Abstract:

Missing data is a very common phenomenon in social science research. Among most existing statistical analysis about missing data, Full-information maximum likelihood estimation and multiple imputation are recommended as most common approach at present for handling missing data. Planned missing data designs use special research design which create completely random missing data, and then employ modern missing data estimation techniques to get unbiased parameters and maximize statistical power in the process. Planned missing data designs can be used in cross-section survey to increase questionnaire items or reduce respondent burden. In longitudinal survey to shorten measure occasion, moreover, enrich validities. There are two types of planned missing data designs: 3-form design and two-method measurement design.

Key words: missing data, planned missing data designs, full-information maximum likelihood estimation, multiple imputation, 3-form design, two methods measurement design