A novel internal validity index based on the cluster centre and the nearest neighbour cluster

2018 ◽  
Vol 71 ◽  
pp. 78-88 ◽  
Author(s):  
Shibing Zhou ◽  
Zhenyuan Xu
Keyword(s):  
Internal Validity ◽  
Nearest Neighbour ◽  
Validity Index ◽  
Cluster Centre ◽  
Neighbour Cluster

scholarly journals Creation and validation of a questionnaire to assess pre-conceptional health needs of women in Italy

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
A Orfino ◽  
D Zace ◽  
A M Viteritti ◽  
C de Waure ◽  
M L Di Pietro
Keyword(s):  
Young Women ◽  
Internal Validity ◽  
Healthcare Services ◽  
Access To Healthcare ◽  
Health Needs ◽  
Women Of Childbearing Age ◽  
Childbearing Age ◽  
Validity Index ◽  
Delphi Procedure ◽  
Mother And Child

Abstract Background Pre-conceptional health refers to women's conditions before pregnancy. Women's knowledge, behavior and lifestyle in this period greatly influence the health of the future mother and child. This study aimed at creating and validating a questionnaire to describe the knowledge, behaviors, health status and access to healthcare services of young women of childbearing age in Italy. Methods A systematic literature review on Scopus, PubMed and Web of Science was conducted to collect the relevant information for the questionnaire's construction. Based on the review's results, a first draft of the questionnaire was developed and, then, submitted to a panel of experts for validation through the Delphi Procedure. Twenty-one multidisciplinary experts reviewed the items for content, applicability, and rated each item in terms of validity and relevance by indicating a value from 1 to 5 on a Likert scale. Cronbach's Alpha and Internal Validity Index were calculated to verify the internal reliability and validity of content. Results After the screening process, thirty-one articles were included in the systematic review. The main results concerned knowledge on pre-conceptional health, physical, mental and social health, nutritional status, lifestyle and access to healthcare services. The first draft of the questionnaire, submitted to the experts' panel for consensus, consisted of 89 items and 13 sections. Consensus was reached after two rounds of Delphi Procedure. The final version of the questionnaire consisted of 88 items and 10 sections, reporting a Cronbach's Alpha of 0.99 and an Internal Validity Index of 0.93. Conclusions The questionnaire developed in this study is a valid tool to identify the pre-conceptional health needs of young women. The results may be used by policy makers and various guidelines concerning pre-conceptional health and for the implementation of personalized interventions, aimed to improve the health of this population. Key messages Women’s knowledge, behaviours and lifestyle in the pre-conceptional period greatly influence the health of the future mother and child. This study reports the process of creation of a questionnaire which is proved to be a valid tool to identify the pre-conceptional health needs of young women of childbearing age in Italy.

A Hybrid Validity Index to Determine K Parameter Value of k-Means Algorithm for Time Series Clustering

2021 ◽  
pp. 1-22
Author(s):  
Fatma Ozge Ozkok ◽  
Mete Celik
Keyword(s):  
Time Series ◽  
Clustering Algorithms ◽  
Real Life ◽  
Internal Validity ◽  
The Other ◽  
Sequential Data ◽  
Data Mining Technique ◽  
Validity Index ◽  
Number Of Clusters ◽  
Benchmark Datasets

Time series is a set of sequential data point in time order. The sizes and dimensions of the time series datasets are increasing day by day. Clustering is an unsupervised data mining technique that groups objects based on their similarities. It is used to analyze various datasets, such as finance, climate, and bioinformatics datasets. [Formula: see text]-means is one of the most used clustering algorithms. However, it is challenging to determine the value of [Formula: see text] parameter, which is the number of clusters. One of the most used methods to determine the number of clusters (such as [Formula: see text]) is cluster validity indexes. Several internal and external validity indexes are used to find suitable cluster numbers based on characteristics of datasets. In this study, we propose a hybrid validity index to determine the value of [Formula: see text] parameter of [Formula: see text]-means algorithm. The proposed hybrid validity index comprises four internal validity indexes, such as Dunn, Silhouette, C index, and Davies–Bouldin indexes. The proposed method was applied to nine real-life finance and benchmarks time series datasets. The financial dataset was obtained from Yahoo Finance, consisting of daily closing data of stocks. The other eight benchmark datasets were obtained from UCR time series classification archive. Experimental results showed that the proposed hybrid validity index is promising for finding the suitable number of clusters with respect to the other indexes for clustering time-series datasets.

scholarly journals An Internal Validity Index Based on Density-Involved Distance

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 40038-40051 ◽  
Author(s):  
Lianyu Hu ◽  
Caiming Zhong
Keyword(s):  
Internal Validity ◽  
Validity Index

scholarly journals Improving Prototypes Representativeness by Internal Validity Index Analysis

2021 ◽  
Vol 19 (1) ◽  
pp. 4-16
Author(s):  
Alexandre Szabo ◽  
Thomaz A. Ruckl
Keyword(s):  
Internal Validity ◽  
Synthetic Dataset ◽  
Validity Index ◽  
Squared Error ◽  
Index Analysis ◽  
Error Index ◽  
Index Value

Internal validity indexes are applied to evaluate the solution of a partition, which no equally reflects the same quality for all clusters, individually, in terms of prototypes representativeness. Thus, knowing their representativeness in respective clusters, it is possible adjust them to increase the confidence in analysis of found clusters. In this sense, this paper proposes a simple and effective method to obtain the internal validity index value in every cluster in a partition, identify those with low prototypes representativeness and improve them. Experiments were carried out by sum of the squared error index, which measures the compactness of clusters. The behavior of the method was illustrated by a synthetic dataset and performed for ten datasets from the literature with k-Means algorithm. The results demonstrated its effectiveness for all experiments.

The structure of amorphous and polycrystalline materials using energy-filtered RDF analysis

1992 ◽  
Vol 50 (2) ◽  
pp. 1190-1191
Author(s):  
David Cockayne ◽  
David McKenzie
Keyword(s):  
Electron Diffraction ◽  
Diffraction Pattern ◽  
Density Function ◽  
Electron Diffraction Pattern ◽  
Polycrystalline Materials ◽  
Nearest Neighbour ◽  
X Ray ◽  
Selected Area Electron Diffraction ◽  
Reduced Density ◽  
System F

The technique of Electron Reduced Density Function (RDF) analysis has ben developed into a rapid analytical tool for the analysis of small volumes of amorphous or polycrystalline materials. The energy filtered electron diffraction pattern is collected to high scattering angles (currendy to s = 2 sinθ/λ = 6.5 Å-1) by scanning the selected area electron diffraction pattern across the entrance aperture to a GATAN parallel energy loss spectrometer. The diffraction pattern is then converted to a reduced density function, G(r), using mathematical procedures equivalent to those used in X-ray and neutron diffraction studies.Nearest neighbour distances accurate to 0.01 Å are obtained routinely, and bond distortions of molecules can be determined from the ratio of first to second nearest neighbour distances. The accuracy of coordination number determinations from polycrystalline monatomic materials (eg Pt) is high (5%). In amorphous systems (eg carbon, silicon) it is reasonable (10%), but in multi-element systems there are a number of problems to be overcome; to reduce the diffraction pattern to G(r), the approximation must be made that for all elements i,j in the system, fj(s) = Kji fi,(s) where Kji is independent of s.

Reversion Toward the Mean Independently of Regression Toward the Mean

Methodology ◽  
2009 ◽  
Vol 5 (1) ◽  
pp. 3-6 ◽  
Author(s):  
Merton S. Krause
Keyword(s):  
Random Error ◽  
Evaluation Studies ◽  
Internal Validity ◽  
Intervention Evaluation ◽  
Population Mean ◽  
Experimental Intervention ◽  
Sample Data ◽  
The Mean ◽  
Regression Toward The Mean

There is another important artifactual contributor to the apparent improvement of persons subjected to an experimental intervention which may be mistaken for regression toward the mean. This is the phenomenon of random error and extreme selection, which does not at all involve the population regression of posttest on pretest scores but involves a quite different and independent reversion of subjects’ scores toward the population mean. These two independent threats to the internal validity of intervention evaluation studies, however, can be detected and differentiated on the sample data of such studies.

Internal Validity of the School-Climate Bullying Survey

2008 ◽  
Author(s):  
Sharmila Bandyopadhyay ◽  
Dewey G. Cornell ◽  
Timothy R. Konold
Keyword(s):  
School Climate ◽  
Internal Validity

The Distribution of Hospitality Services in Uyo Urban, Nigeria

2018 ◽  
pp. 137-150
Author(s):  
Violet Bassey Eneyo
Keyword(s):  
Data Collection ◽  
Global Positioning System ◽  
Central Area ◽  
Positioning System ◽  
Nearest Neighbour ◽  
Global Positioning ◽  
Neighbour Analysis

This paper examines the distribution of hospitality services in Uyo Urban, Nigeria. GIS method was the primary tool used for data collection. A global positioning system (GPS) Garmin 60 model was used in tracking the location of 102 hospitality services in the study area. One hypothesis was stated and tested using the nearest neighbour analysis. The finding shows evidence of clustering of the various hospitality services. The tested hypothesis further indicated that hospitality services clustered in areas that guarantee a sustainable level of patronage to maximize profit. Thus, the hospitality services clustered in selected streets in the metropolis while limited numbers were found outside the city’s central area.

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