scholarly journals Experience in developing graphical user interface to R programming language for clinical and experimental data analysis

2013 ◽  
Vol 94 (5) ◽  
pp. 677-681
Author(s):  
T I Dolgikh ◽  
D A Serbaev ◽  
G V Chekmarev ◽  
T V Kadcyna
Keyword(s):  
Data Analysis ◽  
Correlation Matrix ◽  
Rank Correlation ◽  
Health Indicators ◽  
Federal District ◽  
Epidemiological Studies ◽  
Medical Data ◽  
Spearman’S Rank Correlation ◽  
Box Plots ◽  
Presentation Methods

Aim. To develop the software product for of medical data analysis and public health indicators presentation. Methods. R_MED software - an interface for typical experimental, clinical and laboratory, epidemiologic analysis using the R system opportunities - was developed. Results. Functionally, the program consists of the following blocks: «Load Data», «Settings», «Basic calculations», «Data Mining», «Presentation of health indicators». Interface simplifying is also achieved by the inclusion of only those methods that are most often required in medical data analysis. So, the «Basic calculation» unit includes the following statistical calculations: descriptive statistics for quantitative variables, frequency tables, bar charts and box plots, Pearson’s correlation matrix, Pearson’s linear correlation, Spearman’s rank correlation, Spearman’s correlation matrix, 2D scatter plots, defining the difference in two independent sample groups using Student’s test and the Mann-Whitney test, analysis of variance (ANOVA). In the «Settings» unit, a user can choose a set of variables and observations for analysis, to change the set of features for any value, to add, delete, rename the variable, and optionally customize the «Load Data» mode, the basic calculation, and data output. The program provides the ability to visualize data using «Presentation of health indicators» block in the context of territory, year and variant. Territorial cuts can be differentiated into three levels: municipal, regional, district (Federal District) level. To construct the maps, vector data on all 3 spatial levels are stored in the R_MED system, including the Federal Districts of Russian Federation. Conclusion. Originally developed for research problems solving of pathology risk forecasting, the R_MED program, if configured properly, can also be used in other clinical diagnostic and epidemiological studies to monitor problems of socially significant diseases and of health services, as well as in the preparation of annual statistical reports, including the regional level.

scholarly journals Level of inequality and the role of governance indicators in the coverage of reproductive maternal and child healthcare services: Findings from India

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0258244
Author(s):  
Sumirtha Gandhi ◽  
Tulasi Malini Maharatha ◽  
Umakant Dash ◽  
Suresh Babu M.
Keyword(s):  
Correlation Matrix ◽  
Tamil Nadu ◽  
Rank Correlation ◽  
Family Health ◽  
Healthcare Services ◽  
Public Affairs ◽  
Relative Index ◽  
Spearman’S Rank Correlation ◽  
Governance Indicators ◽  
Index Of Inequality

Background Diligent monitoring of inequalities in the coverage of essential reproductive, maternal, new-born and child health related (RMNCH) services becomes imperative to smoothen the journey towards Sustainable Development Goals (SDGs). In this study, we aim to measure the magnitude of inequalities in the coverage of RMNCH services. We also made an attempt to divulge the relationship between the various themes of governance and RMNCH indices. Methods We used National Family Health Survey dataset (2015–16) and Public Affairs Index (PAI), 2016 for the analysis. Two summative indices, namely Composite Coverage Index (CCI) and Co-Coverage (Co-Cov) indicator were constructed to measure the RMNCH coverage. Slope Index of Inequality (SII) and Relative Index of Inequality (RII) were employed to measure inequality in the distribution of coverage of RMNCH. In addition, we have used Spearman’s rank correlation matrix to glean the association between governance indicator and coverage indices. Results & conclusions Our study indicates an erratic distribution in the coverage of CCI and Co-Cov across wealth quintiles and state groups. We found that the distribution of RII values for Punjab, Tamil Nadu, and West Bengal hovered around 1. Whereas, RII values for Haryana was 2.01 indicating maximum inequality across wealth quintiles. Furthermore, the essential interventions like adequate antenatal care services (ANC4) and skilled birth attendants (SBA) were the most inequitable interventions, while tetanus toxoid and Bacilli Calmette- Guerin (BCG) were least inequitable. The Spearman’s rank correlation matrix demonstrated a strong and positive correlation between governance indicators and coverage indices.

scholarly journals The Effect of Pre-Analytical Conditions on Blood Metabolomics in Epidemiological Studies

Metabolites ◽  
2019 ◽  
Vol 9 (4) ◽  
pp. 64 ◽  
Author(s):  
Diana Santos Ferreira ◽  
Hannah Maple ◽  
Matt Goodwin ◽  
Judith Brand ◽  
Vikki Yip ◽  
...  
Keyword(s):  
Rank Correlation ◽  
Correlation Coefficients ◽  
Epidemiological Studies ◽  
Processing Conditions ◽  
Linear Regression Models ◽  
Nmr Analysis ◽  
Serum Samples ◽  
Spearman’S Rank Correlation ◽  
Epidemiology Studies ◽  
The Impact

Serum and plasma are commonly used in metabolomic-epidemiology studies. Their metabolome is susceptible to differences in pre-analytical conditions and the impact of this is unclear. Participant-matched EDTA-plasma and serum samples were collected from 37 non-fasting volunteers and profiled using a targeted nuclear magnetic resonance (NMR) metabolomics platform (n = 151 traits). Correlations and differences in mean of metabolite concentrations were compared between reference (pre-storage: 4 °C, 1.5 h; post-storage: no buffer addition delay or NMR analysis delay) and four pre-storage blood processing conditions, where samples were incubated at (i) 4 °C, 24 h; (ii) 4 °C, 48 h; (iii) 21 °C, 24 h; and (iv) 21 °C, 48 h, before centrifugation; and two post-storage sample processing conditions in which samples thawed overnight (i) then left for 24 h before addition of sodium buffer followed by immediate NMR analysis; and (ii) addition of sodium buffer, then left for 24 h before NMR profiling. We used multilevel linear regression models and Spearman’s rank correlation coefficients to analyse the data. Most metabolic traits had high rank correlation and minimal differences in mean concentrations between samples subjected to reference and the different conditions tested, that may commonly occur in studies. However, glycolysis metabolites, histidine, acetate and diacylglycerol concentrations may be compromised and this could bias results in association/causal analyses.

scholarly journals VULNERABILITY OF WEATHER ON COVID-19 PANDEMIC IN WEST JAVA, INDONESIA

2020 ◽  
Vol 6 (4) ◽  
pp. 123-128
Author(s):  
Ramadhan Tosepu ◽  
Devi Savitri Effendy ◽  
La Ode Ali Imran Ahmad ◽  
Hariati Lestari ◽  
Hartati Bahar ◽  
...  
Keyword(s):  
Data Analysis ◽  
Wind Speed ◽  
Rank Correlation ◽  
Secondary Data ◽  
Weather Data ◽  
Maximum Temperature ◽  
Weather Factors ◽  
West Java ◽  
Spearman’S Rank Correlation ◽  
The Republic

Background: COVID-19 is a pandemic that spreads very fast. Until now, COVID-19 has spread in 207 countries.Objective: This study aimed to analyze the correlation between weather factors and COVID-19 in West Java, Indonesia. This study used a secondary data analysis of weather data from the Meteorological Department of the Republic of Indonesia and surveillance of COVID-19 from the Ministry of Health of the Republic of Indonesia. The weather has five components, including minimum temperature (0C), maximum temperature (0C), temperature average (0C), humidity (%), amount of rainfall (mm), and wind speed (m/s). Data were analyzed using Spearman’s rank correlation test.Result: Of the weather components, only temperature average (r = 0.545; p 0.001) and humidity (r = -0.500; p 0.001) significantly correlated with COVID-19.Conclusion: The results can be used to decrease the pandemic of COVID-19 in Indonesia.

scholarly journals Spectral statistics of large dimensional Spearman’s rank correlation matrix and its application

2015 ◽  
Vol 43 (6) ◽  
pp. 2588-2623 ◽  
Author(s):  
Zhigang Bao ◽  
Liang-Ching Lin ◽  
Guangming Pan ◽  
Wang Zhou
Keyword(s):  
Correlation Matrix ◽  
Rank Correlation ◽  
Spearman’S Rank Correlation ◽  
Spectral Statistics

scholarly journals Exploration of Ethnobotanical and Ethnomedicinal Importance of Naturally Growing Plants of District Neelum From Areas of Dawarian to Ratti Gali, Azad Jammu and Kashmir

2020 ◽  
Author(s):  
Muhammad Ajaib ◽  
ishtiaq muhammad ◽  
Mehwish Maqbool ◽  
Tanveer Hussain ◽  
Khizar Hayat Bhatti ◽  
...  
Keyword(s):  
Data Analysis ◽  
Research Work ◽  
Rank Correlation ◽  
Wild Plants ◽  
Ethnobotanical Study ◽  
Fidelity Level ◽  
Statistical Tools ◽  
Jammu And Kashmir ◽  
Spearman’S Rank Correlation ◽  
The World

Abstract Background: Ethnobotanical study was continued from old civilization to date. Kashmir covered with 46 % vagatation and out of these many are naturally growing plants. Many areas are still unexplored the plants ethnomedicinal inportanmce of wild plants. In this regard, ethnobotanical survey on the unexplored area of District Anthmaqam, Azad Jummu & Kashmir was conducted for identification of wild plants and their ethnomedical values. Methods: The current research work was carried out by interviewing the local peoples through a questionnaire method. Data analysis was done by different novel statistical tools such as fidelity level (FL), Spearman’s rank correlation (SRC), informant consensus factor (ICF) and direct matrix ranking (DMR) strategies. The ethnobotanical uses of many wild plants were correlated with the plants who already used by societies in some countries of the world. But few plants are used as medicines only indigenous peoples and we reccomented these plants for peoples in other parts of countery as well as throughout the world in future. Results: Peoples used plants in daily life as in form of vegetables, fodder, fuel, timber as well as for medicinal purposes. Indegeneous peoples are using many types of wild plants to cure different diseases like asthma, dysentery, constipation, cold, fever, joint pain, wound healing, kidney infection and many types of skin diseases. Current study revealed on 103 plants species belonging to 46 plant families from selected area of District Neelum, Azad Jammu and Kashmir. It was observed that Asteraceae with 12 plants species was the the most prominant family occurs in the study area. Out of 103 plants, 75.72% have single-usage, 20.38% have dual-usages and 3.88% have multiple-usage. Among plant partused, leaves having the highest percentage (34 %) that are used by people of the study area for the treatment of different diseases followed by the root 25.2%. Powdered is the dosage form having highest percentage 38% followed by juice and mixture with 29% and 13%, respectively. Some plants used as fodder having highest percentage 37% followed by Food (vegetables and fruits) with 32%. Construction having lowest percentage with 6%. Different statistical tools were applied for more consize results elaboration as mentioned in method section. Data analysis through FL depicted that Allium griffithianum and Adiantum aethiopicum have highest fidelity level of 75% followed by the Mentha longifolia with fedility level of about 72 %. The highest ICF value for recorded for ear-ache and house-thatching (0.91) followed by the construction (0.89) while the lowest ICF value recorded for fodder (0.03) followed by blood purification (0.5). Spearman’s rank correlation test confirmed that the number of uses of plants increases with the increase in the number of species. Conclusions: The present research focused to explore the uses of plants in different purposes by experience of old peoples in the study area. Ethnobotanical research focused to explore the uses of plants in different purposes by experience of old peoples in the study area. Young gereration of the area did not know ethnobotanical importance of wild plants in the area. So, this study will be useful those peoples and researchers in different fields such as ethnopharmacology, agriculture and biotechnology for future work.

scholarly journals Accuracy of self-reported waist and hip measurements in 4492 EPIC–Oxford participants

2004 ◽  
Vol 7 (6) ◽  
pp. 723-727 ◽  
Author(s):  
Elizabeth A Spencer ◽  
Andrew W Roddam ◽  
Timothy J Key
Keyword(s):  
Body Mass Index ◽  
Rank Correlation ◽  
Correlation Coefficients ◽  
Epidemiological Studies ◽  
Hip Circumference ◽  
Men And Women ◽  
Waist To Hip Ratio ◽  
Spearman’S Rank Correlation ◽  
Hip Measurements ◽  
Prospective Investigation

AbstractObjective:To assess the accuracy of self-reported waist and hip circumferences and the waist-to-hip ratio (WHR) by comparison with measured waist and hip circumferences and WHR in a sample of middle-aged men and women.Design:Analysis of measured and self-reported waist and hip data from participants in the Oxford cohort of the European Prospective Investigation into Cancer and Nutrition (EPIC–Oxford).Participants:Four thousand four hundred and ninety-two British men and women aged 35–76 years.Results:Spearman's rank correlation coefficients between measured and self-reported waist, hip and WHR were 0.80, 0.74 and 0.44, respectively, for men and 0.83, 0.86 and 0.62 for women. Waist was underestimated, on average, by 3.1 (standard deviation (SD) 5.6) cm in men and 1.9 (SD 5.4) cm in women. The extent of underestimation was greater in participants with larger waists, older participants and women with greater body mass index (BMI). Hip was underestimated by a mean of 1.8 (SD 4.9) cm in men and 1.2 (SD 4.5) cm in women; the extent of underestimation was greater in participants with larger hip circumference and older participants. On average, WHR was underestimated by less than 2% by men and women; the extent of underestimation was greater among those with larger WHR, older people and those with greater BMI. Using self-reported values, the proportion of classification to the correct tertile was over 65% for waist and hip measurements. For WHR this proportion was 50% among men and 60% among women.Conclusions:Self-reported waist and hip measurements in EPIC–Oxford are sufficiently accurate for identifying relationships in epidemiological studies.

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.

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