Identifying outliers and implausible values in growth trajectory data
نویسندگان
چکیده
منابع مشابه
New approach for the identification of implausible values and outliers in longitudinal childhood anthropometric data
PURPOSE We aimed to demonstrate the use of jackknife residuals to take advantage of the longitudinal nature of available growth data in assessing potential biologically implausible values and outliers. METHODS Artificial errors were induced in 5% of length, weight, and head circumference measurements, measured on 1211 participants from the Maternal Vitamin D for Infant Growth (MDIG) trial fro...
متن کاملAppendix a Methods for Identifying Data Outliers
Only extremely large rates are flagged, not extremely small ones, because only large values will have a major influence on statistics involving pounds of pesticide use. What value to use for the maximum rate in each criterion is somewhat arbitrary; the value determines how conservative one wants to be. We chose maximum rates to be close to what were considered obvious outliers by a group of sci...
متن کاملStatistical data preparation: management of missing values and outliers
Missing values and outliers are frequently encountered while collecting data. The presence of missing values reduces the data available to be analyzed, compromising the statistical power of the study, and eventually the reliability of its results. In addition, it causes a significant bias in the results and degrades the efficiency of the data. Outliers significantly affect the process of estima...
متن کاملIdentifying Multi-instance Outliers
This paper studies a new data mining problem called multiinstance outlier identification. This problem arises in tasks where each sample consists of many alternative feature vectors (instances) that describe it. This paper defines the multi-instance outliers and analyzes the basic types of multiinstance outliers. Two general identification approaches are proposed based on the state-of-the-art (...
متن کاملImpact of Outliers in Data Envelopment Analysis
This paper will examine the relationship between "Data Envelopment Analysis" and a statistical concept ``Outlier". Data envelopment analysis (DEA) is a method for estimating the relative efficiency of decision making units (DMUs) having similar tasks in a production system by multiple inputs to produce multiple outputs. An important issue in statistics is to identify the outliers. In this pap...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Annals of Epidemiology
سال: 2016
ISSN: 1047-2797
DOI: 10.1016/j.annepidem.2015.10.002