Literature DB >> 33407168

Multiple imputation validation study: addressing unmeasured survey data in a longitudinal design.

Claire A Kolaja1,2, Ben Porter3,4, Teresa M Powell3,4, Rudolph P Rull4.   

Abstract

BACKGROUND: Questionnaires used in longitudinal studies may have questions added or removed over time for numerous reasons. Data missing completely at a follow-up survey is a unique issue for longitudinal studies. While such excluded questions lack information at one follow-up survey, they are collected at other follow-up surveys, and covariances observed at other follow-up surveys may allow for the recovery of the missing data. This study utilized data from a large longitudinal cohort study to assess the efficiency and feasibility of using multiple imputation (MI) to recover this type of information.
METHODS: Millennium Cohort Study participants completed the 9-item Patient Health Questionnaire (PHQ) depression module at 2 time points (2004, 2007). The suicidal ideation item in the module was set to missing for the 2007 assessment. Several single-level MI models using different sets of predictors and forms of suicidal ideation were used to compare self-reported values and imputed values for this item in 2007. Additionally, associations with sleep duration and smoking status, which are related constructs, were compared between self-reported and imputed values of suicidal ideation.
RESULTS: Among 63,028 participants eligible for imputation analysis, 4.05% reported suicidal ideation on the 2007 survey. The imputation models successfully identified suicidal ideation, with a sensitivity ranging between 34 and 66% and a positive predictive value between 36 and 42%. Specificity remained above 96% and negative predictive value above 97% for all imputed models. Similar associations were found for all imputation models on related constructs, though the dichotomous suicidal ideation imputed from the model using only PHQ depression items yielded estimates that were closest with the self-reported associations for all adjusted analyses.
CONCLUSIONS: Although sensitivity and positive predictive value were relatively low, applying MI techniques allowed for inclusion of an otherwise missing variable. Additionally, correlations with related constructs were estimated near self-reported values. Therefore, the other 8 depression items can be used to estimate suicidal ideation that was completely missing from a survey using MI. However, these imputed values should not be used to estimate population prevalence.

Entities:  

Keywords:  Cohort study; Longitudinal data; Major depressive disorder; Multiple imputation; Patient health questionnaire; Suicidal ideation; Survey data

Mesh:

Year:  2021        PMID: 33407168      PMCID: PMC7789687          DOI: 10.1186/s12874-020-01158-w

Source DB:  PubMed          Journal:  BMC Med Res Methodol        ISSN: 1471-2288            Impact factor:   4.615


  31 in total

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Authors:  J L Schafer; M K Olsen
Journal:  Multivariate Behav Res       Date:  1998-10-01       Impact factor: 5.923

2.  Association between short sleep and suicidal ideation and suicide attempt among adults in the general population.

Authors:  Renee D Goodwin; Andrej Marusic
Journal:  Sleep       Date:  2008-08       Impact factor: 5.849

3.  Use of missing data methods in longitudinal studies: the persistence of bad practices in developmental psychology.

Authors:  Helena Jelicić; Erin Phelps; Richard M Lerner
Journal:  Dev Psychol       Date:  2009-07

4.  Imputation of systematically missing predictors in an individual participant data meta-analysis: a generalized approach using MICE.

Authors:  Shahab Jolani; Thomas P A Debray; Hendrik Koffijberg; Stef van Buuren; Karel G M Moons
Journal:  Stat Med       Date:  2015-02-09       Impact factor: 2.373

5.  A comparison of the PRIME-MD PHQ-9 and PHQ-8 in a large military prospective study, the Millennium Cohort Study.

Authors:  Timothy S Wells; Jaime L Horton; Cynthia A LeardMann; Isabel G Jacobson; Edward J Boyko
Journal:  J Affect Disord       Date:  2012-12-14       Impact factor: 4.839

6.  Enhanced survey methods to clinically assess suicide risk.

Authors:  Matthew J Reinhard; Katharine J Bloeser
Journal:  Psychiatr Serv       Date:  2014-09-01       Impact factor: 3.084

7.  Reliability of standard health assessment instruments in a large, population-based cohort study.

Authors:  Tyler C Smith; Besa Smith; Isabel G Jacobson; Thomas E Corbeil; Margaret A K Ryan
Journal:  Ann Epidemiol       Date:  2007-04-11       Impact factor: 3.797

8.  Increased risk of suicidal ideation in smokers and former smokers compared to never smokers: evidence from the Baltimore ECA follow-up study.

Authors:  Diana E Clarke; William W Eaton; Kenneth R Petronis; Jean Y Ko; Anjan Chatterjee; James C Anthony
Journal:  Suicide Life Threat Behav       Date:  2010-08

9.  Alcohol use and alcohol-related problems before and after military combat deployment.

Authors:  Isabel G Jacobson; Margaret A K Ryan; Tomoko I Hooper; Tyler C Smith; Paul J Amoroso; Edward J Boyko; Gary D Gackstetter; Timothy S Wells; Nicole S Bell
Journal:  JAMA       Date:  2008-08-13       Impact factor: 56.272

10.  Does response on the PHQ-9 Depression Questionnaire predict subsequent suicide attempt or suicide death?

Authors:  Gregory E Simon; Carolyn M Rutter; Do Peterson; Malia Oliver; Ursula Whiteside; Belinda Operskalski; Evette J Ludman
Journal:  Psychiatr Serv       Date:  2013-12-01       Impact factor: 3.084

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