Missing Data

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Date/Time
Date(s) - 10/04/2019 - 10/05/2019
9:00 am - 5:00 pm

Location
Temple University Center City

Categories



Statistical Horizons is teaching a new 2 day seminar called “Missing Data.” The course taught by Dr. Paul Allison will cover the theory and practice of both maximum likelihood and multiple imputation. Maximum likelihood for linear models will be demonstrated with SAS, Stata, and Mplus.

If you’re using conventional methods for handling missing data, you may be missing out. Conventional methods for missing data, like listwise deletion or regression imputation, are prone to three serious problems:

  • Inefficient use of the available information, leading to low power and Type II errors.
  • Biased estimates of standard errors, leading to incorrect p-values.
  • Biased parameter estimates, due to failure to adjust for selectivity in missing data.

Virtually anyone who does statistical analysis can benefit from new methods for handling missing data. To take this course, you should have a good working knowledge of the principles and practice of multiple regression, as well as elementary statistical inference.

The event will begin on October 4th at 9am, in Philadelphia. To register for the event click HERE.


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