scholarly journals Improper Multivariate Receiver Operating Characteristic (iMROC) Curve

2020 ◽  
Vol 9 (2) ◽  
pp. 492-501
Author(s):  
S Balaswamy ◽  
R V. Vardhan ◽  
G Sameera
Keyword(s):  
Receiver Operating Characteristic ◽  
Likelihood Ratio ◽  
Operating Characteristic ◽  
Real Data ◽  
Data Sets ◽  
Correct Classification ◽  
Classification Techniques ◽  
Classification Technique ◽  
The Individual ◽  
Receiver Operating

In a multivariate setup, the classification techniques have its significance in identifying the exact status of the individual/observer along with accuracy of the test. One such classification technique is the Multivariate Receiver Operating Characteristic (MROC) Curve. This technique is well known to explain the extent of correct classification with the curve above the random classifier (guessing line) when it satisfies all of its properties especially the property of increasing likelihood ratio function. However, there are circumstances where the curve violates the above property. Such a curve is termed as improper curve. This paper demonstrates the methodology of improperness of the MROC Curve and ways of measuring it. The methodology is explained using real data sets.

scholarly journals Systematic Review with Meta-Analysis: Fecal Calprotectin as a Surrogate Marker for Predicting Relapse in Adults with Ulcerative Colitis

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Jiajia Li ◽  
Xiaojing Zhao ◽  
Xueting Li ◽  
Meijiao Lu ◽  
Hongjie Zhang
Keyword(s):  
Ulcerative Colitis ◽  
Receiver Operating Characteristic ◽  
Likelihood Ratio ◽  
Odds Ratio ◽  
Operating Characteristic ◽  
Diagnostic Odds Ratio ◽  
Fecal Calprotectin ◽  
Clinical Relapse ◽  
Sensitivity Specificity ◽  
Receiver Operating

The clinical course of ulcerative colitis (UC) is featured by remission and relapse, which remains unpredictable. Recent studies revealed that fecal calprotectin (FC) could predict clinical relapse for UC patients in remission, which has not yet been well accepted. To detect the predictive value of FC for clinical relapse in adult UC patients based on updated literature, we carried out a comprehensive electronic search of PubMed, Web of Science, Embase, and the Cochrane Library to identify all eligible studies. Diagnostic accuracy including pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and pooled area under the receiver operating characteristic (AUROC) was calculated using a random effects model. Heterogeneity across studies was assessed by the I2 metric. Sources of heterogeneity were detected using subgroup analysis. Metaregression was used to test potential factors correlated to DOR. Publication bias was assessed using Deek’s funnel plots. In our study, 14 articles enrolling a total of 1110 participants were finally included, and all articles underwent a quality assessment. Pooled sensitivity, specificity, PLR, and NLR with 95% confidence intervals (CIs) were 0.75 (95% CI: 0.70–0.79), 0.77 (95% CI: 0.74–0.80), 3.45 (95% CI: 2.31–5.14), and 0.37 (95% CI: 0.28–0.49) respectively. The area under the summary receiver operating characteristic (sROC) curve was 0.82, and the diagnostic odds ratio was 10.54 (95% CI: 6.16–18.02). Our study suggested that FC is useful in predicting clinical relapse for adult UC patients in remission as a simple and noninvasive marker.

scholarly journals Skor Prediksi Kematian Pneumonia pada Anak Usia di Bawah Lima Tahun

Sari Pediatri ◽  
2017 ◽  
Vol 18 (3) ◽  
pp. 214
Author(s):  
Ambarsari Latumahina ◽  
Rina Triasih ◽  
Kristia Hermawan
Keyword(s):  
Receiver Operating Characteristic ◽  
Likelihood Ratio ◽  
Operating Characteristic ◽  
Receiver Operating

Latar belakang. Pneumonia merupakan penyebab utama kematian pada anak usia di bawah lima tahun di negara berkembang. Pengembangan sistem skor yang sederhana untuk memprediksi kematian pada pneumonia dapat meningkatkan kualitas pelayanan dan menurunkan angka kematian anak akibat pneumonia.Tujuan. Menyusun skor prediksi kematian pada anak dengan pneumonia.Metode. Penelitian kohort retrospektif pada anak (umur 2 bulan sampai 5 tahun) yang dirawat di RSUP Dr. Sardjito dengan pneumonia sejak Januari 2009 sampai Desember 2014. Anak dengan rekam medis tidak lengkap atau dengan infeksi HIV dieksklusi. Digunakan metode Spiegelhalter Knill-Jones untuk penyusunan skor kematian. Prediktor kematian dengan likelihood ratio (LHR) ≤0,5 atau ≥2 dimasukkan dalam sistem skor. Cut off point dari skor total ditentukan dengan kurva receiver operating characteristic (ROC).Hasil. Di antara 225 anak yang memenuhi kriteria, 42 (18,7%) meninggal. Prediktor kematian yang memenuhi kriteria LHR adalah usia <6 bulan (LHR 2,05), takikardia (LHR 2,11), saturasi oksigen (SpO2) <92% (LHR 2,54), anemia (LHR 0,38) dan leukositosis (LHR 2,04). Skor prediksi kematian terdiri atas usia (skor=5 bila usia <6 bulan dan 0 bila >6 bulan); frekuensi nadi skor=6 bila takikardia dan -8 bila normal); saturasi oksigen (skor=3 bila SpO2 <92% dan 0 bila SpO2 >92%); hemoglobin (skor=4 bila anemia dan -6 bila normal), leukosit (skor=3 bila leukosit dan 0 bila normal). Total skor >3 Mempunyai sensitivitas dan spesifitas terbaik, yaitu 85,7% dan 72,1%.Kesimpulan. Skor prediksi kematian pneumonia >3 dapat digunakan untuk memprediksi kematian pada anak dengan pneumonia.

Diagnostic studies

2010 ◽  
pp. 339-351
Author(s):  
Janet L. Peacock ◽  
Philip J. Peacock
Keyword(s):  
Receiver Operating Characteristic ◽  
Likelihood Ratio ◽  
Sensitivity And Specificity ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Diagnostic Testing ◽  
Roc Curves ◽  
Clinical Situation ◽  
Post Test ◽  
Receiver Operating

Sensitivity and specificity 340 Calculations for sensitivity and specificity 342 Effect of prevalence 344 Likelihood ratio, pre-test odds, post-test odds 346 Receiver operating characteristic (ROC) curves 348 Links to other statistics 350 In this chapter we describe how statistical methods are used in diagnostic testing to obtain different measures of a test’s performance. We describe how to calculate sensitivity, specificity, and positive and negative predictive values, and show the relevance of pre- and post-test odds and likelihood ratio in evaluating a test in a clinical situation. We also describe the receiver operating characteristic curve and show how this links with logistic regression analysis. All methods are illustrated with examples....

scholarly journals A Statistical Comparison of the Blossom Blight Forecasts of MARYBLYT and Cougarblight with Receiver Operating Characteristic Curve Analysis

2007 ◽  
Vol 97 (9) ◽  
pp. 1164-1176 ◽  
Author(s):  
M. M. Dewdney ◽  
A. R. Biggs ◽  
W. W. Turechek
Keyword(s):  
Receiver Operating Characteristic ◽  
Roc Curve ◽  
Fire Blight ◽  
Operating Characteristic ◽  
Curve Analysis ◽  
Data Sets ◽  
Risk Threshold ◽  
Geographic Regions ◽  
Pairwise Contrasts ◽  
Receiver Operating

Blossom blight forecasting is an important aspect of fire blight, caused by Erwinia amylovora, management for both apple and pear. A comparison of the forecast accuracy of two common fire blight forecasters, MARYBLYT and Cougarblight, was performed with receiver operating characteristic (ROC) curve analysis and 243 data sets. The rain threshold of Cougarblight was analyzed as a separate model termed Cougarblight and rain. Data were used as a whole and then grouped into geographic regions and cultivar susceptibilities. Frequency distributions of cases and controls, orchards or regions (depending on the data set), with and without observed disease, respectively, in all data sets overlapped. MARYBLYT, Cougarblight, and Cougarblight and rain all predicted blossom blight infection better than chance (P = 0.05). It was found that the blossom blight forecasters performed equivalently in the geographic regions of the east and west coasts of North America and moderately susceptible cultivars based on the 95% confidence intervals and pairwise contrasts of the area under the ROC curve. Significant differences (P < 0.05) between the forecasts of Cougarblight and MARYBLYT were found with pairwise contrasts in the England and very susceptible cultivar data sets. Youden's index was used to determine the optimal cutpoint of both forecasters. The greatest sensitivity and specificity for MARYBLYT coincided with the use of the highest risk threshold for predictions of infection; with Cougarblight, there was no clear single risk threshold across all data sets.

scholarly journals “Emergency Room Evaluation and Recommendations” (ER2) Tool for the Screening of Older Emergency Department Visitors With Major Neurocognitive Disorders: Results From the ER2 Database

2022 ◽  
Vol 12 ◽  
Author(s):  
Olivier Beauchet ◽  
Liam A. Cooper-Brown ◽  
Joshua Lubov ◽  
Gilles Allali ◽  
Marc Afilalo ◽  
...  
Keyword(s):  
Emergency Department ◽  
High Risk ◽  
Emergency Room ◽  
Receiver Operating Characteristic ◽  
Likelihood Ratio ◽  
Predictive Value ◽  
Operating Characteristic ◽  
Neurocognitive Disorders ◽  
Risk Level ◽  
Receiver Operating

Purpose: The Emergency Room Evaluation and Recommendation (ER2) is an application in the electronic medical file of patients visiting the Emergency Department (ED) of the Jewish General Hospital (JGH; Montreal, Quebec, Canada). It screens for older ED visitors at high risk of undesirable events. The aim of this study is to examine the performance criteria (i.e., sensitivity, specificity, positive predictive value [PPV], negative predictive value [NPV], positive likelihood ratio [LR+], negative likelihood ratio [LR-] and area under the receiver operating characteristic curve [AUROC]) of the ER2 high-risk level and its “temporal disorientation” item alone to screen for major neurocognitive disorders in older ED visitors at the JGH.Methods: Based on a cross-sectional design, 999 older adults (age 84.9 ± 5.6, 65.1% female) visiting the ED of the JGH were selected from the ER2 database. ER2 was completed upon the patients' arrival at the ED. The outcomes were ER2's high-risk level, the answer to ER2's temporal disorientation item (present vs. absent), and the diagnosis of major neurocognitive disorders (yes vs. no) which was confirmed when it was present in a letter or other files signed by a physician.Results: The sensitivities of both ER2's high-risk level and temporal disorientation item were high (≥0.91). Specificity, the PPV, LR+, and AROC were higher for the temporal disorientation item compared to ER2's high-risk level, whereas a highest sensitivity, LR-, and NPV were obtained with the ER2 high-risk level. Both area under the receiver operating characteristic curves were high (0.71 for ER2's high-risk level and 0.82 for ER2 temporal disorientation item). The odds ratios (OR) of ER2's high-risk level and of temporal disorientation item for the diagnosis of major neurocognitive disorders were positive and significant with all OR above 18, the highest OR being reported for the temporal disorientation item in the unadjusted model [OR = 26.4 with 95% confidence interval (CI) = 17.7–39.3].Conclusion: Our results suggest that ER2 and especially its temporal disorientation item may be used to screen for major neurocognitive disorders in older ED users.

scholarly journals Dual Tasking With the Timed “Up & Go” Test Improves Detection of Risk of Falls in People With Parkinson Disease

2015 ◽  
Vol 95 (1) ◽  
pp. 95-102 ◽  
Author(s):  
Roisin C. Vance ◽  
Dan G. Healy ◽  
Rose Galvin ◽  
Helen P. French
Keyword(s):  
Parkinson Disease ◽  
Receiver Operating Characteristic ◽  
Likelihood Ratio ◽  
Sensitivity And Specificity ◽  
Fall Risk ◽  
Operating Characteristic ◽  
Risk Of Falling ◽  
Discriminative Performance ◽  
Study Objective ◽  
Receiver Operating

BackgroundFalls are a common and disabling feature of Parkinson disease (PD). Early identification of patients at greatest risk of falling is a key goal of physical therapy assessment. The Timed “Up & Go” Test (TUG), a frequently used mobility assessment tool, has moderate sensitivity and specificity for identifying fall risk.ObjectiveThe study objective was to investigate whether adding a task (cognitive or manual) to the TUG (TUG-cognitive or TUG-manual, respectively) increases the utility of the test for identifying fall risk in people with PD.DesignThis was a retrospective cohort study of people with PD (N=36).MethodsParticipants were compared on the basis of self-reported fall exposure in the preceding 6 months (those who had experienced falls [“fallers”] versus those who had not [“nonfallers”]). The time taken to complete the TUG, TUG-cognitive, and TUG-manual was measured for both groups. Between-group differences were calculated with the Mann-Whitney U test. The discriminative performance of the test at various cutoff values was examined, and estimates of sensitivity and specificity were based on receiver operating characteristic curve plots.ResultsFallers took significantly longer than nonfallers (n=19) to complete the TUG under all 3 conditions. The TUG-cognitive showed optimal discriminative performance (receiver operating characteristic area under the curve=0.82; 95% confidence interval [CI]=0.64, 0.92) at a cutoff of 14.7 seconds. The TUG-cognitive was more likely to correctly classify participants with a low risk of falling (positive likelihood ratio=2.9) (&lt;14.7 seconds) and had higher estimates of sensitivity (0.76; 95% CI=0.52, 0.90) than of specificity (0.73; 95% CI=0.51, 0.88) at this threshold (negative likelihood ratio=0.32).LimitationsRetrospective classification of fallers and nonfallers was used.ConclusionsThe addition of a cognitive task to the TUG enhanced the identification of fall risk in people with PD. The TUG-cognitive should be considered a component of a multifaceted fall risk assessment in people with PD.

scholarly journals The Diagnostic Accuracy of Direct Agglutination Test for Serodiagnosis of Human Visceral Leishmaniasis: A Systematic Review with Meta-analysis

2020 ◽  
Author(s):  
Mehdi Mohebali ◽  
Hossein Keshavarz ◽  
Sedigheh Shirmohammad ◽  
Behnaz Akhoundi ◽  
Alireza Borjian ◽  
...  
Keyword(s):  
Systematic Review ◽  
Visceral Leishmaniasis ◽  
Diagnostic Accuracy ◽  
Receiver Operating Characteristic ◽  
Likelihood Ratio ◽  
Operating Characteristic ◽  
Meta Analysis ◽  
Agglutination Test ◽  
Summary Receiver Operating Characteristic ◽  
Receiver Operating

Abstract Background: agglutination test (DAT) as simple, accurate and non-expensive tool that has been used widely for serodiagnosis of visceral leishmaniasis (VL) during the last three decades. We conducted a systematic review and meta-analysis to evaluate the diagnostic accuracy of DAT for serodiagnosis of human VL.Methods: Electronic databases, including MEDLINE (via PubMed), SCOPUS, Web of Science, SID and Mag Iran (two Persian scientific search engines) were searched from December 2004 to April 2019.The study quality was evaluated using the QUADAS checklist. We determined the sensitivities and specificities across studies, calculated positive and negative likelihood ratios (LR+ and LR-), and constructed summary receiver operating characteristic(ROC) curves parameters.Results: Of the 2928 records identified in the mentioned electronic databases and through articles’ reference lists, 25 articles met inclusion criteria and enrolled into the systematic review and among them 22 records were qualified for meta-analysis. The pooled sensitivity and specificity of DAT was 96% [(95% CI, 93–98] )and 95% [(95 % CI, 88–98]), respectively. The likelihood ratio of a positive test (LR+) was found to be 19.8 [CI95%, 7.6–51.8] and the likelihood ratio of a negative test (LR−) was found to be 0.04 [CI95%, 0.02–0.08]. The combined estimate of the diagnostic odds ratio for DAT was high [454 )136-1561]) ].We found that the summary receiver operating characteristic curve (SROC) is positioned near the upper left corner of the curve and the area under curve (AUC) was 0.98 (95% CI, 0.97 to 0.99).Conclusion: Based on our analysis, we find DAT can be considered as valuable tool for the serodiagnosis and seroprevalence of human VL with high sensitivity and specificityrates. As DAT is simple, accurate ,non-invasive and efficient serological test, it can be used for serodiagnosis of human VL particularly in endemic areas of the disease.

scholarly journals Sistem Pengambilan Keputusan dalam Penentuan Kelas Jabatan Fungsional Umum (JFU) Pegawai Negeri Sipil (PNS) Menggunakan Metode Multi Rough Set dan Fuzzifikasi

2019 ◽  
Vol 6 (1) ◽  
pp. 63
Author(s):  
Asri Yulianti
Keyword(s):  
Receiver Operating Characteristic ◽  
Rough Set ◽  
Operating Characteristic ◽  
Area Under The Curve ◽  
Civil Servant ◽  
Civil Servants ◽  
Average Error ◽  
Data Sets ◽  
Data Set ◽  
Receiver Operating

<p class="Abstrak">Seorang Pegawai Negeri Sipil (PNS) pada instansi pemerintah, dituntut harus memiliki kompetensi atau kemampuan untuk dapat melakukan pekerjaan secara efektif dan efisien sesuai dengan bidang dan lingkup pekerjaannya. Pada kenyataannya, proses penentuan kompetensi dan kelas jabatan sangat berpengaruh bagi proses penempatan Jejabat Fungsional Umum (JFU) seorang Pegawai Negeri Sipil dan <span lang="EN-US">karena proses </span>tersebut<span lang="EN-US"> selama ini</span>masih dilakukan secara manual, <span lang="EN-US">maka</span> waktu yang<span lang="EN-US"> dibutuhkan</span> cukup lama dan hasil yang diperoleh belum tentu akurat sesuai dengan kompetensi yang dimiliki. Pada penelitian ini, Metode <em>Multi Rough Set</em> digunakan dalam penentuan klasifikasi kompetensi dan kelas jabatan bagi PNS yang belum diketahui kompetensinya maupun sebagai bahan evaluasi kinerja pegawai yang telah menduduki suatu jabatan. Metode <em>Multi Rough Set</em>  ini dilakukan dengan cara membagi data set menjadi beberapa data set dengan atribut yang sejenis. Berdasarkan penelitian yang telah dilakukan, <span lang="EN-US">dapat </span>diketahui bahwa <span lang="EN-US">Metode Multi Rough Set sebagai metode klasifikasi yang baik (<em>Good Classifier</em>) dalam pengambilan keputusan klasifikasi kompetensi pegawai dalam Jabatan Fungsional Umum, karena berdasarkan hasil kurva pada <em>Receiver Operating Characteristic</em> (ROC) mempunyai luas daerah di bawah kurva sebesar <strong>0,866</strong>, selain itu rata-rata error dari </span>hasil klasifikasi dengan Metode Multi Rough Set <span lang="EN-US">yang </span>digabungkan dengan pengambilan keputusan melalui fuzzifikasi meningkat secara signifikan dibandingkan dengan Metode <em>Single Rough Set</em> yaitu dari <strong><span lang="EN-US">28,75%</span></strong> menjadi <strong><span lang="EN-US">0</span></strong><strong>%</strong><span lang="EN-US"> untuk hasil yang tidak terklasifikasi.</span></p><p class="Abstrak"><em><strong><span lang="EN-US">Abstract</span></strong></em></p><p class="Judul21"><em>A Civil Servant in government agencies is required to have the competency or ability to be able to perform work effectively and efficiently in accordance with the field and scope of work. In fact, the process of determining the competency and class of works is very influential for the process of placement of General Functional Works of a Civil Servant. However, the process takes a long time because it is still done manually.  Moreover, the obtained results are not necessarily accurate in accordance with the competence which is owned by the civil servants. In this study, Multi Rough Set Method is used for determining unknown civil servants competency classification and class position, or as civil servants performance evaluation. The multi Rough Set method is applied by dividing the data set into several similar attributes data sets.</em><em> Based on the research that has been conducted, it can be seen that the Multi Rough Set Method is a good classifier method in decision making of employee competency classification in General Functional Work. It is because based on the Receiver Operating Characteristic (ROC) curve results, the area under the curve reaches 0.866. Besides, the average error from the results of the classification using the combination of Multi Rough Set Method and fuzzification increased significantly compared to the Single Rough Set Method which goes from 28.75% to 0% for unclassified results.</em></p><p class="Abstrak"><strong><span lang="EN-US"><br /></span></strong></p>

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