Missing-data analysis: socio- demographic, clinical and lifestyle determinants of low response rate on self- reported psychological and nutrition related multi- item instruments in the context of the ATTICA epidemiological study
Abstract Background Missing data is a common problem in epidemiological studies, while it becomes more critical, when the missing data concern a multi-item instrument, since lack of information in even one of its items, leads to the inability to calculate the total score of the instrument. The aim w...
Main Authors: | Thomas Tsiampalis, Demosthenes B. Panagiotakos |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2020-06-01
|
Series: | BMC Medical Research Methodology |
Subjects: | |
Online Access: | http://link.springer.com/article/10.1186/s12874-020-01038-3 |
Similar Items
-
The Effects of Missing Data Characteristics on the Choice of Imputation Techniques
by: Oyekale Abel Alade, et al.
Published: (2020-05-01) -
The Effect Of Missing Data Tecniques On Model Fit And Item Model Fit
by: Duygu KOÇAK, et al.
Published: (2017-06-01) -
DBSCANI: Noise-Resistant Method for Missing Value Imputation
by: Purwar Archana, et al.
Published: (2016-07-01) -
Foods, Nutrients and Dietary Patterns in Relation to Irrational Beliefs and Related Psychological Disorders: The ATTICA Epidemiological Study
by: Christina Vassou, et al.
Published: (2021-04-01) -
SICE: an improved missing data imputation technique
by: Shahidul Islam Khan, et al.
Published: (2020-06-01)