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Combining and Analyzing Complex Data
  • Level Foundation
  • Duration 10 hours
  • Course by University of Maryland, College Park
  • Offered by

About

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.

Modules

Overview

    • 1 Videos
    • 1 Readings
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1 Videos

  • Overview

1 Readings

  • Slides

Basic R Examples

    • 2 Videos
    • 1 Readings
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2 Videos

  • Basic R examples
  • Basic R examples (continued)

1 Readings

  • Slides

Degrees of Freedom

    • 1 Videos
    • 1 Readings
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1 Videos

  • Degrees of Freedom

1 Readings

  • Slides

Basic Stata Examples

    • 2 Videos
    • 2 Readings
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2 Videos

  • Estimating Means
  • Multistage samples

2 Readings

  • Slides
  • Slides (continued)

Quantiles

    • 1 Videos
    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Course 6 Module 1

1 Videos

  • Quantile estimation in R

1 Readings

  • Slides

Models

    • 1 Videos
    • 1 Readings
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1 Videos

  • Introduction

1 Readings

  • Slides

Estimation Method

    • 1 Videos
    • 1 Readings
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1 Videos

  • Estimation Method

1 Readings

  • Slides

Linear Models in R

    • 1 Videos
    • 1 Readings
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1 Videos

  • Linear Models

1 Readings

  • Slides

Diagnostics

    • 1 Videos
    • 1 Readings
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1 Videos

  • Diagnostics in R

1 Readings

  • Slides

Linear Models in Stata

    • 1 Videos
    • 1 Readings
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1 Videos

  • Linear Models in Stata

1 Readings

  • Slides

Logistic Models in R

    • 2 Videos
    • 2 Readings
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2 Videos

  • Logistic Models in R
  • Odds Ratios

2 Readings

  • Slides
  • Slides

Logistic Regression in Stata

    • 1 Videos
    • 1 Readings
    • 1 Assignment
Show info about module content

1 Assignment

  • Course 6 Module 2

1 Videos

  • Logistic Regression in Stata

1 Readings

  • Slides

Motivation

    • 1 Videos
    • 4 Readings
    • 1 Discussion
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1 Discussions

  • Country specific examples

1 Videos

  • Why we link records

4 Readings

  • Improving Federal Statistics Using Multiple Data Sources
  • Longitudinal Employer-Household Dynamics (LEHD)
  • Impact of Research on Innovation, Competition and Science
  • Slides

Gentle Introduction: Application, Challenges

    • 2 Videos
    • 3 Readings
Show info about module content

2 Videos

  • Gentle Introduction
  • Challenges

3 Readings

  • Slides - Introduction
  • Technical Overview - Software
  • Slides: Challenges

Key Linkage Techniques

    • 1 Videos
    • 3 Readings
Show info about module content

1 Videos

  • Key Techniques

3 Readings

  • Slides
  • Record Linkage (Herzog/Scheuren/Winkler 2010)
  • Febrl - A Freely Available Record Linkage System (Christen)

Advanced Record Linkage Techniques

    • 2 Readings
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2 Readings

  • Machine Learning and Record Linkage (Winkler 2011)
  • Privacy Preserving Record Linkage (Schnell et al. 2009)

Assessment

    • 1 Assignment
Show info about module content

1 Assignment

  • Quiz 3 - Record Linkage

Privacy and Confidentiality

    • 1 Videos
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1 Videos

  • Privacy and Confidentiality

Linkage Consent

    • 4 Videos
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4 Videos

  • Linkage Consent and Consent Bias
  • Correlates of Consent
  • Bias in Administrative Estimates
  • Optimizing Linkage Consent

Readings

    • 3 Readings
Show info about module content

3 Readings

  • Slides
  • Assessing the Magnitude of Non-Consent Biases (Sakshaug & Kreuter 2012)
  • Placement, Wording and Interviewers (Sakshaug et al.)

Assessment

    • 1 Assignment
Show info about module content

1 Assignment

  • Quiz - Linkage Consent

Auto Summary

Unlock the power of data with the "Combining and Analyzing Complex Data" course, specifically designed for those venturing into the realm of Data Science and AI. Led by industry experts on Coursera, this foundational course spans 600 minutes of in-depth content. Dive into the essential techniques of using survey weights for estimating descriptive statistics and model parameters for both linear and logistic regressions, with a special focus on R® software capabilities. The curriculum also introduces you to the fundamentals of record linkage and statistical matching, crucial for integrating data from various sources. Ethical considerations are a core component of the course, encompassing the necessity of informed consent and the legal nuances across different countries when handling personal data. Available through Starter and Professional subscription plans, this course is perfect for beginners aiming to build a strong foundation in data analysis and ethical data management. Enroll now to enhance your data science skills and stay ahead in the field!

Richard Valliant, Ph.D.
Instructor

Richard Valliant, Ph.D.