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Background:

The aim of the article is demonstrating an application of multiple imputation (MI) for handling missing clinical data in the setting of rheumatologic surveys using data derived from 10291 people participating in the first phase of the Community Oriented Program for Control of Rheumatic Disorders (COPCORD) in Iran.

Methods:

Five data subsets were produced from the original data set. Certain demographics were selected as complete variables. In each subset, we created a univariate pattern of missingness for knee osteoarthritis status as the outcome variable (disease) using different mechanisms and percentages. The crude disease proportion and its standard error were estimated separately for each complete data set to be used as true (baseline) values for percent bias calculation. The parameters of interest were also estimated for each incomplete data subset using two approaches to deal with missing …