SRAM Courses of Instruction

816. Principles of Survey Analysis (3 credits)
Introduction to the basic principles of causality and inductive logic in contemporary social and behavioral science. One, two, and multi-way layouts in analysis of variance, fixed effects models, and linear regression in several variables; the Gauss-Markov Theorem; multiple regression analysis; and basic principles of experimental and quasi-experimental designs.

817. Cross-cultural and Multi-population Survey Methodology (3 credits)
Multi-national research projects and the methdological challenges. Key aspects of cross-national, cross-cultural survey research, study design and organization; survey error and bias; question design; harmonization; adaptation and translation; survey process quality monitoring and control; and process and output documentation.

818. Data Collection Methods (3 credits)
Effects of various data collection methods on survey errors. The strengths, weaknesses, and challenges of data collection modes and mixed-mode methods. Processes underlying data collection and prctical challenges that arise with each mode; coverage error; nonresponse error; interviewer effects and training; timing; and mode effects.

819. Applied Sampling (3 credits)
Design of probability samples, sampling populations of humans and unique challenges posed by such populations, restricted by cost and available sampling frames. Simple random sampling, stratification, cluster sampling, systematic sampling, multistage sampling, and probability proportional to size sampling, area probability sampling, and telephone samples.

824. Advanced Quantitative Analysis in Marketing (MRKT 824) (3 credits)
Prerequisite: Permission.
Review, evaluation, and design of advanced marketing research investigations. State-of-the-art methodological issues relevant to marketing to provide an understanding of multivariate data analysis pertinent to the marketing literature. Analysis of linkage, structure, and causality/change for marketing phenomena.

863. Advanced Methods of Social Research II (SOCI 863) (3 credits)
Intensive analysis of the logic and techniques of sociological analysis: techniques of scaling and index construction; contingency table analysis; measures of association; parametric and nonparametric statistical inference; and generalizations from systematic findings.

895. Internship (3-6 credits)
Prerequisite: Permission.
Experience applying concepts and methods of survey research in preparation for a professional career.

896. Practicum in Survey Research and Methodology (3 credits)
Prerequisite: Permission.
Application of theory and research gained during internship.

898. Special Topics (3 credits, max. 24 credits)
Topic varies.

899. Master’s Thesis (6-10 credits)
Prerequisite: Admission to Master’s degree program and permission of major adviser.

902. Seminar in Research Methods (SOCI 902) (3 credits, max 9 credits)
Prerequisite: Permission.

915. Advanced Sampling (3 credits)
Advanced topics related to sampling error in surveys. Complex sample designs used to measure populations of humans, effect of nonresponse on sampling error and data analysis; methods available to "repair" the missing information; the implications of complex sample designs for analyses; and variance estimation.

920. Instrument Design and Development for Cross-cultural Surveys (3 credits)
Major approaches and strategies used in cross-national and cross-cultural reserach to design, test, adapt, and translate instrument for multilingual studies.

921. Total Survey Error (3 credits)
Common language of survey errors across social science disciplines. Causes of survey coverage, nonresponse, measurement, and processing errors; techniques used to reduce teh error in practice; and statistical models and designs that exist to measure the error. Implications of cost and trade-offs between error sources.

922. Randomized and Nonrandomized Research Design (3 credits)
Logic of causal inference in reserch esign. Obstacles to causal inference, faulty measurement, un-representativeness, spuriousness, specification errors, and confounds. Experimental and quasi-experimental designs, with infrerential pitfalls peculiar to each design. Statistical procedures to illustrate the logic behind various data analytic approaches and the different problems that can limit conclusions derived from these tools.

941. Intermediate Statistics: Experimental Methods (EDPS 941) (3 credits)
Prerequisite: EDPS 859.
Computation, interpretation, and application of analysis of variance techniques, including factorial and mixed model designs. Computer and microcomputer software accessed.

942. Intermediate Statistics: Correlational Methods (EDPS 942) (3 credits)
Prerequisite: EDPS 859 or equivalent.
Various correlational-based statistical procedures presented, including linear and nonlinear regression, multiple regression, statistical control, analysis of interactions, the general linear model, factor analysis, and discriminant analysis.

946. Psychology of Survey Response (PSYC 946) (3 credits)
Cognitive and communicative processes effect on dynamics of survey interviewing and relationships to principles of survey design. Effects of question wording on comprehension; question order and context on attitude; communicative and retrieval processes on validity of retrospective behavioral reports; and impact of response alternatives on answers.

947. Questionnaire Design (PSYC 947) (3 credits)
Design of questionnaries for survey research and the theoretical and practical issues arising from them. Selection of appropriate measurement techniques for assessing opinions, past behaviors and events, and factual material.

970. Theory and Methods of Educational Measurement (EDPS 970) (3 credits)
Prerequisite: EDPS 859 and 870; SRAM/EDPS 941; or equivalent.
Presentation of various measurement theories and concepts, including classical true-score theory, reliability and validity, text construction, item response theory, test equating, test bias, and criterion-referenced tests.

971. Structural Equation Modeling (EDPS 971) (3 credits)
Prerequisite: SRAM/EDPS 942 and 970; or equivalent.
Introduction to the techniques of path analysis, confirmatory factor analysis, and structural equation modeling with emphasis on the set-up and interpretation of different models using the LISREL program. Model testing and evaluation, goodness-of-fit indices, violations of assumptions, specification searches, and power analyses.

972. Multivariate Analysis (EDPS 972) (3 credits)
Prerequisite: SRAM/EDPS 941 and 942.
Techniques of multivariate analyses, including multivariate analysis of variance and covariance, multivariate multiple regression, multigroup discriminant analysis, canonical analysis, repeated measures (Multivariate model), and time series Mathematical models presented and analyzed. Instruction complemented by appropriate statistical software packages.

998D. Seminar in Special Topics (MRKT 998D) (3 credits)
Prerequisite: Permission

999. Doctoral Dissertation (1-24 credits)
Prerequisite: Admission to doctoral degree program and permission of supervisory committee chair.