Basic and Applied Statistical Inference and Measurement

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Statistical information plays an important role in establishing the facts upon which public policies are based. For example, the levels of employment and unemployment and other important economic and health statistics are obtained from sample surveys. Statistical evidence is also used in legal cases, especially those concerning equal pay or employment discrimination and trademark infringement. Since there are some imperfections in most real world data sets (e.g., a question in a survey may not be clear to all respondents or it is difficult to obtain information about some potentially relevant variables), it is important to develop methods for assessing the accuracy of the data used in statistical analyses as well as techniques which are less sensitive to modest errors in the data. One goal of the project is to further develop a new approach to determining the misclassification rates in the labor force survey. The effect of these errors on the reported rates of unemployment and employment will be studied. This should enable policy makers to adjust for these misclassification errors when they interpret the monthly economic statistics. Often reasonably sound studies are questioned because some variables that might influence the outcome under investigation (e.g., the efficacy of a drug or educational program) were not included. Methods for assessing the potential impact of an omitted variable are being developed and applied to data arising in legal cases, economics, and public policy. Quite often it can be shown that the main conclusion of the study would not be changed so that action, such as providing a public warning about a potentially harmful drug or introducing a better educational method, can be implemented with further delay and study.