Peter Jacoby1, Andrew Whitehouse1, Helen Leonard1, Jacinta Saldaris1, Scott Demarest2, Tim Benke2, Jenny Downs1,3. 1. Telethon Kids Institute, the University of Western Australia, Perth, Western Australia, Australia. 2. Children's Hospital Colorado, Paediatric Neurology, University of Colorado School of Medicine, Aurora, CO. 3. School of Allied Health, Curtin University, Perth, Western Australia, Australia.
Abstract
OBJECTIVE: The aim of this study was to devise an evidence-based missing data rule for the Quality of Life Inventory-Disability (QI-Disability) questionnaire specifying how many missing items are permissible for domain and total scores to be calculated using simple imputation. We sought a straightforward rule that can be used in both research and clinical monitoring settings. METHOD: A simulation study was conducted involving random selection of missing items from a complete data set of questionnaire responses. This comprised 520 children with intellectual disability from 5 diagnostic groups. We applied a simple imputation scheme, and the simulated distribution of errors induced by imputation was compared with the previously estimated standard error of measurement (SEM) for each domain. RESULTS: Using a stringent criterion, which requires that the 95th percentile of absolute error be less than the SEM, 1 missing item should be permitted for 2 of the 6 QI-Disability subdomain scores to be calculated and 1 missing item per domain for the total score to be calculated. Other, less stringent criteria would allow up to 2 missing items per domain. CONCLUSION: Empirical evidence about the impact of imputing missing questionnaire responses can be gathered using simulation methods applied to a complete data set. We recommend that such evidence be used in devising a rule that specifies how many items can be imputed for a valid score to be calculated.
OBJECTIVE: The aim of this study was to devise an evidence-based missing data rule for the Quality of Life Inventory-Disability (QI-Disability) questionnaire specifying how many missing items are permissible for domain and total scores to be calculated using simple imputation. We sought a straightforward rule that can be used in both research and clinical monitoring settings. METHOD: A simulation study was conducted involving random selection of missing items from a complete data set of questionnaire responses. This comprised 520 children with intellectual disability from 5 diagnostic groups. We applied a simple imputation scheme, and the simulated distribution of errors induced by imputation was compared with the previously estimated standard error of measurement (SEM) for each domain. RESULTS: Using a stringent criterion, which requires that the 95th percentile of absolute error be less than the SEM, 1 missing item should be permitted for 2 of the 6 QI-Disability subdomain scores to be calculated and 1 missing item per domain for the total score to be calculated. Other, less stringent criteria would allow up to 2 missing items per domain. CONCLUSION: Empirical evidence about the impact of imputing missing questionnaire responses can be gathered using simulation methods applied to a complete data set. We recommend that such evidence be used in devising a rule that specifies how many items can be imputed for a valid score to be calculated.
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