in interventional or observational longitudinal studies, the issue of missing values is one of the main concepts that should be investigated. the researcher's main concerns are the impact of missing data on the final results of the study and the appropriate methods that missing values should be handled. regarding the role and the scale of the variable that missing values have been occurred and ...

:هلاقم هصلاخ هداد حیضوت تیوضع عباوت ریداقم هلیسو هب تفج هب تفج هسیاقم هک ینامز یزاف یبتارم هلسلس لیلحترد اب یزافیراگزاس زا یفیرعت قیقحت نیا رد ،تسا هداس رایسب متسیس یراگزاس دروم رد ثحب،دوش یم ثعابو دنتسه رادروخرب یا هژیو تیمها زا یزاف یاه تبسن ،ًامازلا .دوش یم هئارا یراگزاس خرن نازیم یعضوم یاه تیولا تیوضع ریداقم اب یاه تیدودحم ناونع هب نینچمه ،دوش یم یراگزاسان خرن داجیا یدنب هبتر max-minیاه هعوم...

Background Policy makers need models to be able to detect groups at high risk of HIV infection. Incomplete records and dirty data are frequently seen in national data sets. Presence of missing data challenges the practice of model development. Several studies suggested that performance of imputation methods is acceptable when missing rate is moderate. One of the issues which was of less concern...

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....