The Federal Motor Carrier Safety Administration has identified a number of resources that provide widely-accepted standard social science protocols for conducting sound research. The list below, while not exhaustive, summarizes these protocols. Any entity conducting research, analysis, or other relevant work for the Agency must adhere to widely-accepted research protocols.
Methods for Designing Research Studies
Washington, S., et al. (2002)
- Problem statement development
- Literature searching
- Development of the research work plan
- Execution of the experiment
- Data collection, management, quality control, reporting of results, and
- Evaluation of the effectiveness of the research.
Quasi Experimentation: Design and Analysis Issues for Field Settings
Cook, T.D., & Campbell, D.T. (1979)
This resource addresses causal inference and the language of experimentation, study designs, the conduct of randomized experiments, validity, and statistical analysis of data.
RAND Corporation (2015)
- Formulation of the problem and purpose of the study
- Selection of study approach
- Understanding of related studies
- Quality of data
- Management of assumptions
- Substance and quality of findings
- Structure and explanation of implications, recommendations, and caveats
- Tone, structure, and readability of documentation and final reports.
Basic Sampling Techniques
Cochran, W.G. (1977)
- Simple random sampling
- Sampling proportions and percentages
- Estimation of sample size
- Stratified random sampling
- Ratio and regression estimators
- Systematic sampling
- Cluster sampling
- Double sampling
- Sources of error in surveys.
Protection of Human Subjects
U.S. Department of Health and Human Services (2014)
- Protocols for obtaining approvals
- Guidance for institutional review boards (IRBs)
- Informed consent requirements
- Collection of biological materials and data
- Investigator responsibilities
- Working with vulnerable populations (e.g., children, prisoners, etc.).
Conducting Data Analysis
Lyles, R.W., et al. (2012)
- Descriptive statistics
- Fitting distributions/goodness of fit
- Simple one- and two-sample comparison of means
- Simple comparisons of multiple means using analysis of variance (ANOVA)
- Factorial designs (also ANOVA)
- Simple comparisons of means before and after some treatment
- Complex before-and-after comparisons involving control groups
- Trend analysis
- Logit analysis
- Survey design and analysis
- Non-parametric methods.
Analyzing Naturalistic Driving Data
Feasibility of Using In-vehicle Data to Explore How to Modify Driver Behavior that Causes Nonrecurring Congestion (S2-L10-RR-1)
Rakha, H., et al. (2011)
This report includes guidance on protocols and procedures for conducting video data reduction analysis, along with technical guidance on the features, technologies, and complementary data sets that researchers can consider when designing instrumented in-vehicle data collection studies.
Use of Independent Review Panels
Office of Management and Budget (2004)
This bulletin establishes independent peer review requirements for important scientific information intended for distribution by the Government. The purpose of the bulletin is to enhance the quality and credibility of the Government’s scientific information. Agencies are granted broad discretion to weigh the costs and benefits of using a particular peer review mechanism for a specific information product.
Guidance for Formatting Public-Use Data Sets
The Guide to Social Science Data Preparation and Archiving: Best Practice throughout the Data Life Cycle
Inter-university Consortium on Political and Social Research (2012)
This guide is aimed at those engaged in the cycle of research, from applying for a research grant, through the data collection phase, and ultimately to preparation of the data for deposit in a public archive. The guide is a compilation of best practices gleaned from the experience of many archivists and investigators.
Standards and Guidelines for Statistical Surveys
Office of Management and Budget (2006)
This document provides 20 standards that apply to Federal censuses and surveys whose statistical purposes include the description, estimation, or analysis of the characteristics of groups, segments, activities, or geographic areas in any biological, demographic, economic, environmental, natural resource, physical, social, or other sphere of interest. The development, implementation, or maintenance of methods, technical or administrative procedures, or information resources that support such purposes are also covered by these standards. In addition, these standards apply to censuses and surveys that are used in research studies or program evaluations if the purpose of the survey meets any of the statistical purposes noted above. To the extent they are applicable, these standards also cover the compilation of statistics based on information collected from individuals or firms (such as tax returns or the financial and operating reports required by regulatory commissions), applications/registrations, or other administrative records.
 Washington, S.; Leonard, J.; Manning, D.; Roberts, C.; Williams, B.; Bacchus, A.; Devanhalli, A.; Ogle, J.; and Melcher, D. (2002). Scientific Approaches to Transportation Research (NCHRP 20-45); National Academy of Sciences, Washington, DC. Available at: http://onlinepubs.trb.org/onlinepubs/nchrp/cd-22/chapters.html.
 Cook, T. D., and Campbell, D. T. (1979). Quasi-experimentation: Design and analysis issues for field settings; Houghton Mifflin, Boston, MA.
 RAND Corporation (2015). Standards for High-Quality Research and Analysis; Santa Monica, CA. Available at: http://www.rand.org/pubs/corporate_pubs/CP413-2015-05.
 Cochran, W.G. (1977). Sampling Techniques (3rd ed.); John Wiley & Sons, New York, NY.
 Lyles, R.W.; Siddiqui, M.A.; Buch, N.; Taylor, W.; Haider, S.W.; Gilliland, D.C.; and Pigozzi, B.W. (2012). Effective Experiment Design and Data Analysis in Transportation Research (NCHRP Report 727); National Academy of Sciences, Washington, DC. Available at: http://onlinepubs.trb.org/onlinepubs/nchrp/nchrp_rpt_727.pdf.
 Rakha, H.; Du, J.; Park, S.; Guo, F.; Doerzaph, Z.; Viita, D.; Golembiewski, G.; Katz, B.; Kehoe, N.; and Rigdon, H. (2011). Feasibility of Using In-vehicle Data to Explore How to Modify Driver Behavior that Causes Nonrecurring Congestion (Report S2-L10-RR-1); National Academies Press, Washington DC.
 Office of Management and Budget (December 16, 2004). Final Information Quality Bulletin for Peer Review; Washington, DC.
 Inter-university Consortium for Political and Social Research (ICPSR) (2012). Guide to Social Science Data Preparation and Archiving: Best Practice Throughout the Data Life Cycle (5th ed.); Ann Arbor, MI. Available at: http://www.icpsr.umich.edu/files/deposit/dataprep.pdf.
 Office of Management and Budget (September 2006). Standards and Guidelines for Statistical Surveys; Washington, DC. Available at: https://www.whitehouse.gov/sites/default/files/omb/inforeg/statpolicy/standards_stat_surveys.pdf.