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Statistical Model Development in Epidemiological Research

Award Information
Agency: Department of Defense
Branch: Defense Health Program
Contract: W81XWH-11-C-0511
Agency Tracking Number: O111-H02-3074
Amount: $147,696.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: OSD11-H02
Solicitation Number: 2011.1
Timeline
Solicitation Year: 2011
Award Year: 2011
Award Start Date (Proposal Award Date): 2011-09-30
Award End Date (Contract End Date): N/A
Small Business Information
2 Wisconsin Circle, Suite 700, Chevy Chase, MD, -
DUNS: 969278980
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Harrey Ji
 Manager
 (877) 531-7701
 Harrey.G@DigSysInc.com
Business Contact
 Raymond Santarsiero
Title: Manager
Phone: (877) 531-7701
Email: ray.s@digsysinc.com
Research Institution
 Stub
Abstract
Utilizing all SAS"s statistical and data manipulation power; Using SAS to interface with data sources -- Excel, Access, Oracle, DBII, Teradata, CSV, directly entered data; Building point and click to select data, read into application, save to output. Applying basic statistical model -- logistic, general linear, conditional logistic, ANOVA, MANCOVA, repeated measurements, survival/Poisson analysis , descriptive analysis.; Approaching complex statistical methods -- Propensity score (applied via matching, stratification, regression adjustment), instrumental variables, doubly robust estimation, local control to handle bias correction. For missing values, applying Baseline Observation Carried Forward, Last Observation Carried Forward, Completer"s Analysis, Multiple Imputation using MCMC, Multi-Imputation under MAR (Missing at Random) and MCAR (Missing Completely at Random) missing mechanisms in nonparametric regression, Mixed Model Repeated Measures, Marginal Structural Model with Inverse Probability of Treatment Weighting. To handle correlated longitudinal data, using innovative models such as mixed Model with appropriate variance-covariance structure to identify and correct the co-linearity; Applying small-area estimation techniques including synthetic method, spatial smoothing, regression to combine small area data. Developing software with features of Speed, flexibility, intuitive and easy; Enabling interact with operating system, and host system application such as SAS, SPSS, S-PLUS, STATA, R, JMP, JAVA, C++, SQL, VB, VBA, HTML.

* Information listed above is at the time of submission. *

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