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Dealing With Missing Data, Мэрилендский университет в Колледж-Парке

3.7
Оценки: 77
Рецензии: 20

Об этом курсе

This course will cover the steps used in weighting sample surveys, including methods for adjusting for nonresponse and using data external to the survey for calibration. Among the techniques discussed are adjustments using estimated response propensities, poststratification, raking, and general regression estimation. Alternative techniques for imputing values for missing items will be discussed. For both weighting and imputation, the capabilities of different statistical software packages will be covered, including R®, Stata®, and SAS®....

Лучшие рецензии

автор: MM

Jun 05, 2017

This course quite help to get as much reliable data as possible for any survey.

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Рецензии: 17

автор: marine henry

Feb 13, 2019

very idfficult to understand. The sound of the videio is so low that most of it is impossible to understand, I had to try 10 times some of the tests because couldn't find the answer and had to guess it!

автор: Lingbing Feng

Feb 10, 2019

The topic of this course is attractive as it is hard to get from elsewhere. However, the content of this course is actually quite barren, practices are easy and not closely refective of the corresponding videos.

The fourth week is most interesting and I was happy to know that multiple imputation is actually not key on the "imputation" part. It emphasizes the fact that missingness should be considered as uncertainty in modelling.

After all, this is a interesting course and can be better designed and delievered. Thanks to the team.

автор: Iyshia Lowman

Nov 08, 2018

As others have stated before the audio is REALLY LOW. It makes it very difficult to hear him without headphones for my phone. The course was fine, overall.

автор: Anandita Ghosh

Nov 03, 2018

There is scope for a lot of improvement in terms of quality of content as well as videos. There also appeared to be technical issues in the quizzes wherein the correct responses were often returned as incorrect & vice-versa, for a few quizzes. Without a moderator, queries are not addressed and nobody appears to be keeping track of the feedback. I was disappointed in the course since the previous courses in the specialization were far better designed and executed.

автор: Reni Amelia

Apr 05, 2018

Prof. Richard Valliant, Ph.D. clearly enough explain all of these course materials. I will use these materials to dealing missing data on our census or survey. I believe that these materials were very helpful for me and my agency.

Thank you very much for all of this course.

автор: Anna Bellido Rivas

Jan 24, 2018

Great course!

автор: Hussein Ezzeldin

Dec 25, 2017

This is a higher level course. Good for beginners.

автор: Hiroki NISHINO

Nov 17, 2017

the course materials are of very low quality.

автор: Mohammad Morshedloo

Jun 05, 2017

This course quite help to get as much reliable data as possible for any survey.

автор: Carlos F. Pavon

Apr 27, 2017

Excellent review of relevant material.