Statistical Methods for Incomplete Data with Measurement Errors

Award Information
Agency:
Department of Health and Human Services
Branch
n/a
Amount:
$198,601.00
Award Year:
2012
Program:
SBIR
Phase:
Phase I
Contract:
1R43GM100573-01
Award Id:
n/a
Agency Tracking Number:
R43GM100573
Solicitation Year:
2012
Solicitation Topic Code:
NIGMS
Solicitation Number:
PA11-096
Small Business Information
6120 149TH AVE SE, BELLEVUE, WA, 98006-4620
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
3849838
Principal Investigator:
EDWARDCHAO
(425) 591-7944
echao@datanumerica.com
Business Contact:
KATHERINEWANG
(425) 802-9627
kwang@datanumerica.com
Research Institute:
Stub




Abstract
DESCRIPTION (provided by applicant): Missing data and measurement errors are common problems in statistical data analysis. We are interested in experimental and observational studies where there exist missing data and measurement errors problems. Examplesinclude health surveys containing non-responders or missing items, surrogate marker data with measurement errors, etc. The applications could be longitudinal clinical trials, multilevel community studies and health surveys. The incomplete data could be thenon-ignorable missing response used in a model or as predictors, i.e. missing response, missing covariate, and covariate measurement errors. The most complicated scenario is the combination of such difficulties, i.e. the missing response with covariate measurement errors. The results from this project include innovative statistical methods, case studies, tools, solutions, and publications. These resources will be incorporated in our Longit Informatics Center for sharing and illustration. The Longit Informatics Center is an online data analysis environment. Subscribers can access many statistical packages and dynamic graphics for data analysis. In this project, the ultimate results will be two statistical packages added to Longit: 1) MiMe: statistical methods for missing data and measurement errors, and 2) Laso: joint modeling methods for longitudinal and survival outcomes in the study of surrogate marker for clinical event time. These packages include innovative statistical methods, sensitivity analysis andgraphical methods. There is no commercial software to deal with complicated case as Laso. PUBLIC HEALTH RELEVANCE: This project aims to develop statistical methods and tools for analyzing incomplete data with missing data and measurement errors.

* information listed above is at the time of submission.

Agency Micro-sites


SBA logo

Department of Agriculture logo

Department of Commerce logo

Department of Defense logo

Department of Education logo

Department of Energy logo

Department of Health and Human Services logo

Department of Homeland Security logo

Department of Transportation logo

Enviromental Protection Agency logo

National Aeronautics and Space Administration logo

National Science Foundation logo
US Flag An Official Website of the United States Government