Responsible Imputation of Missing Speech Perception Testing Data & Analysis of 4,739 Observations and Predictors of Performance
Copyright © 2023, Otology & Neurotology, Inc..
OBJECTIVE: To address outcome heterogeneity in cochlear implant (CI) research, we built imputation models using multiple imputation by chained equations (MICEs) and K-nearest neighbors (KNNs) to convert between four common open-set testing scenarios: Consonant-Nucleus-Consonant word (CNCw), Arizona Biomedical (AzBio) in quiet, AzBio +5, and AzBio +10. We then analyzed raw and imputed data sets to evaluate factors affecting CI outcome variability.
STUDY DESIGN: Retrospective cohort study of a national CI database (HERMES) and a nonoverlapping single-institution CI database.
SETTING: Multi-institutional (32 CI centers).
PATIENTS: Adult CI recipients (n = 4,046 patients).
MAIN OUTCOME MEASURES: Mean absolute error (MAE) between imputed and observed speech perception scores.
RESULTS: Imputation models of preoperative speech perception measures demonstrate a MAE of less than 10% for feature triplets of CNCw/AzBio in quiet/AzBio +10 (MICE: MAE, 9.52%; 95% confidence interval [CI], 9.40-9.64; KNN: MAE, 8.93%; 95% CI, 8.83-9.03) and AzBio in quiet/AzBio +5/AzBio +10 (MICE: MAE, 8.85%; 95% CI, 8.68-9.02; KNN: MAE, 8.95%; 95% CI, 8.74-9.16) with one feature missing. Postoperative imputation can be safely performed with up to four of six features missing in a set of CNCw and AzBio in quiet at 3, 6, and 12 months postcochlear implantation using MICE (MAE, 9.69%; 95% CI, 9.63-9.76). For multivariable analysis of CI performance prediction, imputation increased sample size by 72%, from 2,756 to 4,739, with marginal change in adjusted R2 (0.13 raw, 0.14 imputed).
CONCLUSIONS: Missing data across certain sets of common speech perception tests may be safely imputed, enabling multivariate analysis of one of the largest CI outcomes data sets to date.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:44 |
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| Enthalten in: |
Otology & neurotology : official publication of the American Otological Society, American Neurotology Society [and] European Academy of Otology and Neurotology - 44(2023), 6 vom: 01. Juli, Seite e369-e378 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Pavelchek, Cole [VerfasserIn] |
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| Links: |
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| Themen: |
Journal Article |
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| Anmerkungen: |
Date Completed 16.06.2023 Date Revised 21.08.2023 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1097/MAO.0000000000003903 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM357338243 |
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| 100 | 1 | |a Pavelchek, Cole |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Responsible Imputation of Missing Speech Perception Testing Data & Analysis of 4,739 Observations and Predictors of Performance |
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| 500 | |a Date Revised 21.08.2023 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2023, Otology & Neurotology, Inc. | ||
| 520 | |a OBJECTIVE: To address outcome heterogeneity in cochlear implant (CI) research, we built imputation models using multiple imputation by chained equations (MICEs) and K-nearest neighbors (KNNs) to convert between four common open-set testing scenarios: Consonant-Nucleus-Consonant word (CNCw), Arizona Biomedical (AzBio) in quiet, AzBio +5, and AzBio +10. We then analyzed raw and imputed data sets to evaluate factors affecting CI outcome variability | ||
| 520 | |a STUDY DESIGN: Retrospective cohort study of a national CI database (HERMES) and a nonoverlapping single-institution CI database | ||
| 520 | |a SETTING: Multi-institutional (32 CI centers) | ||
| 520 | |a PATIENTS: Adult CI recipients (n = 4,046 patients) | ||
| 520 | |a MAIN OUTCOME MEASURES: Mean absolute error (MAE) between imputed and observed speech perception scores | ||
| 520 | |a RESULTS: Imputation models of preoperative speech perception measures demonstrate a MAE of less than 10% for feature triplets of CNCw/AzBio in quiet/AzBio +10 (MICE: MAE, 9.52%; 95% confidence interval [CI], 9.40-9.64; KNN: MAE, 8.93%; 95% CI, 8.83-9.03) and AzBio in quiet/AzBio +5/AzBio +10 (MICE: MAE, 8.85%; 95% CI, 8.68-9.02; KNN: MAE, 8.95%; 95% CI, 8.74-9.16) with one feature missing. Postoperative imputation can be safely performed with up to four of six features missing in a set of CNCw and AzBio in quiet at 3, 6, and 12 months postcochlear implantation using MICE (MAE, 9.69%; 95% CI, 9.63-9.76). For multivariable analysis of CI performance prediction, imputation increased sample size by 72%, from 2,756 to 4,739, with marginal change in adjusted R2 (0.13 raw, 0.14 imputed) | ||
| 520 | |a CONCLUSIONS: Missing data across certain sets of common speech perception tests may be safely imputed, enabling multivariate analysis of one of the largest CI outcomes data sets to date | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Multicenter Study | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 700 | 1 | |a Lee, David S |e verfasserin |4 aut | |
| 700 | 1 | |a Walia, Amit |e verfasserin |4 aut | |
| 700 | 1 | |a Michelson, Andrew P |e verfasserin |4 aut | |
| 700 | 1 | |a Ortmann, Amanda |e verfasserin |4 aut | |
| 700 | 1 | |a Gentile, Brynn |e verfasserin |4 aut | |
| 700 | 1 | |a Herzog, Jacques A |e verfasserin |4 aut | |
| 700 | 1 | |a Buchman, Craig A |e verfasserin |4 aut | |
| 700 | 1 | |a Shew, Matthew A |e verfasserin |4 aut | |
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