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Brief report| Volume 96, ISSUE 4, P746-749, April 2015

A Validation Study for Using Iterative Proportional Fitting to Weight the Traumatic Brain Injury Model Systems National Database: An NIDRR-Sponsored Study

Published:October 11, 2014DOI:https://doi.org/10.1016/j.apmr.2014.09.025

      Abstract

      Objective

      To verify that iterative proportional fitting (IPF), or raking, has the desired effect of aligning estimates and parameters so that researches have confidence in population projections when weighting the Traumatic Brian Injury Model Systems National Database.

      Design

      Secondary data analysis using IPF.

      Setting

      Inpatient rehabilitation.

      Participants

      People aged 16 years and older with a primary diagnosis of traumatic brain injury receiving initial inpatient rehabilitation.

      Intervention

      Not applicable.

      Main Outcome Measures

      Age at injury, race, sex, marital status, rehabilitation length of stay, payer source, and motor and cognitive FIM scores.

      Results

      This study demonstrates the utility of applying IPF to weight the TBI Model System National Database so that results of ensuing statistical analyses better reflect those in the United States who are 16 years and older with a primary diagnosis of TBI and are receiving inpatient rehabilitation.

      Conclusions

      In general, IPF aligns population estimates on the basis of weighted Traumatic Brian Injury Model Systems data and known population parameters. It is reasonable to assume that IPF has the same effect on unknown variables. This provides confidence to researchers wishing to use IPF for making population projections in analyses.

      Keywords

      List of abbreviations:

      IPF (iterative proportional fitting), TBI (traumatic brain injury), TBIMS (Traumatic Brain Injury Model Systems)
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