<abstract xmlns="http://www.w3.org/1999/xhtml"><p> In survey data, an observation is considered influential if it is reported correctly and its weighted contribution has an excessive effect on a key estimate, such as an estimate of total or change. In previous research with data from the U.S. Monthly Retail Trade Survey (MRTS), two methods, Clark Winsorization and weighted M-estimation, have shown potential to detect and adjust influential observations. This article discusses results of the application of a simulation methodology that generates realistic population time-series data. The new strategy enables evaluating Clark Winsorization and weighted M-estimation over repeated samples and producing conditional and unconditional performance measures. The analyses consider several scenarios for the occurrence of influential observations in the MRTS and assess the performance of the two methods for estimates of total retail sales and month-to-month change.</p></abstract>

In survey data, an observation is considered influential if it is reported correctly and its weighted contribution has an excessive effect on a key estimate, such as an estimate of total or change. In previous research with data from the U.S. Monthly Retail Trade Survey (MRTS), two methods, Clark Winsorization and weighted M-estimation, have shown potential to detect and adjust influential observations. This article discusses results of the application of a simulation methodology that generates realistic population time-series data. The new strategy enables evaluating Clark Winsorization and weighted M-estimation over repeated samples and producing conditional and unconditional performance measures. The analyses consider several scenarios for the occurrence of influential observations in the MRTS and assess the performance of the two methods for estimates of total retail sales and month-to-month change.

Detecting and Treating Verified Influential Values in a Monthly Retail Trade Survey

U.S. Census Bureau, Washington, DC 20233, U.S.A.

Journal of Official Statistics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

In survey data, an observation is considered influential if it is reported correctly and its weighted contribution has an excessive effect on a key estimate,...

Detecting and Treating Verified Influential Values in a Monthly Retail Trade Survey

Data publikacji: 11 gru 2014

Zakres stron: 721 - 747

Otrzymano: 01 lis 2012

Przyjęty: 01 paź 2014

DOI: https://doi.org/10.2478/jos-2014-0045

Słowa kluczowe
Outlier, Winsorization, M-estimation

© by Mary H. Mulry

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Detecting and Treating Verified Influential Values in a Monthly Retail Trade Survey

Data publikacji: 11 gru 2014

Zakres stron: 721 - 747

Otrzymano: 01 lis 2012

Przyjęty: 01 paź 2014

DOI: https://doi.org/10.2478/jos-2014-0045

Słowa kluczoweOutlier, Winsorization, M-estimation

© by Mary H. Mulry

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Słowa kluczowe
Outlier, Winsorization, M-estimation