Selected Problems of Social Research: Longitudinal Data Analysis

Transcription

1 Selected Problems of Social Research: Longitudinal Data Analysis Purdue University, Sociology 681 (28890-SOC ) Syllabus, Fall 2008 T-Th 9:00-10:15; Stone 215 Course Description Examines common modes of longitudinal data analysis in sociology including linear panel analysis, event history analysis, and the analysis of repeated cross-sectional data. Attrition and selection bias in panel studies are also considered. Working with available data, students perform exercises and conduct one research project including conceptualization, operational procedures, data analysis, and report writing. Credits 3. Prerequisite: SOC 680 or PSY 600 or consent of instructor. Instructors Dr. Kenneth F. Ferraro Professor of Sociology Stone Hall 335, Director, Center on Aging and the Life Course Young Hall 824, Office Hours: Monday 10:45-11:15 in Young Hall; Thursday 10:30-11:20 in Stone Hall For appointments, please contact: Ann Howell, 828 Young Hall, ; Mr. Markus Schafer, Doctoral Student in Sociology and Gerontology Young Hall 824, Laboratory hours (held in Stone 342): Monday: 8:30-10:00; Wednesday: 2:30-4:00; other times by appointment. Required Reading Allison, Paul D Event History Analysis: Regression for Longitudinal Event Data. Beverly Hills, CA: Sage. Elder, Glen, H., Jr., Eliza K. Pavalko and Elizabeth C. Clipp Working With Archival Data: Studying Lives. Newbury Park, CA: Sage. Glenn, Norval D Cohort Analysis, 2 nd edition. Beverly Hills, CA: Sage. Menard, Scott Longitudinal Research, 2nd edition. Newbury Park, CA: Sage. There are additional required readings, but most are available electronically through JSTOR or Purdue library subscriptions. Others will be available from library reserves. Optional Reading The syllabus lists a number of optional readings that are designed to enhance understanding of the material. You may also be interested in purchasing one or more of the Stata manuals. View the table of contents at: (Stata College Station, Texas: Stata Corporation). Course Content and Educational Philosophy The course is divided into 6 sections. Representative readings are included for each section. Students should achieve a working knowledge of the major topics and expertise in at least one of the major procedures covered (see parts 3-6). My educational philosophy emphasizes learning by doing rather than just learning by absorbing lectures. Class time and assignments are structured in the classical problem solving pedagogical approach advanced by John Dewey. Thus, laboratory assignments are a critical part of the learning process and constitute the bulk of the course evaluation. 1

2 Software Students may be familiar with a statistical processing package that will perform the most commonly used procedures, but SPSS and SAS do not offer all of the procedures used in the course. STATA will handle all the exercises and is available in the SRI laboratory (Stone 342). All laboratory exercises will be conducted in Stata. No prior knowledge of Stata is necessary. You may purchase Intercooled Stata 10.0 for $155 through Purdue University s grad plan agreement with Stata. Call 800-STATAPC, identify yourself as a Purdue students, and order with credit card. It will be delivered via Krannert School of Management (Lisa Ratliff, ). Data All laboratory exercises will be completed with data provided to students. The research paper may be completed on any longitudinal data set suitable for a scientific contribution. Perhaps you have a data set you are currently working with, from which assignments and your research paper may be developed. Thousands of data sets are also available to you from the Interuniversity Consortium for Political and Social Research (ICPSR). If you are not familiar with ICPSR, go to: For the research paper, the optimal strategy for the course is for you to find your own data and work with it so that you can develop a publishable work. Course Requirements General Please double space text for all course documents with a font size of 11 or more. Papers are due by 4:00pm on the assigned date. Five-percent point deductions transpire each weekday that a paper is late. For each laboratory assignment, number each step of the assignment. Attach and annotate the relevant Stata output for each step to highlight your method. 1. Reading assignments, attendance, and class participation: A reading list specifies the readings to be completed for the week or each day's class (30 points possible). 2. Laboratory assignments: There are seven laboratory assignments (LA). The possible points range from 5 to 35. Although working on the STATA component of the assignments in pairs or small groups is wholly acceptable, the actual written assignment should reflect independent thought and interpretation. 3. Research paper: Students will write one research paper. The paper will be developed in consultation with classmates and the instructor. Papers previously or simultaneously submitted to other classes are not acceptable; this is to be an original work. Papers co-authored with class participants are not permitted. Co-authorship with faculty members is also not acceptable, but you are free to add a faculty member as an author after drafting the paper for the course. You are responsible to know what plagiarism is; acts of plagiarism will result in a course grade of F. Research Paper Assignments (RPA) There are three research paper assignments that are scheduled throughout the semester. Although the complete paper is due during finals week, the following RPAs should assist students in developing their papers. 1. Description of data (30 points) 2. Weighting and missing data (30 points) 3. Preliminary analyses and presentation (30 points) The paper is to be an empirical report, just like a refereed journal article. (Empirical reports are the building blocks of science.) The highest goal for any student is to write a paper from the 2

3 course that will result in publication in a prestigious refereed journal in one s field of expertise. Craft the paper to resemble an article for the journal to which it would be an appropriate submission. Append copies of the pertinent Stata output for the reported analyses. You are required to append the frequency distribution of key variables and final models. If you have ANY intention of ever publishing from the data with which you work, you must complete a form for Use of Human Subjects as soon as possible. Failure to complete the appropriate form and garner approval may result in your being unable to publish from the data. For students outside of sociology, please check to see if your department has its own Human Subjects Committee from which you must seek prior approval. 190 points are possible for the research paper (including the RPAs). Papers will be presented to the class near the end of the semester. Two formats are acceptable: paper or didactic poster presentation. Complete papers are due 12/15/08. Evaluation Method Requirement Points Possible Due Date 1. Reading assignments & class participation 30 class meetings 2. Laboratory assignments (LAs) 155 variable 3. Research paper RPAs 90 variable Final paper /15/08 Total 375 I use the + / - grading system. The percent of total points needed for letter grades are as follows: A, ; A-, 90-92; B+, 88-89; B, 83-87; B-, 80-82; C+, 78-79, etc. Part 1. Why Longitudinal Data? Tuesday, August 26, Introduction Chapters 1-3, Menard, Scott Longitudinal Research. Newbury Park, CA: Sage. Ferraro, Kenneth F. and Jessica A. Kelley-Moore A Half-Century of Longitudinal Methods in Social Gerontology: Evidence of Change in the Journal. Journal of Gerontology: Social Sciences 58B:S264-S270. Thursday, August 28, Modes of Analysis for Archival Data Chapters 1-2, Elder, Glen, H., Jr., Eliza K. Pavalko and Elizabeth C. Clipp Working With Archival Data: Studying Lives. Newbury Park, CA: Sage. Tuesday, September 2, Recasting Archival Data Chapters 3-5, Elder, Glen, H., Jr., Eliza K. Pavalko and Elizabeth C. Clipp Working With Archival Data: Studying Lives. Newbury Park, CA: Sage. Thursday, September 4, Time Lags and Power Ferraro, Kenneth F. and Janet Wilmoth Measuring Morbidity: Disease Counts, Binary Variables, and Statistical Power. Journal of Gerontology: Social Sciences 55B:S173- S189. Optional: Review a book on statistical power. Any version of Jacob Cohen s Statistical Power Analysis for the Behavioral Sciences. Hillsdale, NJ: L. Erlbaum Associates. Laboratory Assignment 1 due, Protecting human subjects (5 points) Review and submit one paragraph summarizing whether you will need to submit a request for the protection of human subjects. Include copy of CITI certification if you have completed it (see 3

4 Part 2. Data Preparation Tuesday, September 9, To Weight or Not to Weight? Optional: Lee, Eun Sul and Ronald N. Forthofer Analyzing complex survey data, 2 nd edition. Thousand Oaks, CA: Sage Publications. Winship, Christopher and Larry Radbill Sampling Weights and Regression Analysis. Sociological Methods and Research 23: Thursday, September 11, Laboratory, Introduction to Stata 10.0: Descriptive statistics and power; accessing data meet in Stone 342 Kelley-Moore, Jessica ICPSR/NACDA Help Sheet. Purdue University. Tuesday, September 16, Missing Data Boyston, Patrick Multiple imputation of missing values. Stata Journal 4(3): Optional readings: Boyston, Patrick Multiple imputation of missing values: update. Stata Journal 5(2):1-14. Little, Roderick J., and Nathaniel Schenker "Missing Data." Pp in Handbook of Statistical Modeling for the Social and Behavioral Sciences, edited by Gerhard Arminger, Clifford C. Clogg, and Michael E. Sobel. New York: Plenum Press. Von Hippel, Paul T Regression with Missing Y s: An Improved Strategy for Analyzing Multiply Imputed Data. Sociological Methodology 37(1): Laboratory Assignment 2 due, Descriptive statistics and power (10 points) Thursday, September 18, Laboratory, Weights and missing data meet in Stone 342 Optional readings: On the importance of care with missing data: American Sociological Review (a) 1978, vol. 43, ; comment: 1980, vol. 45, and (b) 1985, vol. 50: ; comment: 1986, vol. 51: (1986). Monday, September 22, Laboratory Assignment 3 due, Weights and missing data (30 points) Part 3. Linear Panel Analysis Tuesday, September 23, Linear Panel Analysis quantitative variables Chapters 4-5, Menard, Scott Longitudinal Research. Newbury Park, CA: Sage. Optional: Allison, Paul D "Change Scores as Dependent Variables in Regression Analysis." Pp in Sociological Methodology, 1990, edited by Clifford C. Clogg. Washington, DC: American Sociological Association. Thursday, September 25, Accounting for Selection Bias Stolzenberg, Ross M. and Daniel A. Relles "Tools for Intuition about Sample Selection Bias and Its Correction." American Sociological Review 62: Optional: Berk, Richard "An Introduction to Sample Selection Bias in Sociological Data." American Sociological Review 48: Tuesday, September 30, Correcting for Selection Bias Bushway, Shawn, Brian D. Johnson and Lee Ann Slocum Is the Magic Still There? The Use of the Heckman Two-Step Correction for Selection Bias in Criminology. Journal of Quantitative Criminology 23:

5 Optional: Ferraro, Kenneth F. and Jessica A. Kelley-Moore Cumulative Disadvantage and Health: Long-Term Consequences of Obesity? American Sociological Review 68: Thursday, October 2, Laboratory, Change and selection bias; Students should also identify proposed data for research paper Stone 342 Monday, October 6, Laboratory Assignment 4 due, Change and selection bias (35 points) Part 4. Three or More Waves Tuesday, October 7, Analyzing Three or More Waves of Data Willett, John B., Judith D. Singer, and Nina C. Martin The Design and Analysis of Longitudinal Studies of Development and Psychopathology in Context: Statistical Models and Methodological Recommendations. Development and Psychopathology 10: Optional: Rogosa, David "Myths About Longitudinal Research." Pp in Methodological Issues in Aging Research, edited by K. W. Schaie, R. T. Campbell, W. Meredith, and S. C. Rawlings. New York: Springer. Thursday, October 9, Multi-level Modeling for the Analysis of Change Albright, Jeremy J Estimating Multilevel Models using SPSS, Stata, and SAS. Unpublished manuscript ( Optional: Rabe-Hesketh, Sophia and Anders Skrondal Multilevel and Longitudinal Modeling Using Stata, 2nd Edition. College Station, TX: Stata Press. October 13-14, October break 2008 Thursday, October 16, Laboratory, Multi-level model for change Stone 342 Monday, October 20, Laboratory Assignment 5 due, Multi-level model for change (25 points) Tuesday, October 21, Research Project Assignment 1 due, Description of data and research project (30 points) Data selected and ready to begin analysis. Class time for discussing projects. 5. Event History Analysis Thursday, October 23, Why Event History Analysis? Chapters 1-3 of Allison, Paul D Event History Analysis: Regression for Longitudinal Event Data. Beverly Hills, CA: Sage. Tuesday, October 28, How to Analyze Event History Data? Chapters 4-8 of Allison, Paul D Event History Analysis: Regression for Longitudinal Event Data. Beverly Hills, CA: Sage. Optional: Cleves, Mario A., William W. Gould, and Roberto G. Gutierrez An Introduction to Survival Analysis Using Stata, Revised Edition. College Station, TX: Stata Corporation. Optional: Ferraro, Kenneth F. and Jessica A. Kelley-Moore Self-Rated Health and Mortality Among Black and White Adults: Examining the Dynamic Evaluation Thesis." Journal of Gerontology: Social Sciences 56B:S195-S205. 5

6 Thursday, October 30, Laboratory, Event history analysis meet in Stone 342 Monday, November 3, Laboratory Assignment 6 due, Event history analysis (20 points) Part 6. Repeated Cross-Sectional Analysis Tuesday, November 4, Pooling Multiple Cross-Sections for Trend Analysis Optional: Firebaugh, Glenn Analyzing Repeated Surveys. Thousand Oaks, CA: Sage. Thursday, November 6, Introduction to Cohort Analysis Pages 1-45 of Glenn, Norval D Cohort Analysis. Beverly Hills, CA: Sage. Optional: Ferraro, Kenneth F "Cohort Analysis of Retirement Preparation, " Journal of Gerontology: Social Sciences 45:S Tuesday, November 11, Data Preparation for Cohort Analysis and Palmore Method Pages of Glenn, Norval D Cohort Analysis. Beverly Hills, CA: Sage. Palmore, Erdman When Can Age, Period, and Cohort Be Separated? Social Forces 57(1): Wednesday, November 12, Research Project Assignment 2 due, Weights and missing data (30 points) Thursday, November 13, Laboratory, Cohort or repeated cross-sectional analysis Stone 342 Tuesday, November 18, Beyond Cohort Analysis Rodgers, Willard L "Estimable Functions of Age, Period, and Cohort Effects." American Sociological Review 47: (Commentary included with article, ) Optional: Ferraro, Kenneth F "Group Benefit Orientation Toward Older Adults at Work? A Comparison of Cohort Analytic Methods." Journal of Gerontology: Social Sciences 45:S Thursday, November 20, Open Laboratory meet in Stone 342 Tuesday, November 25, Laboratory Assignment 7 due, Cohort or repeated crosssectional analysis (30 points) November 26-28, Thanksgiving Break Tuesday, December 2, Research Project Assignment 3 due, Preliminary analysis (30 points), Student Presentations

7 Thursday, December 4, Student Presentations Tuesday, December 9, Student Presentations and Teaching Evaluations Thursday, December 11, Student Presentations Monday, December 15, Final research Paper due by 4:00pm Summary of Important Dates Date Meet in Stone 342 (lab) Laboratory Assignment 9/4 LA1, Protecting human subjects (5) 9/11 Introduction to Stata /16 LA2, Introduction to Stata 10.0: Descriptive statistics and power (10) 9/18 Weights & missing data 9/22 LA3, Weights & missing data (30) 10/2 Change & selection bias Research Project Assignment Identify data set (0) 10/6 LA4, Change & selection bias (35) 10/16 Multi-level model for change 10/20 LA5, Multi-level model for change (25) 10/21 RPA1 (30) 10/30 Event history analysis 11/3 LA6, Event history analysis(20) 11/12 RPA2 (30) 11/13 Cohort or repeated crosssectional analysis 11/20 Open lab 11/25 LA7, Cohort or repeated crosssectional analysis (30) 12/2 RPA3 (30) 12/15 Complete paper (100) 7