JSM Activity #16

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Activity ID:  16
Title
Estimating Variance in the Presence of Missing Data
Date / Time / Room Sponsor Type
08/11/2002
2:00 PM - 3:50 PM
Room: H-Gramercy Suite A 		ENAR, Section on Government Statistics*, Section on Survey Research Methods* Contributed
Organizer: n/a
Chair: Michael P. Cohen, U.S. Department of Transportation
Discussant:  
Floor Discussion 3:35 PM
Description

How can one account for missing data when estimating variances? We see approaches in a variety of nonresponse situations, whether applying a weighting adjustment, or any of several types of imputation--ratio, hot-deck, or nearest-neighbor.
  301206  By:  Patrick J. Cantwell 2:05 PM 08/11/2002
Accounting for Imputation When Estimating Variances in the Economic Surveys at the Census Bureau

  301817  By:  Sonya  Vartivarian 2:20 PM 08/11/2002
Weighting Adjustments for Unit Nonresponse

  301968  By:  Jae-Kwang  Kim 2:35 PM 08/11/2002
Replication Variance Estimation for Nearest Neighbor Imputation With Application to the 2000 Census Long Form Data

  301329  By:  A.  Demnati 2:50 PM 08/11/2002
Linearization Variance Estimators for Survey Data with Missing Responses

  301201  By:  Michael D. Sinclair 3:05 PM 08/11/2002
A Simulation Study To Evaluate The Robustness Of Recent Methods For Preparing Variance Estimates In The Presence Of Hot Deck Imputation

  300936  By:  Sylvia  G. Leaver 3:20 PM 08/11/2002
Assessing the Impact of Imputation on the Sampling Variance of the U.S. Consumer Price Index

JSM 2002

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Revised March 2002