University of Maryland - Combining and Analyzing Complex Data
- Offered byCoursera
- Public/Government Institute
Combining and Analyzing Complex Data at Coursera Overview
Duration | 10 hours |
Total fee | Free |
Mode of learning | Online |
Official Website | Explore Free Course  |
Credential | Certificate |
Combining and Analyzing Complex Data at Coursera Highlights
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Course 6 of 7 in the Survey Data Collection and Analytics Specialization
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Approx. 10 hours to complete
- English Subtitles: English
Combining and Analyzing Complex Data at Coursera Course details
- In this course you will learn how to use survey weights to estimate descriptive statistics, like means and totals, and more complicated quantities like model parameters for linear and logistic regressions. Software capabilities will be covered with R® receiving particular emphasis. The course will also cover the basics of record linkage and statistical matching?both of which are becoming more important as ways of combining data from different sources. Combining of datasets raises ethical issues which the course reviews. Informed consent may have to be obtained from persons to allow their data to be linked. You will learn about differences in the legal requirements in different countries.
Combining and Analyzing Complex Data at Coursera Curriculum
Basic Estimation
Overview
Basic R examples
Basic R examples (continued)
Degrees of Freedom
Estimating Means
Multistage samples
Quantile estimation in R
Slides
Slides
Slides
Slides
Slides (continued)
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Course 6 Module 1
Models
Introduction
Estimation Method
Linear Models
Diagnostics in R
Linear Models in Stata
Logistic Models in R
Odds Ratios
Logistic Regression in Stata
Slides
Slides
Slides
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Slides
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Course 6 Module 2
Record Linkage
Why we link records
Gentle Introduction
Challenges
Key Techniques
Improving Federal Statistics Using Multiple Data Sources
Longitudinal Employer-Household Dynamics (LEHD)
Impact of Research on Innovation, Competition and Science
Slides
Slides - Introduction
Technical Overview - Software
Slides: Challenges
Slides
Record Linkage (Herzog/Scheuren/Winkler 2010)
Febrl - A Freely Available Record Linkage System (Christen)
Machine Learning and Record Linkage (Winkler 2011)
Privacy Preserving Record Linkage (Schnell et al. 2009)
Quiz 3 - Record Linkage
Ethics
Privacy and Confidentiality
Linkage Consent and Consent Bias
Correlates of Consent
Bias in Administrative Estimates
Optimizing Linkage Consent
Slides
Assessing the Magnitude of Non-Consent Biases (Sakshaug & Kreuter 2012)
Placement, Wording and Interviewers (Sakshaug et al.)
Quiz - Linkage Consent
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