Comparison of parametric and Random Forest MICE in imputation of missing data in survival analysis

نویسندگان

  • Anoop D. Shah
  • Jonathan W. Bartlett
  • James Carpenter
  • Owen Nicholas
  • Harry Hemingway
چکیده

3 Results 6 3.1 Fully observed variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 3.2 Partially observed variable . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 3.3 Pairwise comparisons between methods . . . . . . . . . . . . . . . . . . . . 7 3.3.1 Comparison of bias . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 3.3.2 Comparison of precision . . . . . . . . . . . . . . . . . . . . . . . . . 8 3.3.3 Comparison of confidence interval length . . . . . . . . . . . . . . . . 8 3.3.4 Comparison of confidence interval coverage . . . . . . . . . . . . . . 8

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Comparison of Random Forest and Parametric Imputation Models for Imputing Missing Data Using MICE: A CALIBER Study

Multivariate imputation by chained equations (MICE) is commonly used for imputing missing data in epidemiologic research. The "true" imputation model may contain nonlinearities which are not included in default imputation models. Random forest imputation is a machine learning technique which can accommodate nonlinearities and interactions and does not require a particular regression model to be...

متن کامل

ارزیابی صحت پیش‌بینی ژنومی در معماری‌های مختلف ژنومی صفات کمی و آستانه‌ای با جانهی داده‌های ژنومی شبیه‌سازی‌شده، توسط روش جنگل تصادفی

Genomic selection is a promising challenge for discovering genetic variants influencing quantitative and threshold traits for improving the genetic gain and accuracy of genomic prediction in animal breeding. Since a proportion of genotypes are generally uncalled, therefore, prediction of genomic accuracy requires imputation of missing genotypes. The objectives of this study were (1) to quantify...

متن کامل

Influence of Pattern of Missing Data on Performance of Imputation Methods: An Example from National Data on Drug Injection in Prisons

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...

متن کامل

تحلیل مشاهدات گمشده در مطالعه اثر دوزهای مختلف مکمل ویتامین D بر مقاومت به انسولین در دوران بارداری

Introduction: The aim  of  this  study  was to impute missing data  and  to compare the effect  of  different doses of  vitamin D supplementation on  insulin resistance during  pregnancy. Methods: A clinical trial  study   was done on 104  women  with diabetes and gestational age less than 12 weeks between 1391 and...

متن کامل

Comparison of Random Survival Forests for Competing Risks and Regression Models in Determining Mortality Risk Factors in Breast Cancer Patients in Mahdieh Center, Hamedan, Iran

Introduction: Breast cancer is one of the most common cancers among women worldwide. Patients with cancer may die due to disease progression or other types of events. These different event types are called competing risks. This study aimed to determine the factors affecting the survival of patients with breast cancer using three different approaches: cause-specific hazards regression, subdistri...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2014