Non-classical Measurement Error with False Positives and Negatives

2020 ◽  
Author(s):  
Julio Acuna
Author(s):  
Cheng-Yuan Ho ◽  
Ying-Dar Lin ◽  
Yuan-Cheng Lai ◽  
I-Wei Chen ◽  
Fu-Yu Wang ◽  
...  

2012 ◽  
Vol 58 (11) ◽  
pp. 1241-1257 ◽  
Author(s):  
Roberto Velasco-García ◽  
Rocío Vargas-Martínez

Many of the functions fulfilled by proteins in the cell require specific protein–protein interactions (PPI). During the last decade, the use of high-throughput experimental technologies, primarily based on the yeast 2-hybrid system, generated extensive data currently located in public databases. This information has been used to build interaction networks for different species. Unfortunately, due to the nature of the yeast 2-hybrid system, these databases contain many false positives and negatives, thus they require purging. A method for confirming these PPI is to test them using a technique that operates in vivo and detects binary PPI. This article comprises an overview of the study of PPI and describes the main techniques that have been used to identify bacterial PPI, prioritizing those that can be used for their verification, and it also mentions a number of PPI that have been identified or confirmed using these methods.


2013 ◽  
Vol 22 (23) ◽  
pp. 5738-5742 ◽  
Author(s):  
Hugo B. Harrison ◽  
Pablo Saenz-Agudelo ◽  
Serge Planes ◽  
Geoffrey P. Jones ◽  
Michael L. Berumen

2021 ◽  
Author(s):  
Andrew Athan McAleavey

The reliable change index (RCI) is a widely used statistical tool designed to account for measurement error when evaluating difference scores. Because of its conceptual simplicity and computational ease, it persists in research and applied psychology. However, researchers have repeatedly demonstrated ways that the RCI is insufficient or invalid for various applications. This is a problem in research and clinical psychology since this common tool is potentially problematic. The aims of this manuscript are to non-technically describe the formulation and assumptions of the RCI, to offer guidance as to when the RCI is (and is not) appropriate, and to identify what is needed for proper calculation of the RCI when it is used. Several criteria are identified to help determine whether the RCI is appropriate for a specific use. It is apparent that the RCI is the best available method only in a small number of situations, is frequently miscalculated, and produces incorrect inferences more often than simple alternatives, largely because it is highly insensitive to real changes. Specific alternatives are offered which may better operationalize common inferential tasks, including when more than two observations are available and when false negatives are equally costly to false positives.


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