems. NY: Harcourt, Brace & World, Inc., 1961, pp. 651-694.
13) Glass, R.I., Urrutia, J.J., Sibony, S. et al. Earthquake injuries related to housing in
a Guatemalan village. Science 197-638-643, 1977.
14) Goltz, J.A., Russell, L.A., Bourque, L.B. Initial response to a rapid onset disaster:
A case study of the October 1, 1987 Whittier Narrows earthquake. International
Journal of Mass Emergencies and Disasters 10(1):43-69, 1992.
15) Kano M, Wood MM, Bourque LB, Mileti DS. Terrorism Preparedness and Exposure
Reduction since 9/11: The Status of Public Readiness in the United States. Journal of
Homeland Security and Emergency Management 2011; 8. DOI:10.2202/1547-7355.1807.
Available at: http://www.bepress.com/jhsem/vol8/iss1/37.
16) Koenig, K.L, Schultz, C.H. Disaster Medicine: Comprehensive Principles and
Practices. Cambridge University Press, 2010.
17) Kunreuther, H., R.J. Roth, Editors, Paying the Price, The Status and Role of
Insurance Against Natural Disasters in the United States. Washington, D.C.,
Joseph Henry Press, 1998.
18) Lechat, M.F. The international decade for natural disaster reduction: Background
and objectives. Disasters 14(1):1-6, 1990.
19) Lindell, M.K., Perry, R.W. Household adjustment to earthquake hazard: A review
of research. Environment and Behavior 32: 590-630.
20) Lindell, M.K., Arlikatti, S., Prater, C.S. Why people do what they do to protect
against earthquake risk: Perceptions of hazard adjustment attributes. Risk Analysis
29: 1072-1088, 2009.
21) Logue, J.N. Disasters, the environment, and public health: Improving our response.
Am J Public Health 86(9):1207-1210, 1996.
22) Mileti, D.S. Human adjustment to the risk of environmental extremes. Sociology
and Social Research 64(3):327-347, 1980.
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23) Mileti, D.S. Disasters by Design, A Reassessment of Natural Hazards in the
United States. Washington, D.C., Joseph Henry Press, 1999.
24) Mileti, D.S., Fitzpatrick, C. The causal sequence of risk communication in the
Parkfield Earthquake Prediction Experiment. Risk Analysis 12(3):393-400, 1992.
25) Pantelic, J. The link between reconstruction and development. Land Use Policy
October:343-347, 1991.
26) Perry, R.W. Evacuation decision-making in natural disasters. Mass Emergencies
4:25-38, 1979.
27) Perry, R.W. The Social Psychology of Civil Defense. Lexington, MA: Lexington
Books, 1982.
28) Quarantelli, E.L., Dynes, R.R. Response to social crisis and disaster. Annual
Review of Sociology 2:23-49, 1977.
29) Rodríguez, H., Quarantelli, E.L., Dynes, R.R. Handbook of Disaster Research.
New York City, NY: Springer, 2006.
30) Russell, L.A., Goltz, J.D., Bourque, L.B. Preparedness & hazard mitigation actions
before and after two earthquakes. Environment & Behavior 27(6):744-770, 1995.
31) Tierney, K.J., M.K. Lindell, R.W. Perry. Facing the Unexpected, Disaster
Preparedness and Response in the United States. Washington, D.C., Joseph Henry
Press, 2001.
32) Trainer, P., Bolin, R. Persistent effects of disasters on daily activities: A cross-
cultural comparison. Mass Emergencies 1:279-290, 1976.
33) Wood MM, Kano M, Mileti DS, Bourque LB. Reconceptualizing Household Disaster
Readiness: The “Get Ready” Pyramid. Journal of Emergency Management. 2009; 7(4):
25-37.
34) Wood, M.M., Mileti, D.S.,Kano, M., Kelley, M. M., Regan, R., Bourque, L.B.
Communicating actionable risk for terrorism and other hazards. Risk Analysis.
2012; 32:601-615. Published online:
http://onlinelibrary.wile.com/doi/10.1111/j.1539-6924.2011.01645.x/pdf.
2. Other readings of possible interest.
1) Bailar, B.A. The Past is Prologue. Survey Methodology 2000; 26:21-30.
2) Bellhouse, D.R. Survey Sampling Theory Over the Twentieth Century and its
Relation to Computing Technology. Survey Methodology 2000; 26:11-20.
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3) Stevens, G., Cho, J.H. Socioeconomic indexes and the New 1980 Census
Occupational Classification Scheme. Social Science Research 14:142-168, 1985.
4) Stevens, G., Featherman, D. A revised socioeconomic index of occupational status.
Social Science Research 10:364-395, 1981.
5) U.S. Census, Questions on Race/Ethnicity, 2000, 2010.
3. The data set, questionnaire, and specifications for the National Survey of Disaster
Experiences and Preparedness will be downloaded from the web during the first lab [See
section D. Data Set of this syllabus].
4. American Psychological Association. Publication Manual (5th edition). Washington,
D.C., 2001. (Resource; available in libraries or Student Store, Ackerman Union.)
I have never found a textbook that ideally fulfills the needs of this course. The books listed above
will cover some of the topics quite well and others not at all. Supplementary handouts which may
help in some cases will be provided when available. Over the quarter, I will post handouts and
computer setups on the web site.
I have suggested the point at which some textbook materials may be most relevant. You should,
however, use the materials as you need them. I recommend scanning all the material within the
first couple of weeks, then referring back as needed. You will undoubtedly use the National
Survey questionnaires and specifications most frequently. These will be downloaded from the
web during a lab session from
http://www.sscnet.ucla.edu/issr/da/earthquake/erthqkstudies2.index.htm.
5. Other materials on the web site.
1. Constructing a Code Frame. This includes some examples from past studies. The same
materials were available for M 218.
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Course Requirements
A. Assignments 1-3
Assignments 1-3 are each worth 10% of the final grade. These assignments are designed to
acquaint you with getting data ready for analysis, and with computer processing of data using a
subset of items from the National Survey of Disaster Experiences and Preparedness data set.
1. Create coding frames for questionnaire responses. Six actual questions or sets of
questions from the National Survey for Disaster Experiences and Preparedness are
used. The raw data represent answers given by 31 of 3,300 respondents.
Handed out: January 7. Due on January 14.
2. Use the data set for the National Survey for Disaster Experiences and
Preparedness. Input the data set, make selected transformations in data, and
obtain frequency distributions for specified variables.
Available on the web: January 14. Due on January 23.
3. Data manipulation, transformation, processing, and computation using SPSS.
Available on the web: January 23. Due on February 15.
B. Assignments 4-5
Assignments 4 and 5 are each worth 20% of the final grade. These assignments are designed to
facilitate work on your term paper (Assignment 6) by providing the preliminary analysis of your
topic or problem using the National Survey for Disaster Experiences and Preparedness data set.
Assignments 4 and 5 require that you identify and conduct analyses relevant to your own research
problem. Assignment 4 also assesses your growing expertise with the elaboration model. The
research question that you develop in assignments 4-6 is due on February 22.
4. Elaboration Model and Bivariate data analysis.
Available on the web: February 15 Due on March 8.
5. Scaling: The creation of composite measures.
Available on the web: March 8. Due on March 15 OR with Assignment 6
on March 20.
C. Assignment 6
A required 10- to 15-page (text) paper, worth 30% of the final grade. In this paper, you identify a
research problem of interest, develop a theoretical rationale, pursue a plan of data analysis, and
present and critique the results. The topic (statement of the research question to be addressed) is
due on February 22. The paper must include finished tables with proper titles, headings, and
footnotes to present the data. Attached printout is NOT acceptable. The paper should also
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include one or more figures (as relevant). Before starting this paper, you should familiarize
yourself with some of the publications on disaster research. Due on March 20 at 5:00 P.M.
Grading Requirements for Term Paper
1. The paper should be written as if you were writing for publication. If you need a
reference, use the American Psychological Association Manual.
2. It should include a brief introduction describing the purpose of your analysis (the
research question) and making reference to some appropriate literature, theoretical
structure, and concepts. References should be included as appropriate and should
include some previous disaster research. Do not include a lengthy literature
review, but do cite relevant previous work.
3. There must be a brief methods section in which you describe the characteristics of
the data set, the sample, the actual variables used in your analysis, and your
analytical strategy. Relevant materials will be made available to assist you here.
You must make clear that this paper is based on secondary analysis of an existent
data set.
4. In the results section, a systematic sequence of analyses should be demonstrated.
The analysis should be logical and technically correct. Some form of multivariate
analysis should be used. Statistics selected for inclusion should be justified and
explained. The analysis should involve some data transformations and
computations and one or more scales or indices. Although it would not normally
be required in a journal article, for purposes of this class you must include
information that describes exactly how you went about making any
transformations you used and printout that demonstrates that the transformations
are indeed correct. Tables and figures should be extracted from printout and
include titles, headings, labels, and the statistical tests used.
5. In the discussion section, an interpretation of the resultant data should be made. In
addition, the limits to the conclusions which can be drawn from the analysis should
be spelled out, including limits to the measures used, limits imposed by the study
design (including the sample), and alternative interpretations should be detailed.
6. Give references for studies cited in the paper.
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Data Set
This class uses data collected for the National Survey of Disaster Experiences and
Preparedness (NSDEP). Under funding from the Department of Homeland Security and the
National Science Foundation and as part of the National Consortium for the Study of Terrorism
and Responses to Terrorism (START) based at the University of Maryland, the University of
California, Los Angeles, conducted a survey of a representative sample of 3,300 households in the
continental United States. Three high visibility areas were over-sampled so that generalizations
could be made to them as well as to the nation as a whole. These areas were New York City, Los
Angeles County, and the greater Washington, D.C., area. Data were collected between April
2007 and February 2008.
The survey was designed to answer four questions.
What have Americans done to prepare for terrorist acts and disasters?
What steps have Americans taken to avoid or reduce exposure to terrorism?
What motivates Americans to prepare for terrorism in particular, disasters in general, and
to avoid terrorism risk?
How can policy and programs to increase public readiness for terrorism accomplish
more?
Based on research and theory about what motivates household readiness behavior, data were
collected on the many factors that might explain public readiness, including past events
experienced; the types, sources and channels over which information had been received; activities
that respondents had observed others’ do; the perceived effectiveness of different preparedness
and avoidance activities; self-reported knowledge about terrorism preparedness; perceived future
risk of disasters that could affect the home, community and nation; perceived resilience of self,
community and nation to future disaster events; perceptions of the completeness and honesty of
information provided by agencies at the local, state and national level; standard demographic
characteristics.
For CHS 212, you will be working with the unweighted data set. The data set is in SPSS.
You will be given a pass word to access the data. The questionnaires and specifications are
available on the Social Science Data Archive website at
http://www.sscnet.ucla.edu/issr/da/earthquake/erthqkstudies2.index.htm. Make sure that you
have a flash drive or CD on which you can download the data and other materials on January
11, 2013.
D. Grading Requirements Relevant for All Assignments
1. The textual section of all assignments must be typed.
2. In turning in any assignment, assume the reader (LBB) knows nothing about what is going
on. I cannot assume you know something if you do not tell me in writing and through the
presentation of your assignment that you do, in fact, know it.
3. Assignments are due on the assigned date. Late assignments will be penalized. You
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cannot afford to fall behind in this class! The quarter simply does not allow you the
luxury of time!
4. As in any class, you start with an assumed grade of B. Completion of all assignments on
time and adequately will maintain that B. Provision of brilliant creative insights and
impeccably presented assignments on all materials turned in may, if consistent for the
entire quarter, earn you an A. Poorly presented work, late assignments, and indication that
you are not doing the work or do not understand it, if consistent for the entire quarter, will
earn you a C or F.
E. Printing
During class time (8-10 AM, MWF) you will be able to print class related materials in the
classroom. The printer is not available at other times of the day or for other jobs.
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Week 1 Monday Introduction
January 7 Course Requirements
Survey Data as a Source of Information
Secondary Data Sets
Forms of Variables
Handouts
Syllabus
Assignments
HANDED OUT: #1, Creating Code Frames for Responses to
Open-Ended Questions
Readings
1. Bourque and Clark, Chapter 1, Introduction to Data Processing;
Chapter 2, Designing Forms for Data Collection; Chapter 3, Data
Collection and Quality Control.
2. Bourque & Fielder, Chapter 3, User-Friendly Questionnaires and
Response Categories.
3. Becker & Geer, Participant Observation: The Analysis of
Qualitative Field Data.
4. Bourque in The Sage Encyclopedia of Social Science Research.
5. Examples of code frames on the web site.
Week 1 Wednesday Stages in Data Processing
January 9 A. Constructing Code Frames
1. Relationship to Type of Questions
2. Timing of Constructions
3. Relationship to Type of Variables
4. Relationship to Analytical Objectives
B. Transferring Data From Hard Copy to Computer Accessible
Data
1. Data Input
C. Cleaning Data
D. Processing Machine-Readable Data
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Week 1 Wednesday
continued January 9 Readings
1. Afifi, May, Clark, Chapter 2, Characterizing data for
analysis, and Chapter 3, Preparing for data analysis
2. Treiman, Chapter 4, On the Manipulation of Data by
Computer
Friday Description of Study and Sample (LAB #1)
January 11 National Survey of Disaster Experiences and Preparedness
Introduction to the data sets and the Social Science Data Archive
Downloading from the Web (see above)
Data Set, Specifications and Questionnaires
POSTED ON THE WEB SITE
Information About Your Data Set
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Week 2 Monday National Survey on Disaster Experiences and Preparedness,
January 14 continued.
Assignments
DUE: Assignment #1, Construction of Code Frames
AVAILABLE ON THE WEB: Assignment #2, Input of Data and
Creation of Frequency Distributions
Week 2 Wednesday Univariate Analyses
January 16 As part of data processing
Frequency distributions
Graphs
Collapsing categories
Discuss Assignment #1
POSTED ON WEB SITE
Sets 1A, 1B
Week 2 Friday Introduction to SPSS (LAB #2)
January 18
Readings
1. Bourque and Clark, Chapter 4, Data Entry.
2. Afifi, Clark and May, Chapters 2 and 3, Characterizing data for
analysis and Preparing for data analysis.
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Week 3 Monday NO CLASS – MARTIN LUTHER KING, JR., HOLIDAY
January 21
Week 3 Wednesday Univariate Analysis, continued
January 23
Readings
1. Afifi, May, Clark, Chapters 4 and 5, Data screening and
transformations and Selecting appropriate analyses.
2. Treiman, Chapter 4, On the Manipulation of Data by Computer
Assignments
DUE: Assignment #2, Input of Raw Data and Creation of
Frequency Distributions
AVAILABLE ON THE WEB SITE: Assignment #3, Data
Manipulation, Transformation, Processing and Computation
Week 3 Friday Transformations in SPSS (LAB #3)
January 25 Drills on Transformations
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Week 4 Monday Data Manipulation and Modification as a Result of Univariate
January 28 Data Processing and to Set Up Later Analyses
Missing Data
Recoding Variables
Transformations
Computations
Readings
1. Bourque and Clark, Chapter 5, Data Preparation for Analysis.
2. Afifi, May, and Clark, Chapter 4, Data screening and data
transformations.
Week 4 Wednesday Data Manipulation, continued
January 30
ON WEB SITE
Count vs. Sum vs. Mean
How to get the data for interval variables
Week 4 Friday Transformations in SPSS (LAB #4)
February 1 Drills on Transformations
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Week 5 Monday Univariate Analysis to:
February 4 Create and Restructure Files
Select Subfiles and Subsets for Analysis
Description vs. Inference
Replicate
Set Up Conditional Relationships
ON WEB SITE
Set AB: Setting up and checking two independent variables
Measures of Association and Tests of Statistical Significance
Bivariate Analyses
Week 5 Wednesday Univariate Into Bivariate Analysis
February 6
Readings
Treiman, Chapter 1, Cross-Tabulations
ON WEB SITE
Crosstab Examples
Week 5 Friday Transformations in SPSS (LAB #5)
February 8
Readings
1. Treiman, Chapter 4, On the Manipulation of Data by Computer
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Week 6 Monday Bivariate Analysis
February 11 Crosstabulation
T-tests
Analysis of Variance
Correlation
Week 6 Wednesday Bivariate Analysis, continued
February 13 Analysis of Variance
T Tests
Readings
1. Afifi, May and Clark, Chapter 6, Simple regression and
correlation.
Week 6 Friday Bivariate Analysis in SPSS (LAB #6)
February 15
Assignments
DUE: Assignment #3, Data Manipulation, Transformation,
Processing, and Computation
AVAILABLE ON THE WEB: Assignment #4, Elaboration Model
and Bivariate Data Analysis
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Week 7 Monday NO CLASS-PRESIDENTS’ DAY HOLIDAY
February 18
Week 7 Wednesday Transformations
February 20
Go over Assignment 3
Week 7 Friday Bivariate Analysis into Elaboration Model (LAB #7)
February 22
Readings
1.Davis, J.A. Elementary Survey Analysis. Englewood Cliffs, NJ:
Prentice-Hall, Inc., 1971 (in reader).
2.Rosenberg, M. The Logic of Survey Analysis. NY: Basic Books,
Inc., 1968 (in reader).
3.Treiman, DJ, Chapters 1-3
DUE: Topic for Paper (Assignment 6)
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Week 8 Monday Elaboration Model, continued (LAB #8)
February 25 Extraneous and Intervening Variables
Week 8 Wednesday Elaboration Model, continued (LAB #9)
February 27 Extraneous and Intervening Variables, continued
Readings
1. Wallis and Roberts, How to Read a Table (in reader).
2. Davis, The Logic of Causal Order.
ON WEB SITE
Examples of a Three-Way Table
Examples of Elaboration Analysis
Examples of Write-up on Elaboration Analysis
Week 8 Friday Elaboration Model, continued (LAB #10)
March 1 Suppression, Distortion
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Week 9 Monday Elaboration Model, continued (LAB #11)
March 4 Log-Linear Models
Readings
Treiman, Chapters 12, Log-Linear Analysis
Afifi, May and Clark, Chapter 17, Log-linear analysis
Week 9 Wednesday Elaboration Model, continued
March 6 Logistic Regression
Readings
Treiman, Chapter 13, Binomial Logistic Regression
Afifi, May and Clark, Chapter 12, Logistic regression
Week 9 Friday Factor Analysis and Reliability with SPSS
March 8
Readings
McKennell, A.C. Attitude scale construction
Treiman, Chapter 11, Scale Construction
Afifi, May and Clark, Chapters 14 and 15, Principal components
analysis and Factor analysis
Assignments
DUE: Assignment #4, Elaboration Model and Bivariate Data
Analysis
AVAILABLE ON THE WEB: Assignment #5, Scaling: The
creation of composite measures
CHS 212
Winter 2012
WEEK & DATE TOPIC, RELEVANT READINGS, & ASSIGNMENTS
CHS 212,syllabus.Winter 2013 FINAL 21
Week 10 Monday Index Construction (LAB# 12)
March 11
ON WEB SITE
Index Items
Index Construction
Week 10 Wednesday Multivariate Analysis
March 13 Simple Regression
Dummy Variable Analysis
Logistic Regression
Readings
1.Afifi, May and Clark, Chapters 6-8, Simple regression and
correlation; Multiple regression and correlation; Variable selection
in regressions
.
2.Treiman, Chapters 5-7 on correlation and regression analysis
Assignments
March 11, DUE: Assignment #5, Index Construction
Week 10 Friday Multivariate Analysis, continued
March 15
Week 11 Wednesday Assignments
March 20 DUE: Assignment #6, the Research Paper, is due at or before 5:00
P.M.
CHS 212
Winter 2012
WEEK & DATE TOPIC, RELEVANT READINGS, & ASSIGNMENTS
CHS 212,syllabus.Winter 2013 FINAL 22
OBJECTIVES ASPH COMPETENCIES RELEVANT MATERIALS
Upon completing this course….
Know how to develop code
frames.
K.7. Differentiate between
qualitative and quantitative
evaluation methods in relation
to their strengths, limitations,
and appropriate uses, and
emphases on reliability and
validity.
Communication and
Informatics: The ability to
collect, manage and organize
data to produce information
and meaning that is exchanged
by use of signs and symbols;
to gather, process, and present
information to different
audiences in-person, through
information technologies, or
through media channels; and
to strategically design the
information and knowledge
exchange process to achieve
specific objectives.
Assignment 1
Lectures during first week
Readings by Bourque;
Bourque and Clark; Bourque
and Fielder; Becker and Geer.
Know how to set-up machine-
readable files.
F.1. Describe how the public
health information
infrastructure is used to
collect, process, maintain, and
disseminate data.
Assignment 2
Know how to access
secondary data sets.
C.1. Identify key sources of
data for epidemiologic
purposes.
F.1. Describe how the public
health information
infrastructure is used to
collect, process, maintain, and
disseminate data.
LAB #1
Lectures during second week
Know how to manipulate and
process machine-readable data
for analysis.
F.1. Describe how the public
health information
infrastructure is used to
collect, process, maintain, and
disseminate data.
Assignment 3
LABS 3-5
Readings by: Treiman; Afifi,
Clark, May; Bourque and
Clark.
Know the purpose and uses of A.4. Distinguish among the LABS 3-5
CHS 212
Winter 2012
WEEK & DATE TOPIC, RELEVANT READINGS, & ASSIGNMENTS
CHS 212,syllabus.Winter 2013 FINAL 23
univariate analyses, and be
able to conduct univariate
analyses.
different measurement scales
and the implications for
selection of statistical methods
to be used based on these
distinctions.
A.5. Apply descriptive
techniques commonly used to
summarize public health data.
A.6. Apply common statistical
methods for inference.
A.7. Apply descriptive and
inferential methodologies
according to the type of study
design for answering a
particular research question.
Lectures during third and
fourth weeks
Readings by Afifi, Clark and
May; Treiman.
Know, conduct and interpret
bivariate analyses including
crosstabular, t tests and
analysis of variance
A.4. Distinguish among the
different measurement scales
and the implications for
selection of statistical methods
to be used based on these
distinctions.
A.5. Apply descriptive
techniques commonly used to
summarize public health data.
A.6. Apply common statistical
methods for inference.
A.7. Apply descriptive and
inferential methodologies
according to the type of study
design for answering a
particular research question.
C.7. Calculate basic
epidemiology measures.
LAB 6
Lectures during fifth and sixth
weeks
Readings by Treiman
Know and apply the
Elaboration Model in
developing causal analyses.
E.5. Describe steps and
procedures for the planning,
implementation and evaluation
of public health programs,
policies and interventions.
E.8. Apply evidence-based
approaches in the development
and evaluation of social and
behavioral science
interventions.
Assignment 4
LABS 7-11
Lectures during seventh,
eighth, and ninth week
Readings by Rosenberg;
Davis; Aday and Cornelius;
Aneshensel.
Develop and test a simple Assignment 5
CHS 212
Winter 2012
WEEK & DATE TOPIC, RELEVANT READINGS, & ASSIGNMENTS
CHS 212,syllabus.Winter 2013 FINAL 24
index. Lectures during tenth week
Readings by McKennell;
Treiman
Write the first draft of a
research paper.
A.10. Develop written and oral
presentations based on
statistical analyses for both
public health professionals and
educated lay audiences.
C.10. Evaluate the strengths
and limitations of
epidemiologic reports.
Communication and
Informatics: The ability to
collect, manage and organize
data to produce information
and meaning that is exchanged
by use of signs and symbols;
to gather, process, and present
information to different
audiences in-person, through
information technologies, or
through media channels; and
to strategically design the
information and knowledge
exchange process to
Assignment 6
All lectures, labs, and readings