- From www.coursera.org
Dealing With Missing Data
- Self-paced
- Free Access
- Fee-based Certificate
- 4 Sequences
- Introductive Level
Course details
Syllabus
- Week 1 - General Steps in Weighting
Weights are used to expand a sample to a population. To accomplish this, the weights may correct for coverage errors in the sampling frame, adjust for nonresponse, and reduce variances of estimators by incorporating covariates. The series of steps needed to d... - Week 2 - Specific Steps
Specific steps in weighting include computing base weights, adjusting if there are cases whose eligibility we are unsure of, adjusting for nonresponse, and using covariates to calibrate the sample to external population controls. We flesh out the general step... - Week 3 - Implementing the Steps
Software is critical to implementing the steps, but the R system is an excellent source of free routines. This module covers several R packages, including sampling, survey, and PracTools that will select samples and compute weights. - Week 4 - Imputing for Missing Items
In most surveys there will be items for which respondents do not provide information, even though the respondent completed enough of the data collection instrument to be considered "complete". If only the cases with all items present are retained when fitting... - Week 4 - Summary of Course 5
We briefly summarize the methods of weighting and imputation that were covered in Course 5.
Prerequisite
Instructors
Richard Valliant, Ph.D.
Research Professor
Joint Program in Survey Methodology
Editor
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