Delta Obesity Prevention Research Unit Site Logo
ARS Home About Us Helptop nav spacerContact Us En Espanoltop nav spacer
Printable VersionPrintable Version     E-mail this pageE-mail this page
Agricultural Research Service United States Department of Agriculture
Search
  Advanced Search
 
Programs and Projects
Subjects of Investigation
Research PBRC
Research USM
Research ACHRI
Research UAPB
Research ASU
Research SU
Research ARS
 

Research Project: DELTA OBESITY PREVENTION RESEARCH PROGRAM

Location: Delta Obesity Prevention Research Unit

Title: PRICING MISSING DATA IN THE MISSISSIPPI DELTA.

Authors
item Yadrick, Kathy - DELTA NIRI
item Connell, Carol - DELTA NIRI
item Gossett, Jeff - DELTA NIRI
item Simpson, Pippa - DELTA NIRI
item Jo, Chan-Hee - DELTA NIRI
item Huang, Emma - UNIV NORTH CAROLINA, BIOS
item Bogle, Margaret

Submitted to: Meeting Proceedings
Publication Type: Abstract Only
Publication Acceptance Date: April 23, 2004
Publication Date: June 10, 2004
Citation: Gossett, J., Simpson, P., Jo, C.H., Huang, B.E., Bogle, M., Yadrick, K., Connell, C. 2004. Pricing missing data in the Mississippi Delta [abstract]. Third Annual Conference of the International Society of Behavioral Nutrition and Physical Activity. p. 23.

Technical Abstract: Purpose: To use multiple imputation of missing prices so that prices of a market basket of food items in types of stores can be estimated and compared. Without imputation, even one missing food item would result in the exclusion of the entire store. Background: To assess the accessibility, availability, and cost of food items necessary for a healthy diet, a survey of food stores was conducted by the Lower Mississippi Delta Nutrition Intervention Research Initiative (Delta NIRI*) in rural Delta counties of Arkansas, Mississippi, and Louisiana. In this paper we address the estimation of the cost of a market basket of food items such as the Thrifty Food Plan basket. Basket items, and therefore prices, are not available at all stores. We discuss some approaches to the imputation of missing food item prices. Methods: Since we are sampling from a finite population, most commonly used procedures are not appropriate for the estimation of correct standard errors. We show how this may be done using existing software. For each of 5 sets of imputed data, we estimate the mean cost of the market basket and then use multiple imputation methods developed by Rubin and others to combine mean price and variance estimates. Conclusion: Imputing data may give additional useful information for pricing food baskets, and indeed for nutrition surveys. Methods are now available to do this correctly and relatively easily. Acknowledgements: This work was funded under the Lower Mississippi Delta Nutrition Intervention Research Initiative, USDA ARS grant #6251-53000-003-00D.

   

 
Publications
   Publications
 
Related National Programs
  Human Nutrition (107)
 
 
Last Modified: 05/18/2013
ARS Home | USDA.gov | Site Map | Policies and Links 
FOIA | Accessibility Statement | Privacy Policy | Nondiscrimination Statement | Information Quality | USA.gov | White House