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University of Maryland, College Park

Dealing With Missing Data

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®.

状态:STATA (Software)
状态:Statistical Modeling
课程小时

精选评论

HE

4.0评论日期:Dec 24, 2017

This is a higher level course. Good for beginners.

ZM

5.0评论日期:Aug 19, 2019

interesting material, well taught, lots of short quizzes to enforce understanding.

MM

5.0评论日期:Jun 4, 2017

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

所有审阅

显示:20/34

MARTYNS NWAOKOCHA
3.0
评论日期:May 17, 2019
marine henry
1.0
评论日期:Feb 12, 2019
Evan
2.0
评论日期:Dec 24, 2016
Ahmed Ibrahim
1.0
评论日期:Aug 31, 2016
Reni Amelia
5.0
评论日期:Apr 5, 2018
Lingbing Feng
3.0
评论日期:Feb 9, 2019
Iyshia Lowman
3.0
评论日期:Nov 8, 2018
Patrick Calderon
2.0
评论日期:Aug 19, 2020
Santiago Restrepo
1.0
评论日期:Aug 26, 2020
Zachary Mandell
5.0
评论日期:Aug 20, 2019
Mohammad Morshedloo
5.0
评论日期:Jun 4, 2017
Carlos F. Pavon
5.0
评论日期:Apr 27, 2017
Tin Ko Oo
5.0
评论日期:Jan 25, 2017
Roberto Daniel Cáceres Bauer
5.0
评论日期:Jun 4, 2020
Neeraj Kulkarni
5.0
评论日期:Oct 25, 2016
Anna Bellido Rivas
5.0
评论日期:Jan 24, 2018
Tracy Swett
4.0
评论日期:May 27, 2021
Kelly Dunn
3.0
评论日期:Jun 21, 2021
Yuni Arti
3.0
评论日期:Sep 13, 2022
Vanessa Heng
2.0
评论日期:Nov 20, 2022