In this chapter we continue the discussion of diagnostic testing by considering instruments that are based on continuous outcomes. We also introduce additional diagnostic information in the form of covariates and additional tests. Our primary goal is to generalize the notion of PVP and PVN to a predictive probability of infection/disease conditional on all available diagnostic information. In a...

Mental arithmetic is a powerful paradigm to study problem solving using neuroimaging methods. However, the evaluation of task complexity varies significantly across neuroimaging studies. Most studies have parameterized task complexity by objective features such as the number size. Only a few studies used subjective rating procedures. In fMRI, we provided evidence that strategy self-reports cont...

[Purpose] The purpose of this study was to establish the reliability and validity of the Foot Function Index translated into Korean for use in patients with plantar fasciitis and foot/ankle fracture. [Subjects and Methods] Thirty-six subjects with foot complaints, 14 males and 22 females, participated in the study. Reliability was determined by using the intra-class correlation coefficient and ...

OBJECTIVE The aim of this methodological study is to establish the validity and reliability of the Turkish version of "A Questionnaire for Measuring Attitudes toward Cancer (Cancer Stigma) - Patient version." METHODS The sample comprised oncology patients who had active cancer treatment. The construct validity was assessed using the confirmatory and exploratory factor analysis. RESULTS The ...

Developing novel nuclear cardiology approaches requires evaluating their diagnostic ability. Statistical measures such as sensitivity, specificity, receiver operating characteristic (ROC) curve, and area under the curve (AUC) are useful to evaluate the diagnostic value of novel imaging parameters. This paper reviews key statistical methods used in the evaluation of diagnostic tests and highligh...

The following picture shows the test omission rate and predicted area as a function of the cumulative threshold, averaged over the replicate runs. The omission rate should be close to the predicted omission, because of the definition of the cumulative threshold. The next picture is the receiver operating characteristic (ROC) curve for the same data, again averaged over the replicate runs. Note ...

support vector machines (SVMs) constitute one of the most popular and powerful classification methods. However, SVMs can be limited in their performance on highly imbalanced datasets. A classifier which has been trained on an imbalanced dataset can produce a biased model towards the majority class and result in high misclassification rate for minority class. For many applications, especially fo...

Receiver Operating Characteristic (ROC) analysis is a widely used method for analyzing the performance of two-class classifiers. Advantages of ROC analysis include the fact that it explicitly considers the tradeoffs in sensitivity and specificity, includes visualization methods, and has clearly interpretable summary metrics. Currently, there does not exist a widely accepted performance method s...