1 40 1 Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Citation List Month Backlog URL Address <a href="http://doi.org/10.1186/1471-2288-6-57" target="_blank" rel="noreferrer">http://doi.org/10.1186/1471-2288-6-57</a> Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Dealing with missing data in a multi-question depression scale: a comparison of imputation methods Publisher An entity responsible for making the resource available Bmc Medical Research Methodology Date A point or period of time associated with an event in the lifecycle of the resource 2006 Subject The topic of the resource Female; Humans; Male; Attitude to Health; Questionnaires; Research Design; Hospitals; Reproducibility of Results; Regression Analysis; Alberta; Teaching; Statistical; Data Interpretation; Psychiatric Status Rating Scales; Self Assessment (Psychology); Surgical Procedures; Depression/classification/diagnosis; Operative/psychology; Outcome Assessment (Health Care)/methods/statistics & numerical data; Preoperative Care; Psychometrics/methods Creator An entity primarily responsible for making the resource Shrive FM; Stuart H; Quan H; Ghali WA Description An account of the resource BACKGROUND: Missing data present a challenge to many research projects. The problem is often pronounced in studies utilizing self-report scales, and literature addressing different strategies for dealing with missing data in such circumstances is scarce. The objective of this study was to compare six different imputation techniques for dealing with missing data in the Zung Self-reported Depression scale (SDS). METHODS: 1580 participants from a surgical outcomes study completed the SDS. The SDS is a 20 question scale that respondents complete by circling a value of 1 to 4 for each question. The sum of the responses is calculated and respondents are classified as exhibiting depressive symptoms when their total score is over 40. Missing values were simulated by randomly selecting questions whose values were then deleted (a missing completely at random simulation). Additionally, a missing at random and missing not at random simulation were completed. Six imputation methods were then considered; 1) multiple imputation, 2) single regression, 3) individual mean, 4) overall mean, 5) participant's preceding response, and 6) random selection of a value from 1 to 4. For each method, the imputed mean SDS score and standard deviation were compared to the population statistics. The Spearman correlation coefficient, percent misclassified and the Kappa statistic were also calculated. RESULTS: When 10% of values are missing, all the imputation methods except random selection produce Kappa statistics greater than 0.80 indicating 'near perfect' agreement. MI produces the most valid imputed values with a high Kappa statistic (0.89), although both single regression and individual mean imputation also produced favorable results. As the percent of missing information increased to 30%, or when unbalanced missing data were introduced, MI maintained a high Kappa statistic. The individual mean and single regression method produced Kappas in the 'substantial agreement' range (0.76 and 0.74 respectively). CONCLUSION: Multiple imputation is the most accurate method for dealing with missing data in most of the missind data scenarios we assessed for the SDS. Imputing the individual's mean is also an appropriate and simple method for dealing with missing data that may be more interpretable to the majority of medical readers. Researchers should consider conducting methodological assessments such as this one when confronted with missing data. The optimal method should balance validity, ease of interpretability for readers, and analysis expertise of the research team. 2006 Identifier An unambiguous reference to the resource within a given context <a href="http://doi.org/10.1186/1471-2288-6-57" target="_blank" rel="noreferrer">10.1186/1471-2288-6-57</a> Rights Information about rights held in and over the resource Article information provided for research and reference use only. PedPalASCNET does not hold any rights over the resource listed here. All rights are retained by the journal listed under publisher and/or the creator(s). Type The nature or genre of the resource Journal Article 2006 Alberta Attitude To Health Backlog Bmc Medical Research Methodology Data Interpretation Depression/classification/diagnosis Female Ghali WA Hospitals Humans Journal Article Male Operative/psychology Outcome Assessment (Health Care)/methods/statistics & numerical data Preoperative Care Psychiatric Status Rating Scales Psychometrics/methods Quan H Questionnaires Regression Analysis Reproducibility of Results Research Design Self Assessment (Psychology) Shrive FM statistical Stuart H Surgical Procedures Teaching