Longitudinal Data Analysis Using R

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Date/Time
Date(s) - 04/08/2021 - 04/10/2021
10:00 am - 5:00 pm

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The most common type of longitudinal data is panel data, consisting of measurements of predictor and response variables at two or more points in time for many individuals (or other units of observation). Panel data (also known as repeated measures) enable two major advances over cross-sectional data: 1) the ability to control for unobserved differences across units, and 2) the ability to investigate questions of causal ordering.

Because panel data violate the standard assumption of independent observations, researchers must choose a strategy to deal with (and, ideally, make use of) this non-independence. In this course we will cover four approaches:

  1. Robust standard errors
  2. Random effects models
  3. Fixed effects models
  4. “Between/within” models that combine fixed and random effects

We will cover each of these methods in some detail, considering their advantages and disadvantages. We will also consider different methods for quantitative and categorical outcomes.

The fee of $895 includes all course materials.

Visit the event page for more information.

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