Outcomes from stroke rehabilitation in Veterans Affairs rehabilitation units: detecting and correcting for selection bias.
This paper addresses the issue of statistical selection bias in multivariate models of functional gain estimated from observational data. Stroke patients from 20 high-volume Veterans Affairs Medical Centers (VAMCs) with acute and subacute inpatient rehabilitation treatment units were observed. Their gains in overall, motor, and cognitive functional status were measured with the use of the Functional Independence Measure (FIM). In estimating multivariate models of FIM gain during rehabilitation using these observational data, we found statistically significant evidence of selection bias, along with considerable differences in inferences between standard multivariate analyses and our selectivity-corrected models. Our results demonstrate the importance of detecting and correcting for statistical selection bias when one uses nonexperimental data to study gains in functional status.
Vogel
W Bruce
WB
Veterans Affairs Brain Rehabilitation Research Center, Malcom Randall Veterans Affairs Medical Center, Gainesville, FL 32608, USA. bruce.vogel@med.va.gov
Rittman
Maude
M
Bradshaw
Patrick
P
Nissen
Dan
D
Anderson
Leigh
L
Bates
Barbara
B
Marshall
Cliff
C
D000203:Activities of Daily Living; D003953:Diagnosis-Related Groups / Q000145:classification / Q000706:statistics & numerical data; D006302:Health Services Research; D006787:Hospitals, Veterans / Q000592:standards*; D006801:Humans; D016018:Least-Squares Analysis; D007902:Length of Stay / Q000706:statistics & numerical data; D015999:Multivariate Analysis; D017063:Outcome Assessment, Health Care / Q000592:standards*; D011237:Predictive Value of Tests; D020127:Recovery of Function; D012047:Rehabilitation Centers / Q000592:standards*; D015983:Selection Bias; D012720:Severity of Illness Index; D020521:Stroke / Q000145:classification / Q000503:physiopathology; D000071939:Stroke Rehabilitation; D014481:United States; D014493:United States Department of Veterans Affairs