community health sciences 212 - ucla chs · 2013-09-05 · i have suggested the point at which some...

CHS 212 Winter 2012

CHS 212,syllabus.Winter 2012 FINAL 1

COMMUNITY HEALTH SCIENCES 212 ADVANCED SOCIAL RESEARCH METHODS IN HEALTH

Winter Quarter 2012 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. Aneshensel, Carol. Theory Based Data Analysis for the Social Sciences. Pine Forge

(Sage) Publications, 2002. 2. Afifi, A.A., May, S., Clark, V.A., Practical Multivariate Analysis, 5th Edition. NY:

Chapman & Hall, 2011. 3. Bourque, L.B., Clark, V.A. Processing Data: The Survey Example. Newbury Park, CA:

Sage Publications, 1995. 4. Bourque, L.B., Fielder, E.P. How to Conduct Self-Administered and Mail Surveys, 2nd

Edition. Thousand Oaks, CA: Sage Publications, 2003. 5. Bourque, L.B., Fielder, E.P. How to Conduct Telephone Surveys, 2nd Edition. Thousand

Oaks, CA: Sage Publications, 2003. 6. 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 published online 2 December 2010, DOI: 10.1177/0013916510390318.

7) 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.

8) Bourque, L.B., Shoaf, K.I., Nguyen, L.H. Survey research. International Journal

of Mass Emergencies and Disasters 15:71-101, 1997.

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9) Burby, R.J., Editor, Cooperating with Nature, Confronting Natural hazards with

Land-Use Planning for Sustainable Communities. Joseph Henry Press, Washington, D.C., 1998.

10) Drabek, T.E., Key, W.H. The impact of disaster on primary group linkages. Mass

Emergencies 1: 89-105, 1976.

11) Fritz, C.E. Disaster. In Merton, R.K., Nisbet, R.A. (eds.), Contemporary Social Problems. NY: Harcourt, Brace & World, Inc., 1961, pp. 651-694.

12) Glass, R.I., Urrutia, J.J., Sibony, S. et al. Earthquake injuries related to housing in

a Guatemalan village. Science 197-638-643, 1977.

13) 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.

14) Koenig, K.L, Schultz, C.H. Disaster Medicine: Comprehensive Principles and

Practices. Cambridge University Press, 2010.

15) 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.

16) Lechat, M.F. The international decade for natural disaster reduction: Background

and objectives. Disasters 14(1):1-6, 1990.

17) Lindell, M.K., Perry, R.W. Household adjustment to earthquake hazard: A review of research. Environment and Behavior 32: 590-630.

18) 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.

19) Logue, J.N. Disasters, the environment, and public health: Improving our response.

Am J Public Health 86(9):1207-1210, 1996.

20) Mileti, D.S. Human adjustment to the risk of environmental extremes. Sociology and Social Research 64(3):327-347, 1980.

21) Mileti, D.S. Disasters by Design, A Reassessment of Natural Hazards in the

United States. Washington, D.C., Joseph Henry Press, 1999.

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22) Mileti, D.S., Fitzpatrick, C. The causal sequence of risk communication in the Parkfield Earthquake Prediction Experiment. Risk Analysis 12(3):393-400, 1992.

23) Pantelic, J. The link between reconstruction and development. Land Use Policy

October:343-347, 1991. 24) Perry, R.W. Evacuation decision-making in natural disasters. Mass Emergencies

4:25-38, 1979.

25) Perry, R.W. The Social Psychology of Civil Defense. Lexington, MA: Lexington Books, 1982.

26) Quarantelli, E.L., Dynes, R.R. Response to social crisis and disaster. Annual

Review of Sociology 2:23-49, 1977.

27) Rodríguez, H., Quarantelli, E.L., Dynes, R.R. Handbook of Disaster Research. New York City, NY: Springer, 2006.

28) 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.

29) 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.

30) Trainer, P., Bolin, R. Persistent effects of disasters on daily activities: A cross-

cultural comparison. Mass Emergencies 1:279-290, 1976.

31) 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. 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. 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.

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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.

http://www.sscnet.ucla.edu/issr/da/earthquake/erthqkstudies2.index.htm�

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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 9. Due on January 18. 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 18. Due on January 23. 3. Data manipulation, transformation, processing, and computation using SPSS. Available on the web: January 23. Due on February 17. 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 17 Due on March 9. 5. Scaling: The creation of composite measures.

Available on the web: March 9. Due on March 16 OR with Assignment 6 on March 21.

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

CHS 212 Winter 2012


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 22 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 13, 2012. 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 & DATE TOPIC, RELEVANT READINGS, & ASSIGNMENTS


Week 1 Monday Introduction January 9 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 11 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 11 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 13 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 NO CLASS – MARTIN LUTHER KING, JR., HOLIDAY January 16 Week 2 Wednesday National Survey on Disaster Experiences and Preparedness, January 18 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 Friday Introduction to SPSS (LAB #2)

January 20 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 Univariate Analyses January 23 As part of data processing

Frequency distributions Graphs Collapsing categories

Discuss Assignment #1 POSTED ON WEB SITE Sets 1A, 1B 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 Wednesday Univariate Analysis, continued January 25 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

Week 3 Friday Transformations in SPSS (LAB #3) January 27 Drills on Transformations

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Week 4 Monday Data Manipulation and Modification as a Result of Univariate January 30 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 February 1 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 3 Drills on Transformations

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Week 5 Monday Univariate Analysis to: February 6 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 8 Readings

Treiman, Chapter 1, Cross-Tabulations ON WEB SITE Crosstab Examples Week 5 Friday Transformations in SPSS (LAB #5) February 10 Readings 1. Treiman, Chapter 4, On the Manipulation of Data by Computer

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Week 6 Monday Bivariate Analysis February 13 Crosstabulation T-tests Analysis of Variance Correlation Week 6 Wednesday Bivariate Analysis, continued February 15 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 17 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 20 Week 7 Wednesday Transformations February 22 Go over Assignment 3 DUE: Topic for Paper (Assignment 6)

Week 7 Friday Bivariate Analysis into Elaboration Model (LAB #7) February 24 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

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Week 8 Monday Elaboration Model, continued (LAB #8) February 27 Extraneous and Intervening Variables Week 8 Wednesday Elaboration Model, continued (LAB #9) February 29 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 2 Suppression, Distortion

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Week 8 Monday Elaboration Model, continued (LAB #11) March 5 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 7 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 9 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

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Week 10 Monday Index Construction (LAB# 12) March 12 ON WEB SITE

Index Items Index Construction Week 10 Wednesday Multivariate Analysis

March 14 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 16 Week 11 Wednesday Assignments March 21 DUE: Assignment #6, the Research Paper, is due at or before 5:00

P.M.

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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

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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

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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

community health sciences 212 - ucla chs · 2013-09-05 · i have suggested the point at which some...

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