A new likelihood approach to inference about predictive values of diagnostic tests in paired designs

2016 ◽  
Vol 27 (2) ◽  
pp. 541-548 ◽  
Author(s):  
Tsung-Shan Tsou
Keyword(s):  
Diagnostic Tests ◽  
Screening Test ◽  
Score Test ◽  
Real Data ◽  
Test Results ◽  
Multinomial Model ◽  
Test Statistic ◽  
Predictive Values ◽  
Minimum Number ◽  
Likelihood Approach

Intuitively, one only needs patients with two positive screening test results for positive predictive values comparison, and those with two negative screening test results for contrasting negative predictive values. Nevertheless, current existing methods rely on the multinomial model that includes superfluous parameters unnecessary for specific comparisons. This practice results in complex statistics formulas. We introduce a novel likelihood approach that fits the intuition by including a minimum number of parameters of interest in paired designs. It is demonstrated that our robust score test statistic is identical to a newly proposed weighted generalized score test statistic. Simulations and real data analysis are used for illustration.

Common risk difference test and interval estimation of risk difference for stratified bilateral correlated data

2018 ◽  
Vol 28 (8) ◽  
pp. 2418-2438
Author(s):  
Xi Shen ◽  
Chang-Xing Ma ◽  
Kam C Yuen ◽  
Guo-Liang Tian
Keyword(s):  
Data Analysis ◽  
Confidence Interval ◽  
Score Test ◽  
Real Data ◽  
Risk Difference ◽  
Error Rates ◽  
Correlated Data ◽  
Test Statistic ◽  
Data Set ◽  
Intra Class Correlation

Bilateral correlated data are often encountered in medical researches such as ophthalmologic (or otolaryngologic) studies, in which each unit contributes information from paired organs to the data analysis, and the measurements from such paired organs are generally highly correlated. Various statistical methods have been developed to tackle intra-class correlation on bilateral correlated data analysis. In practice, it is very important to adjust the effect of confounder on statistical inferences, since either ignoring the intra-class correlation or confounding effect may lead to biased results. In this article, we propose three approaches for testing common risk difference for stratified bilateral correlated data under the assumption of equal correlation. Five confidence intervals of common difference of two proportions are derived. The performance of the proposed test methods and confidence interval estimations is evaluated by Monte Carlo simulations. The simulation results show that the score test statistic outperforms other statistics in the sense that the former has robust type [Formula: see text] error rates with high powers. The score confidence interval induced from the score test statistic performs satisfactorily in terms of coverage probabilities with reasonable interval widths. A real data set from an otolaryngologic study is used to illustrate the proposed methodologies.

Clinical Epidemiology

2016 ◽  
pp. 285-290
Author(s):  
Scott C. Litin ◽  
John B. Bundrick
Keyword(s):  
Diagnostic Test ◽  
Diagnostic Tests ◽  
Clinical Decision Making ◽  
Clinical Epidemiology ◽  
Clinical Decision ◽  
Test Results ◽  
Specific Patient ◽  
Predictive Values ◽  
Test Sensitivity ◽  
Sensitivity Specificity

Diagnostic tests are tools that either increase or decrease the likelihood of disease. The sensitivity, specificity, and predictive values of normal and abnormal test results can be calculated with even a limited amount of information. Some physicians prefer interpreting diagnostic test results by using the likelihood ratio. This ratio takes properties of a diagnostic test (sensitivity and specificity) and makes them more helpful in clinical decision making. It helps the clinician determine the probability of disease in a specific patient after a diagnostic test has been performed.

A robust likelihood approach to inference about the kappa coefficient for correlated binary data

2018 ◽  
Vol 28 (4) ◽  
pp. 1188-1202 ◽  
Author(s):  
Tsung-Shan Tsou
Keyword(s):  
Data Analysis ◽  
Binary Data ◽  
Likelihood Function ◽  
Score Test ◽  
Real Data ◽  
Kappa Coefficient ◽  
Correlated Data ◽  
Ratio Test ◽  
Likelihood Approach ◽  
Robust Likelihood

We construct a legitimate likelihood function for the agreement kappa coefficient for correlated data without specifically modelling all levels of correlation. This makes available the likelihood ratio test, the score test and other tools without the knowledge of the underlying distributions. This parametric robust likelihood approach applies to general clustered data scenarios. We provide simulations and real data analysis to demonstrate the advantage of the robust procedure.

Comparing immunochromatography with latex antigen agglutination testing for the diagnosis of cryptococcosis in cats, dogs and koalas

2019 ◽  
Vol 58 (1) ◽  
pp. 39-46 ◽  
Author(s):  
Mark B Krockenberger ◽  
Caroline Marschner ◽  
Patricia Martin ◽  
George Reppas ◽  
Catriona Halliday ◽  
...  
Keyword(s):  
Gold Standard ◽  
Screening Test ◽  
Large Scale ◽  
Point Of Care ◽  
High Specificity ◽  
Agglutination Test ◽  
Test Results ◽  
Predictive Values ◽  
Cryptococcal Antigen ◽  
Rule Out

AbstractAlthough the point-of-care cryptococcal antigen lateral flow assay (LFA) has revolutionized the diagnosis of cryptococcosis in human patients, to date there has been no large-scale examination of this test in animals. We therefore assessed the LFA in cats, dogs and koalas suspected of having cryptococcosis. In sum, 528 serum specimens (129 from cats, 108 from dogs, 291 from koalas) were tested using the LFA and one of two commercially available latex cryptococcal antigen agglutination test (LCAT) kits. The LCAT is a proven and well-accepted method in veterinary patients and therefore taken as the “gold standard” against which the LFA was compared. The LFA achieved a sensitivity of 92%, 100%, and 98% in cats, dogs, and koalas, respectively, with corresponding negative predictive values of 94%, 100%, and 98%. The specificity of the LFA was 81%, 84%, and 62% for cats, dogs, and koalas, respectively, with corresponding positive predictive values of 76%, 48%, and 69%. These findings suggest the most appropriate role for the LFA is as a screening test to rule out a diagnosis of cryptococcosis in cats, dogs, and koalas. Point-of-care accessibility makes it equally suited for use in the field and as a cage-side test in veterinary hospitals. The suboptimal specificity of the LFA makes it less suited to definitive confirmation of cryptococcosis in animals; therefore, all LFA-positive test results should be confirmed by LCAT testing. The discrepancy between these observations and the high specificity of the LFA in humans may reflect differences in the host-pathogen interactions amongst the species.

The Interpretation of Test Results

2000 ◽  
Vol 4 (1) ◽  
pp. 19-25 ◽  
Author(s):  
Michael Binder ◽  
Stephan Dreiseitl
Keyword(s):  
Decision Making ◽  
Receiver Operating Characteristic ◽  
Diagnostic Tests ◽  
Operating Characteristic ◽  
Roc Curves ◽  
Test Results ◽  
Likelihood Ratios ◽  
Clinical Routine ◽  
Predictive Values ◽  
Sensitivity Specificity

Background: Dermatologists need to interpret an increasing number of research studies and diagnostic tests. Understanding the techniques for interpreting test results and making decisions based upon those tests represent important tools for decision making for both clinicians and researchers. Objective: This article focuses briefly on the key parameters of diagnostic tests: sensitivity, specificity, prevalence, predictive values, likelihood ratios, and the concept of receiver-operating-characteristic (ROC) curves. A simple example is presented in a step-by-step manner. Conclusion: The principles of interpreting test results are easy to learn and applicable in daily clinical routine. Therefore, dermatologists should be familiar with the concepts outlined in this paper.

scholarly journals Diagnostic testing: an emergency medicine perspective

CJEM ◽  
2002 ◽  
Vol 4 (05) ◽  
pp. 348-354 ◽  
Author(s):  
Andrew Worster ◽  
Grant Innes ◽  
Riyad B. Abu-Laban
Keyword(s):  
Diagnostic Tests ◽  
Diagnostic Testing ◽  
Test Results ◽  
Emergency Physicians ◽  
Likelihood Ratios ◽  
Predictive Values ◽  
The Core ◽  
Core Concepts ◽  
Sensitivity Specificity ◽  
Test Probability

ABSTRACT: Emergency physicians use diagnostic tests extensively, and the ability to order and interpret test results appropriately is a critical skill. An understanding of sensitivity, specificity, predictive values and likelihood ratios, as well as an awareness of the importance of pre-test probability, is essential. The purpose of this article is to explain, in a straightforward and clinically applicable manner, the core concepts related to diagnostic testing.

scholarly journals Is it enough for COVID-19 screening test? Limitation of swab test and general characteristics of mild symptom patients

2021 ◽  
Vol 104 (2) ◽  
pp. 003685042110261
Author(s):  
Sungwoo Choi ◽  
Hyo Jeong Choi ◽  
Ho Jung Kim
Keyword(s):  
Screening Test ◽  
Community Treatment ◽  
Upper Respiratory Tract ◽  
Test Results ◽  
Rt Pcr ◽  
Pcr Assay ◽  
Positive Rate ◽  
Upper Respiratory ◽  
Polymerase Chain ◽  
Discharge Criteria

The most common method for SARS-CoV-2 testing is throat or nasal swabbing by real-time reverse transcription polymerase chain reaction (RT-PCR) assay. In South Korea, drive-through swab test is used for screening system and community treatment centers (CTCs), which admit and treat confirmed COVID-19 patients with mild symptoms, are being used. This retrospective study was conducted on patients admitted to a CTC on March 6, 2020. A total of 313 patients were admitted. The nasal and throat swabs were collected from the upper respiratory tract, and a sputum test was performed to obtain lower respiratory samples. The positive rate of the first set of test, sputum test was higher than that of the swab test ( p = 0.011). In the second set of test, 1 week after the first ones, the rate of positive swab tests was relatively high ( p = 0.026). In the first set of test, 66 of 152 (43.4%) patients showed 24-h consecutive negative swab test results, when the sputum test results were considered together, that number fell to 29 patients (19.1%) ( p < 0.001). Also, in the second set of test, 63 of 164 (38.4%) patients met the discharge criteria only when the swab test was considered; that number fell to 30 (18.3%) when the sputum test results were also considered ( p < 0.001). Using the swab test alone is insufficient for screening test and discharge decision. Patients who may have positive result in the sputum test can be missed.

scholarly journals Insulin-like growth factor-1 level is a poor diagnostic indicator of growth hormone deficiency

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hideyuki Iwayama ◽  
Sachiko Kitagawa ◽  
Jyun Sada ◽  
Ryosuke Miyamoto ◽  
Tomohito Hayakawa ◽  
...  
Keyword(s):  
Growth Hormone ◽  
Growth Factor ◽  
Diagnostic Accuracy ◽  
Growth Hormone Deficiency ◽  
Screening Test ◽  
Characteristic Curve ◽  
Hormone Deficiency ◽  
Height Velocity ◽  
Insulin Like Growth Factor ◽  
Predictive Values

AbstractWe evaluated the diagnostic accuracy of insulin-like growth factor-1 (IGF-1) for screening growth hormone deficiency (GHD) to determine the usefulness of IGF-1 as a screening test. Among 298 consecutive children who had short stature or decreased height velocity, we measured IGF-1 levels and performed growth hormone (GH) secretion test using clonidine, arginine, and, in cases with different results of the two tests, L-dopa. Patients with congenital abnormalities were excluded. GHD was defined as peak GH ≤ 6.0 ng/mL in the two tests. We identified 60 and 238 patients with and without GHD, respectively. The mean IGF-1 standard deviation (SD) was not significantly different between the GHD and non-GHD groups (p = 0.23). Receiver operating characteristic curve analysis demonstrated the best diagnostic accuracy at an IGF-1 cutoff of − 1.493 SD, with 0.685 sensitivity, 0.417 specificity, 0.25 positive and 0.823 negative predictive values, and 0.517 area under the curve. Correlation analysis revealed that none of the items of patients’ characteristics increased the diagnostic power of IGF-1. IGF-1 level had poor diagnostic accuracy as a screening test for GHD. Therefore, IGF-1 should not be used alone for GHD screening. A predictive biomarker for GHD should be developed in the future.

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