< back Send To Printer  
LSA Course Guide Search Results: UG, GR, Fall 2007, Dept = SURVMETH
 
Page 1 of 1, Results 1 — 17 of 17
Title
Section
Instructor
Term
Credits
Requirements
SURVMETH 600 — Fundamentals of Survey Methodology
Section 001, SEM

Instructor: Couper,Michael

FA 2007
Credits: 3

This course is intended as an introduction to the field, taught at the graduate level. It introduces a set of principles of survey design that are the basis of standard practices in the field. The course examines research literature that uses both observational and experimental methods to test key hypotheses about the nature of human behavior that affect the quality of survey data. It also presents statistical concepts and techniques in sample design, execution, and estimation, and models of behavior describing errors in responding to survey questions. The course uses total survey error as a framework to discuss coverage properties of sampling frames; alternative sample designs and their impact on standard errors of survey statistics; alternative modes of data collection; field administration operations; the role of the survey interviewer; impacts of nonresponse on survey statistics; the effect of question structure, wording and context on respondent behavior; models of measurement error; post survey processing; and estimation in surveys.

SURVMETH 613 — Analysis of Complex Sample Survey Data
Section 001, SEM

Instructor: Heeringa,Steven G

FA 2007
Credits: 3

This introductory course on the analysis of data from complex sample designs covers the development and handling of selection and other compensatory weights; methods for handling missing data; the effect of stratification and clustering on estimation and inference; alternative variance estimation procedures; methods for incorporating weights, stratification, clustering, and imputed values in estimation and inference procedures for complex sample survey data; and generalized design effects and variance functions. Prerequisites: SURVMETH 612.

Advisory Prerequisite: Survey Methodology 612/Sociology 612/Psychology 687

SURVMETH 617 — Methods and Theory of Sample Design
Section 001, LEC

Instructor: Heeringa,Steven G

FA 2007
Credits: 3
Reqs: BS

This course is concerned with the theory underlying methods of survey sampling widely used in practice. It covers basic techniques of simple random sampling, stratification, systematic sampling, cluster and multi-stage sampling, and probability proportional to size sampling. It also examines methods of variance estimation for complex sample designs, including Taylor series expansions, balanced repeated replications, and jackknife methods. It covers specialized topics, including stratification and subclasses, multi-phase or double sampling, ratio estimation, selection with unequal probabilities without replacement, non-response adjustments, imputation, and small area estimation. The course examines both practical applications of sampling techniques as well as the theory supporting the methods.

Advisory Prerequisite: Three or more courses in statistics and preferably a course in methods of survey sampling.

SURVMETH 623 — Data Collection Methods
Section 001, LEC

Instructor: Couper,Michael
Instructor: Conrad,Frederick G; homepage

FA 2007
Credits: 3

This course reviews alternative data collection methods used in surveys, focusing on interviewer-administered methods. It concentrates on the impact these techniques have on the quality of survey data, including measurement error properties, nonresponse, and coverage errors. The course reviews the literature on data collection methods, focusing on comparisons of major modes (face-to-face, telephone, and mail) and alternative methods of data collection (diaries, administrative records, direct observation, etc.). Prerequisites: None.

Advisory Prerequisite: Graduate standing or permission of instructor

SURVMETH 632 — Cognition, Communication, and Survey Measurement
Section 001, SEM

Instructor: Conrad,Frederick G; homepage

FA 2007
Credits: 3

Survey data are only as meaningful as the answers that respondents provide. Hence, the processes that underlie respondents' answers are of crucial importance. This course draws on current theorizing in cognitive and social psychology pertaining to issues like language comprehension, information storage and retrieval, autobiographical memory, social judgment, and the communication dynamics of survey interviewing to understand how respondents deal with the questions asked and arrive at an answer.

Advisory Prerequisite: Background in Psychology is helpful, but not required.

SURVMETH 670 — Design Seminar I
Section 001, SEM

Instructor: Lepkowski,James M; homepage

FA 2007
Credits: 3

This is a wide-ranging graduate seminar in which several Program faculty members join with the students in attempting to solve design issues presented to the seminar by clients from the private, government, or academic sectors of research. Readings are selected from literatures not treated in other classes and practical consulting problems are addressed. Prerequisites: SURVMETH 612, SURVMETH 623.

Advisory Prerequisite: SurvMeth 612, SurvMeth 623

SURVMETH 673 — Survey Practicum: Data Analysis
Section 001, SEM

Instructor: Lepkowski,James M; homepage
Instructor: Yan,Ting

FA 2007
Credits: 3

This course is the second in the series of courses comprising the survey research practicum. The course focuses on lectures and readings on most of the following issues; data cleaning and file preparation; classification systems and recodes; descriptive statistics and hypothesis testing; sums of squares and the analysis of variance; data reduction through factor and/or cluster analysis and the development of indices; cross-classification of categorical data and the measurement of association; multivariate linear regression tools; dummy-variable regression and multiple classification analysis; the logic of causal analysis and multiple dependent variables; multiple indicators, measurement errors and statistical analysis; report writing, graphics and the presentation of data.

Advisory Prerequisite: SURVMETH 672

SURVMETH 685 — Statistical Methods I
Section 001, LEC

Instructor: Valliant,Richard L

FA 2007
Credits: 3

This is the first course in a two term sequence in applied statistical methods covering topics including regression, analysis of variance, categorical data, and survival analysis. The purpose of this class is to learn basic statistical methods. The emphasis will be to understand and apply the methods.

Advisory Prerequisite: TWO COURSE SEQUENCE IN PROBABILITY & STATS OR EQ.

SURVMETH 697 — Special Courses
Section 001, SEM

FA 2007
Credits: 3

This course addresses specific research problems in survey methodology currently under study by faculty members. Topics vary by academic term and instructor.

Advisory Prerequisite: Some background in survey methodology is desirable

SURVMETH 699 — Directed Research
Section 001, IND

FA 2007
Credits: 1 — 3

Directed research on a topic of the student's choice. An individual instructor must agree to direct such research, and the requirements are specified when approval is granted.

Advisory Prerequisite: Graduate standing and permission of instructor

SURVMETH 720 — Total Survey Error I
Section 1, SEM

Instructor: Tourangeau,Roger

FA 2007
Credits: 2

This is the first course in two course sequence that reviews the total error structure of sample survey data, reviewing current research findings on the magnitudes of different error sources, design features that affect their magnitudes, and interrelationships among the errors. Coverage, non-response, sampling, measurement errors, interviewer effects, questionnaire effects, and mode of data collection effects are reviewed. Statistical and social science approaches to the error sources are compared.

Advisory Prerequisite: SurvMeth 612, SurvMeth 623

SURVMETH 790 — Multi-level Analysis of Survey Data
Section 001, LEC

Instructor: Lee,Valerie E; homepage

FA 2007
Credits: 3

Students are introduced to an increasingly common statistical technique, hierarchical linear modeling (HLM). Multi-level methods and the HLM software can be used to analyze nested data and multi-level research questions. Although the course demonstrates multiple uses of the HLM software, including growth-curve modeling, the major focus is on the investigation of organizational effects on individual-level outcomes.

Advisory Prerequisite: At least one graduate-level course in statistics or quantitative methods, and experience with multivariate regresion models, including both analysis of data and interpretation of results.

SURVMETH 890 — Doctoral Seminar I
Section 001, SEM

Instructor: Groves,Robert M
Instructor:

FA 2007
Credits: 3

This is the first course in a two term introduction to the integration of social science and statistical science approaches to the design, collection, and analysis of surveys. The seminar will focus on six to eight areas of statistical and methodological literature that have benefited from alternative approaches. Students demonstrate mastery of those literatures through critical review papers, ideas for extensions of the literature, and empirical projects related to research reviewed. Prerequisites: Candidacy and permission of instructor

Advisory Prerequisite: Candidacy and permission of instructor

SURVMETH 895 — Special Seminars
Section 001, SEM

Instructor: Valliant,Richard L

FA 2007
Credits: 3

Addresses specific research problems currently under study by faculty members. The topics vary by academic term and instructor.

Advisory Prerequisite: Graduate Standing and permission of instructor

SURVMETH 899 — Directed Research
Section 001, IND

FA 2007
Credits: 1 — 3

Directed research on a topic of the student's choice. An individual instructor must agree to direct such research, and the requirements are specified when approval is granted.

Advisory Prerequisite: Candidacy and permission of instructor

SURVMETH 990 — Dissertation Pre-Candidacy
Section 001, IND

FA 2007
Credits: 1 — 8

Election for dissertation work by doctoral student not yet admitted as a Candidate. Students doing dissertation work prior to achieving candidacy should register fro SURVMETH 990 for that portion of their schedule spent on dissertation work.

Advisory Prerequisite: Graduate standing and permission of instructor.

SURVMETH 995 — Dissertation Candidacy
Section 001, IND

FA 2007
Credits: 8

Graduate School authorization for admission as a doctoral Candidate. N.B. The defense of the dissertation (the final oral examination) must be held under a full term. Candidacy enrollment period. Students who have advanced to candidacy for the Ph.D. are required to register for SURVMETH 995 in any term when they are consulting with member of their dissertation committee or using the Library or other facilities of the University. If the student is to be engaged in a period of study away from the University, the student should file a Certification for Detached Study in advance. Students doing dissertation work prior to achieving candidacy should register for SURVMETH 990 for that portion of their schedule spent on dissertation work.

Enforced Prerequisites: Graduate school authorization for admission as a doctoral Candidate.

 
Page 1 of 1, Results 1 — 17 of 17