title: Ipsative imputation for a 15-item Geriatric Depression Scale in community-dwelling elderly people.
abstract: BACKGROUND
  Missing data are inevitable in almost all medical studies. Imputation methods using the probabilistic model are common, but they cannot impute individual data and require special software. In contrast, the ipsative imputation method, which substitutes the missing items by the mean of the remaining items within the individual, is easy and does not need any special software, but it can provide individual scores. The aim of the present study was to evaluate the validity of the ipsative imputation method using data involving the 15-item Geriatric Depression Scale.
  
  
  METHODS
  Participants were community-dwelling elderly individuals (n = 1178). A structural equation model was constructed. The model fit indexes were calculated to assess the validity of the imputation method when it is used for individuals who were missing 20% of data or less and 40% of data or less, depending on whether we assumed that their correlation coefficients were the same as the dataset with no missing items. Finally, we compared path coefficients of the dataset imputed by ipsative imputation with those by multiple imputation.
  
  
  RESULTS
  When compared with the assumption that the datasets differed, all of the model fit indexes were better under the assumption that the dataset without missing data is the same as that that was missing 20% of data or less. However, by the same assumption, the model fit indexes were worse in the dataset that was missing 40% of data or less. The path coefficients of the dataset imputed by ipsative imputation and by multiple imputation were compatible with each other if the proportion of missing items was 20% or less.
  
  
  CONCLUSIONS
  Ipsative imputation appears to be a valid imputation method and can be used to impute data in studies using the 15-item Geriatric Depression Scale, if the percentage of its missing items is 20% or less.
authors.affiliation: Department of Field Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
authors.forename: Hissei
authors.initials: H
authors.lastname: Imai
authors.forename: Toshiaki A
authors.initials: TA
authors.lastname: Furukawa
authors.forename: Yoriko
authors.initials: Y
authors.lastname: Kasahara
authors.forename: Yasuko
authors.initials: Y
authors.lastname: Ishimoto
authors.forename: Yumi
authors.initials: Y
authors.lastname: Kimura
authors.forename: Eriko
authors.initials: E
authors.lastname: Fukutomi
authors.forename: Wen-Ling
authors.initials: WL
authors.lastname: Chen
authors.forename: Mire
authors.initials: M
authors.lastname: Tanaka
authors.forename: Ryota
authors.initials: R
authors.lastname: Sakamoto
authors.forename: Taizo
authors.initials: T
authors.lastname: Wada
authors.forename: Michiko
authors.initials: M
authors.lastname: Fujisawa
authors.forename: Kiyohito
authors.initials: K
authors.lastname: Okumiya
authors.forename: Kozo
authors.initials: K
authors.lastname: Matsubayashi
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000523:psychology*; D003627:Data Interpretation, Statistical; D003863:Depression / Q000175:diagnosis*; D005260:Female; D015577:Geriatric Assessment; D006801:Humans; D007564:Japan; D016014:Linear Models; D008297:Male; D011569:Psychiatric Status Rating Scales; D011594:Psychometrics; D011788:Quality of Life / Q000523:psychology*; D015203:Reproducibility of Results; D011795:Surveys and Questionnaires
keywords: Geriatric Depression Scale (GDS); depression; imputation; missing data