Research output: Contribution to conference - Without ISBN/ISSN › Poster › peer-review
Research output: Contribution to conference - Without ISBN/ISSN › Poster › peer-review
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TY - CONF
T1 - Influence of Missing Observations on Estimated Rates of Decline in Health Status
AU - Gavriel, Sonia
AU - Spencer, Sally
AU - Jones, Paul W
PY - 2003
Y1 - 2003
N2 - Hierarchical linear model (HLM) estimates of rates of change are used increasingly in COPD. We tested the effect of differential dropout between treatment arms on HLM and simple linear regression (REG) estimates of decline in health status measured using SGRQ data obtained from 149 patients 6-monthly for 3 years (7 observations/patient). 50% of patients were randomly allocated as 'dropouts', from whose data the last 1 or last 4 observations were removed to model different times in the 'study'. All data were retained in the remaining patients 'completers'. There were no differences in HLM or REG decline rates from complete data sets of the two groups (P>0.05). Mean decline rates are tabulated by group and number of missing observations (high score=faster decline). [Table]In 'dropouts' decline rates increased as missing data increased (i.e. period in "study" decreased), but the distribution of HLM decline rates (the SD) decreased while SD of REG estimates increased. In 'completers', the REG decline rates were stable, but the HLM decline rates increased as missing data increased in the 'dropouts'. These two methods of estimating decline rates respond differently to differential study dropout with important implications for longitudinal studies in COPD.This abstract is funded by: GlaxoSmithKlineSunday, May 18, 2003 8:15 AM
AB - Hierarchical linear model (HLM) estimates of rates of change are used increasingly in COPD. We tested the effect of differential dropout between treatment arms on HLM and simple linear regression (REG) estimates of decline in health status measured using SGRQ data obtained from 149 patients 6-monthly for 3 years (7 observations/patient). 50% of patients were randomly allocated as 'dropouts', from whose data the last 1 or last 4 observations were removed to model different times in the 'study'. All data were retained in the remaining patients 'completers'. There were no differences in HLM or REG decline rates from complete data sets of the two groups (P>0.05). Mean decline rates are tabulated by group and number of missing observations (high score=faster decline). [Table]In 'dropouts' decline rates increased as missing data increased (i.e. period in "study" decreased), but the distribution of HLM decline rates (the SD) decreased while SD of REG estimates increased. In 'completers', the REG decline rates were stable, but the HLM decline rates increased as missing data increased in the 'dropouts'. These two methods of estimating decline rates respond differently to differential study dropout with important implications for longitudinal studies in COPD.This abstract is funded by: GlaxoSmithKlineSunday, May 18, 2003 8:15 AM
M3 - Poster
T2 - American Thoracic Society
Y2 - 16 May 2003 through 21 May 2003
ER -