SRAM is no longer accepting new students to our Ph.D. program

The Ph.D. program offers specialization opportunities in areas such as data analysis, social and cognitive survey research, questionnaire design, and cross-cultural and cross-national survey research. The program is designed as a four-year program and requires a dissertation of original work that advances knowledge in the field of survey methodology. In addition to advanced opportunities in government, business, and non-profit sectors, Ph.D. graduates are likely to have opportunities within academic settings.

Course Descriptions

SRAM course descriptions at the University of Nebraska-Lincoln Course Catalog.

  • 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)
    Prereq: 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.

  • 894. Professional Development in Survey Research (1-2 credits, max. 2 credits)
    Pass/No Pass only.
    Basic principles of practice including ethical requirements and procedures, IRB and CIDI, personal conduct, plagiarism. Introduction to relevant databases, data archives, key surveys. Practice in critical discussion, report and abstract writing, creating and presenting conference papers.

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

  • 896. Practicum in Survey Research and Methodology (3 credits)
    Prereq: 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)
    Prereq: Admission to Master’s degree program and permission of major adviser.

  • 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.

  • 917. Principles of Survey Analysis II (3 credits)
    Prereq: SRAM 816
    Key components of analytic models used in analysis of survey data. Analysis of variance (anova), linear regression (ols) and generalized linear model (glm) to include estimation of coefficients for a specified set of “structural equations” designated by a hypothesized causal structure (i.e., SEMs). Main statistical models for estimating nonlinear regression coefficients. Introduction to principles of maximum likelihood estimation (mle) and alternative estimation approaches. Focus on development of the ability to conduct independent quantitative research.

  • 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)
    Prereq: 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)
    Prereq: 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/SOCI 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)
    Prereq: 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)
    Prereq: 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)
    Prereq: 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)
    Prereq: Permission

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

Minor Requirements

Minor in SRAM
Minor in SRAM

Ph.D. minors must take at least one course from at least four SRAM core areas (excluding Intermediate Statistics) and at least one Advanced Statistics class. Students are required to earn a grade of B or better to earn credit towards the SRAM minor. The minor includes the courses as listed below:

  1. SRAM/SOCI 819 – Applied Sampling
  2. SRAM/PSYC/SOCI 947 – Questionnaire Design
  3. SRAM 921 – Total Survey Error
  4. SRAM/SOCI 818 – Data Collection Methods
  5. An Intermediate or Advanced Statistics course from SRAM MS core curriculum
  6. One elective from SRAM MS core curriculum with the exception of an Intermediate Statistics course

Financial Assistance

With funding from various sources to SRAM and the Gallup Research Center, the SRAM program offers MS and PhD graduate research assistantships. These assistantships provide full tuition and a stipend.

A special Gallup Fellowship is available for promising SRAM applicants interested in full-time professional opportunities at Gallup. Candidates may apply for this fellowship at any time, but they must be accepted to the SRAM program to be considered. Please contact Barb Rolfes at SRAM or Lindsey Eastwood at Gallup for more information.

Nielsen Media Research also partners with SRAM in the Nielsen Fellowship program.  Nielsen Fellows are selected by an SRAM faculty supervisor.

All Nebraska programs have possibilities to fund exceptional out-of-state and underrepresented students. For more information on funding opportunities, please contact Barb Rolfes.

Exchange Program

KU Leaven, in Leuven, Belgium
KU Leuven, in Leuven, Belgium

The Survey Research and Methodology graduate program has an on-going one-semester exchange opportunity with the post-graduate program in Quantitative Analysis in the Social Sciences (QASS) at KU Leuven (KUL) in Leuven, Belgium. Both SRAM and the QASS are heavily invested in the modeling and analysis of quantitative survey data, and the communication of these analyses to key decision and policy makers. The QASS program attracts leading quantitative faculty from across Europe and the U.S. to provide up-to-the-moment instruction on the latest developments in quantitative methodology and analysis. Dr. Larry Williams at Nebraska and Dr. Marc Swyngedouw of KUL are the academic coordinators for the exchange program.

Application Checklist

The following checklist will help you to complete your application to the Univeristy of Nebraska Lincoln Survey Research and Methodology graduate studies programs.

U.S. Citizens
  • Statement of intentions for Academic/Professional Objectives (personal statement)
  • Three letters of recommendation
  • One copy of official college transcripts (most current; previous semester if currently enrolled)
  • Official test scores from the Graduate Record Examination(GRE) or Graduate Management Admission Test (GMAT) (neither required for Certificate program)
  • Submit application to the University of Nebraska-Lincoln Office of Graduate Studies
International Citizens
In addition to the above:
  • Evidence of financial support
  • TOEFL scores