Using Adjacent-category Logits Procedure for Estimating Receiver Operating Characteristic Surface

This article presents a semiparametric method for estimating receiver operating characteristic surface under density ratio model. The construction of the proposed method is based on the adjacent-category logit model and the empirical likelihood approach. A bootstrap approach for the VUS estimator inference is presented. In a simulation study, the proposed estimator is compared with the existing parametric and nonparametric estimators in terms of bias, standard error, and mean square error. Finally, a real data example and some discussions on the proposed method are provided.     

Combining ROC curves using MAMSE weighted distributions

The receiver operating characteristic (ROC) curve can be used to evaluate the properties of a diagnostic test from the distribution of a variable on the healthy and diseased populations. The minimum averaged mean squared error (MAMSE) weights were developed to handle data from different sources by adjusting the relative contribution of each data source. The authors use the MAMSE weights to infer the ROC curve of a diagnostic test based on raw data from multiple studies. The proposed estimates are consistent and Monte Carlo simulations show favourable finite sample performance. The method is illustrated in a case study where progesterone level is used to detect ectopic pregnancies and abortions from other natural causes. The Canadian Journal of Statistics 46: 298–315; 2018 © 2018 Statistical Society of Canada     

On the three-way equivalence of AUC in credit scoring with tied scores

In credit scoring, it is well known that AUC (the area under curve) can be calculated geometrically, by the probability of a correct ranking of a good and bad pair, and by the Wilcoxon Rank-Sum statistic. This three-way equivalence was first present by Hanley and McNeil in 1982 without considering tied scores and without giving analytical proofs. In this paper, we extend the three-way equivalence to the case with tied scores and provide analytic proofs for the three-way equivalence.     

Validity and diagnostic accuracy of a measure of parental stress in parents with typically developing children

The Parental Stress and Coping Inventory (PSCI), a 5-point, 18-item questionnaire was evaluated and validated as a screening measure for parental stress in the current sample of 126 mostly low income and ethnic minority parents with typically developing children. One hundred twenty-six participants contributed data to the current receiver-operating characteristics (ROC) analysis. ROC analyses were conducted to determine the cutoff scores of PSCI parental distress, social support, and family-based support measures. We found an optimal parental distress cutoff point of 14.5 with an associated sensitivity of 73% and 82% specificity. The optimal cutoff point of social support measure was 23.5 associated with 76% sensitivity and 49% specificity. And, the optimal cutoff point of family-based support measure was 13.5 associated with 79% sensitivity and 56% specificity. This study not only provided evidence for the reliability and validity of PSCI, but also proved the inventory to be a simple, sensitive, and specific battery for screening for parental stress and coping.     

An extension of parametric ROC analysis for calculating diagnostic accuracy when underlying distributions are mixture of Gaussian

The semiparametric LABROC approach of fitting binormal model for estimating AUC as a global index of accuracy has been justified (except for bimodal forms), while for estimating a local index of accuracy such as TPF, it may lead to a bias in severe departure of data from binormality. We extended parametric ROC analysis for quantitative data when one or both pair members are mixture of Gaussian (MG) in particular for bimodal forms. We analytically showed that AUC and TPF are a mixture of weighting parameters of different components of AUCs and TPFs of a mixture of underlying distributions. In a simulation study of six configurations of MG distributions:{bimodal, normal} and {bimodal, bimodal} pairs, the parameters of MG distributions were estimated using the EM algorithm. The results showed that the estimated AUC from our proposed model was essentially unbiased, and that the bias in the estimated TPF at a clinically relevant range of FPF was roughly 0.01 for a sample size of n=100/100. In practice, with severe departures from binormality, we recommend an extension of the LABROC and software development for future research to allow for each member of the pair of distributions to be a mixture of Gaussian that is a more flexible parametric form.     

Exact confidence interval estimation for the difference in diagnostic accuracy with three ordinal diagnostic groups

In the cases with three ordinal diagnostic groups, the important measures of diagnostic accuracy are the volume under surface (VUS) and the partial volume under surface (PVUS) which are the extended forms of the area under curve (AUC) and the partial area under curve (PAUC). This article addresses confidence interval estimation of the difference in paired VUS s and the difference in paired PVUS s. To focus especially on studies with small to moderate sample sizes, we propose an approach based on the concepts of generalized inference. A Monte Carlo study demonstrates that the proposed approach generally can provide confidence intervals with reasonable coverage probabilities even at small sample sizes. The proposed approach is compared to a parametric bootstrap approach and a large sample approach through simulation. Finally, the proposed approach is illustrated via an application to a data set of blood test results of anemia patients.     

Optimal nonparametric estimator of the area under ROC curve based on clustered data

Abstract

In diagnostic trials, clustered data are obtained when several subunits of the same patient are observed. Intracluster correlations need to be taken into account when analyzing such clustered data. A nonparametric method has been proposed by Obuchowski (1997 Obuchowski, N. A. 1997. Nonparametric analysis of clustered ROC curve data. Biometrics 53 (2):567–78.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]) to estimate the Receiver Operating Characteristic curve area (AUC) for such clustered data. However, Obuchowski’s estimator is not efficient as it gives equal weight to all pairwise rankings within and between cluster. In this paper, we propose a more efficient nonparametric AUC estimator with two sets of optimal weights. Simulation results show that the loss of efficiency of Obuchowski’s estimator for a single AUC or the AUC difference can be substantial when there is a moderate intracluster test correlation and the cluster size is large. The efficiency gain of our weighted AUC estimator for a single AUC or the AUC difference is further illustrated using the data from a study of screening tests for neonatal hearing.     

CONFIDENCE INTERVALS FOR THE DIFFERENCE BETWEEN TWO PARTIAL AUCS

As new diagnostic tests are developed and marketed, it is very important to be able to compare the accuracy of a given two continuous‐scale diagnostic tests. An effective method to evaluate the difference between the diagnostic accuracy of two tests is to compare partial areas under the receiver operating characteristic curves (AUCs). In this paper, we review existing parametric methods. Then, we propose a new semiparametric method and a new nonparametric method to investigate the difference between two partial AUCs. For the difference between two partial AUCs under each method, we derive a normal approximation, define an empirical log‐likelihood ratio, and show that the empirical log‐likelihood ratio follows a scaled chi‐square distribution. We construct five confidence intervals for the difference based on normal approximation, bootstrap, and empirical likelihood methods. Finally, extensive simulation studies are conducted to compare the finite‐sample performances of these intervals, and a real example is used as an application of our recommended intervals. The simulation results indicate that the proposed hybrid bootstrap and empirical likelihood intervals outperform other existing intervals in most cases.     

于畅谈风月之中，寓谐铎谲谏之意——“退中有进”的民初小说理论

小说理论、小说观念的调整是造成民初小说创作面貌迥异于清末的重要因素。表面上看,这一调整似乎只是传统小说观念的回潮,但它以世俗化、趣味化来调解清末小说的政治化、功利化,实则是走向世俗艺术的一种进步,也是中国小说观念的现代变革中不可或缺的一环。     

试析民初小学国文教材德育培养的异同 ——以《新制中华国文教科书》和《中华女子国文教科书》为例

在民初的高等小学教学体系中,道德修养的培育无疑是重中之重,在“修身”被单独列为一门单独的课程以供德育学习的 同时,这一阶段的国文学科的课本中也有大量的篇幅关于德育培养。依据这一时期最具代表性的两套教材,即《新制中华国文 教科书》与《中华女子国文教科书》（后文分别简称为《新制》《女子》）,立足文本选材及作者情感态度价值观等方面,探寻寓于其 中的德育培养的异同之处。