scholarly journals Constructing Confidence Intervals for Spearman’s Rank Correlation with Ordinal Data: A Simulation Study Comparing Analytic and Bootstrap Methods

2008 ◽  
Vol 7 (2) ◽  
pp. 416-434 ◽  
Author(s):  
John Ruscio
Keyword(s):  
Confidence Intervals ◽  
Simulation Study ◽  
Ordinal Data ◽  
Rank Correlation ◽  
Bootstrap Methods ◽  
Spearman’S Rank Correlation

scholarly journals Overcoming Obstacles Facing the Contractors Sector in Saudi Arabia Using a Rank Correlation Method

2013 ◽  
Vol 7 (1) ◽  
pp. 170-181 ◽  
Author(s):  
Mansour N. Jadid
Keyword(s):  
Saudi Arabia ◽  
Ordinal Data ◽  
Rank Correlation ◽  
Correlation Method ◽  
Point Of View ◽  
Improve Performance ◽  
Comprehensive Investigation ◽  
Spearman’S Rank Correlation ◽  
Rank Correlation Method ◽  
Building Activities

The contractors sector is considered to be one of the most important sectors in terms of its effects on economic development, stabilization, and urbanization. The main objective of this study was to explore and analyze the obstacles facing the contractors sector in Saudi Arabia from the contractors’ point of view using Spearman’s rank correlation method, where the dimensionality of ordinal data was reduced by factor analysis. This required a comprehensive investigation of the obstacles that prevented contractors from completing their jobs on time, or that led to them completing a lower quality job and losing money. This study only included Saudi contractors involved with building activities and it was based on data collection using comprehensive questionnaires that defined five main factors: managerial, financial, expansion, environmental and technical. Contractors who were qualified and registered by the Ministry of Municipal and Rural Affairs (MOMRA) were considered in this study. The study concentrated on the building sector, specifically the fields and activities defined by MOMRA. Identifying the obstacles that affect professional and technical activities should help to improve performance and address various problems. A digital interactive structural questionnaire was designed and distributed via the internet to collect responses from the participants where a Likert scale-based method was used. The results obtained using the questionnaires are presented as tables and figures.

scholarly journals Correlation Test Application of Supplier’s Ranking Using TOPSIS and AHP-TOPSIS Method

CAUCHY ◽  
2016 ◽  
Vol 4 (2) ◽  
pp. 65 ◽  
Author(s):  
Ika Yuniwati
Keyword(s):  
Ordinal Data ◽  
Selection Process ◽  
Rank Correlation ◽  
P Value ◽  
Topsis Method ◽  
Kendall’S Tau ◽  
Kendall's Tau ◽  
Spearman Rank ◽  
Correlation Test ◽  
Spearman’S Rank Correlation

The supplier selection process can be done using multi-criteria decision making (MCDM) methods in firms. There are many MCDM Methods, but firms must choose the method suitable with the firm condition. Company A has analyzed supplier’s ranking using TOPSIS method. TOPSIS method has a marjor weakness in its subjective weighting. This flaw is overcome using AHP method weighting having undergone a consistency test. In this study, the comparison of supplier’s ranking using TOPSIS and AHP-TOPSIS method used correlation test. The aim of this paper is to determine different result from two methods. Data in suppliers’ ranking is ordinal data, so this process used Spearman’s rank and Kendall’s tau b correlation. If most of the ranked scored are same, Kendall’s tau b correlation should be used. The other way, Spearman rank should be used. The result of this study is that most of the ranked scored are different, so the process used Spearman rank p-value of Spearman’s rank correlation of 0.505. It is greater than 0.05, means there is no statistically significant correlation between two methods. Furthermore, increment or decrement of supplier’s ranking in one method is not significantly related to the increment or decrement of supplier’s ranking in the second method

A Study of the Relationships between Nursing Students’ Meanings of Life, Positive Beliefs, and Well-Being

2018 ◽  
Vol 3 (01) ◽  
Author(s):  
Fu-Ju Tsai ◽  
Cheng-Yu Chen ◽  
Gwo-Liang Yeh ◽  
Yih-Jin Hu ◽  
Chie-Chien Tseng ◽  
...  
Keyword(s):  
Health Promotion ◽  
Nursing Students ◽  
Analysis Of Variance ◽  
Rank Correlation ◽  
Meaning Of Life ◽  
Well Being ◽  
Social Health ◽  
Cross Sectional ◽  
Nursing Educators ◽  
Spearman’S Rank Correlation

Background: Nursing educators should train nursing students to pursue physical, psychological, spiritual, and social health promotion. The purpose of this study was to explore relationships between nursing students’ meaning of life, positive beliefs, and well-being. Methods: A cross-sectional correlational study with a quantitative approach was adopted. Purposive sampling was used. A total of 170 nursing students voluntarily participated in this study. A 56-item questionnaire was used to examine nursing students’ meaning of life (1-25 items), positive beliefs (1-11 items), and well-being (1-20 items). The content validity index (CVI) of the study questionnaire was established as 0.95 by seven expert scholars. The reliability values for the three parts of the measure were as follows: meaning of life, Cronbach’s α 0.96; positive beliefs, Cronbach’s α 0.93; and well-being, Cronbach’s α 0.95. Percentages, frequencies, means, SDs, Kruskal-Wallis one-way analysis of variance by rank, Spearman’s rank correlation, one-way analysis of variance, Spearman’s rho correlation, and regression analysis were used for the data analysis. Results: Nursing students had the following mean scores: meaning of life with 4.02 (SD 0.56); positive beliefs with 3.92 (SD 0.62); and well-being with 3.95 (SD 0.57). The results indicate that for all nursing students, meaning of life was positively correlated with positive beliefs, r=0.83 (P<.01); similarly, all nursing students had positive beliefs that were positively correlated with meaning of life, r=0.83 (P<.01). In the results of the study, the nursing students’ background, meaning of life and positive beliefs explained 63% of the variance in well-being (Adjusted R2 squared =0.63, F=33.41, P<.001). Conclusions: Nursing students’ sense of meaning of life and positive beliefs may impact their well-being. Therefore, nursing educators can promote meaning of life and positive beliefs to nursing students as a way to increase their well-being for physical, psychological, spiritual, and social health promotion.

scholarly journals Deregulation of lncRNA HIST1H2AG-6 and AIM1-3 in peripheral blood mononuclear cells is associated with newly diagnosed type 2 diabetes

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Hui Jiang ◽  
Peian Lou ◽  
Xiaoluo Chen ◽  
Chenguang Wu ◽  
Shihe Shao
Keyword(s):  
Roc Curve ◽  
Multivariate Logistic Regression Analysis ◽  
Rank Correlation ◽  
Differentially Expressed ◽  
Healthy Controls ◽  
Biological Functions ◽  
Multivariate Logistic Regression ◽  
Spearman’S Rank Correlation ◽  
Spearman’S Rank Correlation Coefficient

Abstract Background Type 2 diabetes mellitus (T2DM) is mainly affected by genetic and environmental factors; however, the correlation of long noncoding RNAs (lncRNAs) with T2DM remains largely unknown. Methods Microarray analysis was performed to identify the differentially expressed lncRNAs and messenger RNAs (mRNAs) in patients with T2DM and healthy controls, and the expression of two candidate lncRNAs (lnc-HIST1H2AG-6 and lnc-AIM1-3) were further validated using quantitative real-time polymerase chain reaction (qRT-PCR). Spearman’s rank correlation coefficient was used to measure the degree of association between the two candidate lncRNAs and differentially expressed mRNAs. Furthermore, the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway and GO (Gene Ontology) enrichment analysis were used to reveal the biological functions of the two candidate lncRNAs. Additionally, multivariate logistic regression analysis and receiver operating characteristic (ROC) curve analysis were performed. Results The microarray analysis revealed that there were 55 lncRNAs and 36 mRNAs differentially expressed in patients with T2DM compared with healthy controls. Notably, lnc-HIST1H2AG-6 was significantly upregulated and lnc-AIM1-3 was significantly downregulated in patients with T2DM, which was validated in a large-scale qRT-PCR examination (90 controls and 100 patients with T2DM). Spearman’s rank correlation coefficient revealed that both lncRNAs were correlated with 36 differentially expressed mRNAs. Furthermore, functional enrichment (KEGG and GO) analysis demonstrated that the two lncRNA-related mRNAs might be involved in multiple biological functions, including cell programmed death, negative regulation of insulin receptor signal, and starch and sucrose metabolism. Multivariate logistic regression analysis revealed that lnc-HIST1H2AG-6 and lnc-AIM1-3 were significantly correlated with T2DM (OR = 5.791 and 0.071, respectively, both P = 0.000). Furthermore, the ROC curve showed that the expression of lnc-HIST1H2AG-6 and lnc-AIM1-3 might be used to differentiate patients with T2DM from healthy controls (area under the ROC curve = 0.664 and 0.769, respectively). Conclusion The profiles of lncRNA and mRNA were significantly changed in patients with T2DM. The expression levels of lnc-HIST1H2AG-6 and lnc-AIM1-3 genes were significantly correlated with some features of T2DM, which may be used to distinguish patients with T2DM from healthy controls and may serve as potential novel biomarkers for diagnosis in the future.

scholarly journals Magnetic resonance cisternography imaging findings related to the leakage of Gadolinium into the subarachnoid space

2021 ◽  
Author(s):  
Rei Nakamichi ◽  
Toshiaki Taoka ◽  
Hisashi Kawai ◽  
Tadao Yoshida ◽  
Michihiko Sone ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Subarachnoid Space ◽  
Area Under The Curve ◽  
Rank Correlation ◽  
Predictive Performance ◽  
Roc Curves ◽  
Imaging Findings ◽  
Spearman’S Rank Correlation ◽  
Sagittal Sinus ◽  
Magnetic Resonance Cisternography

Abstract Purpose To identify magnetic resonance cisternography (MRC) imaging findings related to Gadolinium-based contrast agent (GBCA) leakage into the subarachnoid space. Materials and methods The number of voxels of GBCA leakage (V-leak) on 3D-real inversion recovery images was measured in 56 patients scanned 4 h post-intravenous GBCA injection. Bridging veins (BVs) were identified on MRC. The numbers of BVs with surrounding cystic structures (BV-cyst), with arachnoid granulations protruding into the superior sagittal sinus (BV-AG-SSS) and the skull (BV-AG-skull), and including any of these factors (BV-incl) were recorded. Correlations between these variables and V-leak were examined based on the Spearman’s rank correlation coefficient. Receiver-operating characteristic (ROC) curves were generated to investigate the predictive performance of GBCA leakage. Results V-leak and the number of BV-incl were strongly correlated (r = 0.609, p < 0.0001). The numbers of BV-cyst and BV-AG-skull had weaker correlations with V-leak (r = 0.364, p = 0.006; r = 0.311, p = 0.020, respectively). The number of BV-AG-SSS was not correlated with V-leak. The ROC curve for contrast leakage exceeding 1000 voxels and the number of BV-incl had moderate accuracy, with an area under the curve of 0.871. Conclusion The number of BV-incl may be a predictor of GBCA leakage and a biomarker for waste drainage function without using GBCA.

scholarly journals Predicting presenteeism using measures of health status

2021 ◽  
Author(s):  
Cheryl Jones ◽  
Katherine Payne ◽  
Alexander Thompson ◽  
Suzanne M. M. Verstappen
Keyword(s):  
Health Status ◽  
Online Survey ◽  
Activity Index ◽  
Work Productivity ◽  
Rank Correlation ◽  
Ordinary Least Squares ◽  
Statistical Correlation ◽  
Least Squares Regression ◽  
Mapping Algorithm ◽  
Spearman’S Rank Correlation

Abstract Objectives To identify whether it is feasible to develop a mapping algorithm to predict presenteeism using multiattribute measures of health status. Methods Data were collected using a bespoke online survey in a purposive sample (n = 472) of working individuals with a self-reported diagnosis of Rheumatoid arthritis (RA). Survey respondents were recruited using an online panel company (ResearchNow). This study used data captured using two multiattribute measures of health status (EQ5D-5 level; SF6D) and a measure of presenteeism (WPAI, Work Productivity Activity Index). Statistical correlation between the WPAI and the two measures of health status (EQ5D-5 level; SF6D) was assessed using Spearman’s rank correlation. Five regression models were estimated to quantify the relationship between WPAI and predict presenteeism using health status. The models were specified based in index and domain scores and included covariates (age; gender). Estimated and observed presenteeism were compared using tenfold cross-validation and evaluated using Root mean square error (RMSE). Results A strong and negative correlation was found between WPAI and: EQ5D-5 level and WPAI (r = − 0.64); SF6D (r =− 0.60). Two models, using ordinary least squares regression were identified as the best performing models specifying health status using: SF6D domains with age interacted with gender (RMSE = 1.7858); EQ5D-5 Level domains and age interacted with gender (RMSE = 1.7859). Conclusions This study provides indicative evidence that two existing measures of health status (SF6D and EQ5D-5L) have a quantifiable relationship with a measure of presenteeism (WPAI) for an exemplar application of working individuals with RA. A future study should assess the external validity of the proposed mapping algorithms.

scholarly journals Evaluation of Inter-Observer Reliability of Animal Welfare Indicators: Which Is the Best Index to Use?

Animals ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 1445
Author(s):  
Mauro Giammarino ◽  
Silvana Mattiello ◽  
Monica Battini ◽  
Piero Quatto ◽  
Luca Maria Battaglini ◽  
...  
Keyword(s):  
Animal Welfare ◽  
Confidence Intervals ◽  
Bootstrap Method ◽  
Dairy Goat ◽  
Microsoft Excel ◽  
Bootstrap Methods ◽  
Welfare Indicators ◽  
Observer Reliability ◽  
High Concordance ◽  
Variance Estimates

This study focuses on the problem of assessing inter-observer reliability (IOR) in the case of dichotomous categorical animal-based welfare indicators and the presence of two observers. Based on observations obtained from Animal Welfare Indicators (AWIN) project surveys conducted on nine dairy goat farms, and using udder asymmetry as an indicator, we compared the performance of the most popular agreement indexes available in the literature: Scott’s π, Cohen’s k, kPABAK, Holsti’s H, Krippendorff’s α, Hubert’s Γ, Janson and Vegelius’ J, Bangdiwala’s B, Andrés and Marzo’s ∆, and Gwet’s γ(AC1). Confidence intervals were calculated using closed formulas of variance estimates for π, k, kPABAK, H, α, Γ, J, ∆, and γ(AC1), while the bootstrap and exact bootstrap methods were used for all the indexes. All the indexes and closed formulas of variance estimates were calculated using Microsoft Excel. The bootstrap method was performed with R software, while the exact bootstrap method was performed with SAS software. k, π, and α exhibited a paradoxical behavior, showing unacceptably low values even in the presence of very high concordance rates. B and γ(AC1) showed values very close to the concordance rate, independently of its value. Both bootstrap and exact bootstrap methods turned out to be simpler compared to the implementation of closed variance formulas and provided effective confidence intervals for all the considered indexes. The best approach for measuring IOR in these cases is the use of B or γ(AC1), with bootstrap or exact bootstrap methods for confidence interval calculation.

Multi-Method Vs Single Method Appraisal of Clinical Quality Indicators for the Emergency Medical Services

2020 ◽  
Author(s):  
Ian Howard ◽  
Peter Cameron ◽  
Maaret Castrén ◽  
Lee Wallis ◽  
Veronica Lindström
Keyword(s):  
Group Discussion ◽  
Rank Correlation ◽  
Healthcare Setting ◽  
Prehospital Emergency Care ◽  
Spearman’S Rank Correlation ◽  
Prehospital Emergency ◽  
Single Method ◽  
Multi Method Approach ◽  
The Individual ◽  
Method Approach

ABSTRACT Background Quality Indicator (QI) appraisal protocols are a novel methodology that combines multiple appraisal methods to comprehensively assess the "appropriateness" of QIs for a particular healthcare setting. However, they remain inadequately explored compared to the single appraisal method approach. This paper aimed to describe and test a QI appraisal protocol versus the single method approach, against a series of QIs potentially relevant to the South African Prehospital Emergency Care setting. Methods An appraisal protocol was developed consisting of two categorical-based appraisal methods, combined with the qualitative analysis of the discussion generated during the consensus application of each method. The output of the protocol was assessed and compared with the application and output of each method. Inter-rater reliability of each particular method was evaluated prior to group consensus rating. Variation in the number of non-valid QIs and the proportion of non-valid QIs identified between each method and the protocol were compared and assessed. Results There was mixed IRR of the individual methods. There was similarly low to moderate correlation of the results obtained between the particular methods (Spearman’s rank correlation=0.42,p&lt;0.001). From a series of 104 QIs, 11 non-valid QIs were identified that were shared between the individual methods. A further 19 non-valid QIs were identified and not shared by each method, highlighting the benefits of a multi-method approach. The outcomes were additionally evident in the group discussion analysis, which in and of itself added further input that would not have otherwise been captured by the individual methods alone. Conclusion The utilization of a multi-method appraisal protocol offers multiple benefits, when compared to the single appraisal approach, and can provide the confidence that the outcomes of the appraisal will ensure a strong foundation on which the QI framework can be successfully implemented.

scholarly journals Is HBA1C reliable in diagnosing diabetes in the acute phase of acute coronary syndromes?

2021 ◽  
Vol 10 (Supplement_1) ◽  
Author(s):  
M Stratinaki ◽  
K Milaki ◽  
S Stavrakis ◽  
M Pitarokoilis ◽  
E Charitakis ◽  
...  
Keyword(s):  
Acute Phase ◽  
Acute Coronary Syndromes ◽  
Rank Correlation ◽  
Mean Value ◽  
Gensini Score ◽  
Funding Sources ◽  
Spearman’S Rank Correlation ◽  
Coronary Syndromes ◽  
One Way Anova

Abstract Funding Acknowledgements Type of funding sources: None. Introduction Hospitalization due to acute coronary syndromes (ACS) usually is the occasion that leads to diagnosis of type 2 diabetes mellitus (T2DM). Current literature suggests that the severity of the ACS could be associated with the presence and the severity of DM. Purpose To study the reliability of HbA1c in the diagnosis of T2DM in the acute phase of ACS, as well as the presence of possible correlation between the HbA1c and the severity of ACS. Methods We evaluated 160 consecutive patients admitted due to ACS. HbA1c was measured on day 1 and day 90. HbA1c &gt;6.5% was used to diagnose T2DM and HbA1c 5.7-6.4% was used to diagnose pre-diabetes. The severity of ACS was assessed via Gensini score. Results are interpreted as mean ± SD. Comparisons were made by one way ANOVA(p &lt; 0.05 was regarded statistically significant).Spearman’s rank correlation was used to study the correlation between Gensini score and the other parameters. Results Mean age was 59.73 ± 12.21 years. 103/160(64.37%) were male and 57/160(35.63%) were female. 19/160(11.87%) were diagnosed as STEMI and 141/160(88.13%) as NSTEMI. Mean BMI was 29.55 ± 8.41 kg/m2 and mean Hb 12.62 ± 2.08 g/dl. On day 1, 43/160 (26.87%) had HbA1c &gt; 6.5% and 41/160(25.62%) HbA1c 5.7-6.4%. On day 90, 28/160 (17.5%) had HbA1c &gt; 6.5% and 52/160(32.5%) HbA1c 5.7-6.4%. Gensini score varied between 0-144 with mean value 40.26 ±35.9. A strong correlation was found between Gensini score and HbA1c on admission as well as on day 90 (rho-0.36, p &lt; 0.05 and rho = 0.32, p &lt; 0.05 respectively). Conclusion HbA1c seems to be reliable in the identification of pre-diabetes but not T2DM in the acute phase of ACS. The correlation of the severity between ACS and HbA1c seems to relate with the worst prognosis of T2DM patients.

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