V. A. Sadovnichii, Ya. T. Sultanaev and A. M. Akhtyamov
Trans. Moscow Math. Soc. 80 (2020), 123-131.
Abstract, references and article information

S. A. Nazarov
Trans. Moscow Math. Soc. 80 (2020), 1-51.
Abstract, references and article information

A. Knightly and C. Li
Memoirs of the AMS 224 (2012).
Abstract, references and article information

Nivedita Bhaskhar and Bastian Haase
Trans. Amer. Math. Soc. 373 (2020), 3709-3732.
Abstract, references and article information

Cătălin I. Cârstea, Gen Nakamura and Lauri Oksanen
Trans. Amer. Math. Soc. 373 (2020), 3423-3443.
Abstract, references and article information

M. V. Pratsiovytyi and S. P. Ratushniak
Theor. Probability and Math. Statist. 99 (2020), 211-228.
Abstract, references and article information

Yu. S. Mishura and H. S. Zhelezniak
Theor. Probability and Math. Statist. 99 (2020), 199-210.
Abstract, references and article information

Yingxiang Hu and Shicheng Xu
Proc. Amer. Math. Soc. 148 (2020), 2609-2615.
Abstract, references and article information

The SAS Universal Viewer displays null values appropriately as blanks for XPT files. However, when you select Table ? Save As and save an XPT file as either an XML or CSV file, the SAS Universal Viewer con

Purpose: To explore the value of ⁶⁸Ga-PSMA-PET/CT for detection of phosphatase and tensin homolog (PTEN) - loss prostate cancer (PCa). Methods: We retrospectively enrolled 75 patients who underwent multiparametric MRI (mpMRI) and ⁶⁸Ga-PSMA PET/CT before radical prostatectomy. Lesions were outlined on pathological images and regions of interest were drawn on matched mpMRI and PET/CT images. Imaging parameters including average apparent diffusion coefficient (ADCmean) and maximum standardized uptake value (SUV_max) were derived. Immunohistochemical staining was carried out to evaluate the PTEN status. The diagnostic performance of imaging parameters was analyzed by receiver operating characteristics (ROC) analysis. A univariate logistic regression analyses were used to evaluate the association between clinical and imaging variables and PTEN status. Results: Totally, 103 lesions from 54 patients were analyzed. Of these lesions, 34 of 103 (33.0%) showed PTEN-loss status. Our study showed a strong association between SUV_max and PTEN-loss tumors both in the per-patient analysis (P < 0.01) and per-lesion analysis (P < 0.01), yielding the sensitivity and specificity of 0.80 and 0.77 in the per-patient analysis and 0.83 and 0.74 in the per-lesion analysis. Meanwhile, higher pathological PSMA expression was found in the PTEN-deficiency tumors. However, there was no significant difference between PTEN-loss tumors and PTEN-intact tumors using parameters including ADCmean (P > 0.05) and PI-RADS score (P > 0.05). Surprisingly, SUV_max was a significant predictor for detection of PTEN-loss tumors (odds ratio: 7.56, 95% confidence interval: 2.18-26.24, per-patient analysis; odds ratio: 13.66, 95% confidence interval: 4.32-43.24, per-lesion analysis). Conclusion: ⁶⁸Ga-PSMA-PET/CT could effectively detect aggressive PTEN-loss tumors.

The objective of this retrospective study was to determine the role of ¹⁸F-FDG PET/CT in a large cohort of 495 patients with metastatic neuroendocrine neoplasms (NENs) who were treated with peptide receptor radionuclide therapy (PRRT) with a long-term follow-up. Methods: The 495 patients were treated with ¹⁷⁷Lu- and/or ⁹⁰Y- DOTATOC/DOTATATE PRRT between 2/2002 and 7/2018. All subjects received both ⁶⁸Ga-DOTATOC/TATE/NOC and ¹⁸F-FDG PET/CT prior to treatment and were followed 3-189 months. Kaplan-Meier analysis, log-rank test (Mantel-Cox), and Cox regression analysis were performed for overall survival (OS) and progression-free survival (PFS). Results: 199 patients (40.2%) presented with pancreatic NEN, 49 with CUP (cancer of unknown primary), 139 with midgut NEN, whereas the primary tumor was present in the rectum in 20, in the lung in 38, in the stomach in 8 and other locations in 42 patients. FDG-PET/CT was positive in 382 (77.2%) patients and 113 (22.8%) were FDG-negative before PRRT, while 100% were ⁶⁸Ga-DOTATOC/TATE/NOC positive. For all patients, the median PFS and OS, defined from start of PRRT, were 19.6 mo and 58.7 mo, respectively. Positive FDG predicted shorter PFS (18.5 mo vs 24.1 mo; P = 0.0015) and OS (53.2 mo vs 83.1 mo; P < 0.001) than negative FDG. Amongst the pancreatic NEN, the median OS was 52.8 mo in FDG positive and 114.3 mo in FDG negative subjects (P = 0.0006). For all patients with positive ¹⁸F-FDG uptake, and a ratio of the highest SUV_max on ⁶⁸Ga-SSTR PET to the most ¹⁸F-FDG-avid tumor lesions >2, the median OS was 53.0 mo, compared to 43.4 mo in those patients with a ratio <2 (P = 0.030). For patients with no ¹⁸F-FDG uptake (complete "mismatch" imaging pattern), the median OS was 108.3 mo vs 76.9 mo for SUV_max >15.0 and ≤15.0 on ⁶⁸Ga-SSTR PET/CT, respectively. Conclusion: The presence of positive lesions on ¹⁸F-FDG PET is an independent prognostic factor in patients with NEN treated with PRRT. Metabolic imaging with ¹⁸F-FDG PET/CT compliments the molecular imaging aspect of ⁶⁸Ga-SSTR PET/CT for the prognosis of survival after PRRT. High SSTR expression combined with negative ¹⁸F-FDG PET/CT imaging is associated with the most favorable long-term prognosis.

Large numeric values consisting of 16 digits in SAS might be incorrect when written to Hadoop for columns defined with the BIGINT data type.  This problem was introduced in SAS 9

A DATA step and PROC SQL can round numeric values while creating and loading data into a new Databricks table via JDBC.

Sean Newcomb entered last June as an All-Star candidate and exited the regular season wondering if he had done enough to earn a spot on Atlanta's postseason roster. The inconsistent nature of his first full Major League season enhances the difficulty of projecting how valuable he might be to the Braves from both an immediate and long-term perspective.

With the emergence of sofobuvir, a new direct acting antiviral, treatment for Hepatitis C infection is currently undergoing it's greatest change since the discovery of the virus 25 years ago. However Gilead, who manufacture the treatment, are under fire for the cost of the druge - around $90 000 for a course of treatment. Victor Roy, doctoral...

Pharma companies say that money spent on promotion is essential to educate doctors about the best drugs - but when a medical student asked Joseph Ross, associate professor of medicine and public health at Yale, if those companies are promoting the right drugs for that message to be true, the answer wasn't available. Ross and Tyler Greenaway, his...

Helen Macdonald and Carl Heneghan are back again talking about what's happened in the world of evidence this month. (1.20) Carl grinds his gears over general health checks, with an update in the Cochrane Library. (9.15) Helen is surprised by new research which looks at over prescription of antibiotics - but this time because the courses...

The present study examined the predictive values of amyloid PET, ¹⁸F-FDG PET, and nonimaging predictors (alone and in combination) for development of Alzheimer dementia (AD) in a large population of patients with mild cognitive impairment (MCI). Methods: The study included 319 patients with MCI from the Alzheimer Disease Neuroimaging Initiative database. In a derivation dataset (n = 159), the following Cox proportional-hazards models were constructed, each adjusted for age and sex: amyloid PET using ¹⁸F-florbetapir (pattern expression score of an amyloid-β AD conversion–related pattern, constructed by principle-components analysis); ¹⁸F-FDG PET (pattern expression score of a previously defined ¹⁸F-FDG–based AD conversion–related pattern, constructed by principle-components analysis); nonimaging (functional activities questionnaire, apolipoprotein E, and mini-mental state examination score); ¹⁸F-FDG PET + amyloid PET; amyloid PET + nonimaging; ¹⁸F-FDG PET + nonimaging; and amyloid PET + ¹⁸F-FDG PET + nonimaging. In a second step, the results of Cox regressions were applied to a validation dataset (n = 160) to stratify subjects according to the predicted conversion risk. Results: On the basis of the independent validation dataset, the ¹⁸F-FDG PET model yielded a significantly higher predictive value than the amyloid PET model. However, both were inferior to the nonimaging model and were significantly improved by the addition of nonimaging variables. The best prediction accuracy was reached by combining ¹⁸F-FDG PET, amyloid PET, and nonimaging variables. The combined model yielded 5-y free-of-conversion rates of 100%, 64%, and 24% for the low-, medium- and high-risk groups, respectively. Conclusion: ¹⁸F-FDG PET, amyloid PET, and nonimaging variables represent complementary predictors of conversion from MCI to AD. Especially in combination, they enable an accurate stratification of patients according to their conversion risks, which is of great interest for patient care and clinical trials.

We aimed to assess the value of ¹¹C-choline PET in patients with primary hyperparathyroidism and negative or discordant results on ^99mTc-sestamibi imaging and neck ultrasound. Methods: Eighty-seven such patients were assessed and subsequently underwent parathyroidectomy. PET/CT image data were analyzed semiquantitatively using SUV_max and SUV ratios (target to contralateral thyroid gland and carotid artery). A positive PET/CT result was defined as focal uptake significantly higher than regular thyroid tissue. Ectopic foci were also considered positive. Inconclusive PET/CT cases were defined as a lesion with uptake equal to normal thyroid tissue. If no prominent or ectopic uptake was detectable, the PET/CT result was considered negative. Results: When dichotomizing the ¹¹C-choline PET/CT imaging results by defining lesions with both positive and inconclusive uptake as positive, we found 84 of 92 lesions (91.3%) to have true-positive uptake whereas 8 lesions (8.7%) had false-positive uptake. One lesion showed false-negative uptake; the sensitivity was 98.8%. The corresponding positive predictive value for lesions was 91.3%. The mean SUV_max was 6.15 ± 4.92 in 72 lesions with positive uptake (70 patients) and 2.96 ± 2.32 in 20 lesions with inconclusive uptake (18 patients). Conclusion: These results in a large group of patients indicate that ¹¹C-choline PET/CT is a promising tool for parathyroid adenoma localization when ultrasound and ^99mTc-sestamibi imaging yield negative or discordant results.

As Greece's Aegean islands continue to grapple with migrants arriving on their shores, decisions regarding the needs of newcomers are negotiated in Brussels and Athens, far removed from the situation on the ground. Meanwhile, local communities have had successes in hosting migrants, as this article drawing on observations from the hospitality center and refugee camp on Lesvos explores.

To combat COVID-19, countries have enforced city-wide shutdowns, stay-at-home orders and mask mandates -- but the reaction (and adherence) to these rules has differed markedly in the East and West. In conversation with TED's head of curation Helen Walters, writer and publisher Huang Hung sheds light on how Chinese and American cultural values shaped their responses to the outbreak -- and provides perspective on why everyone needs to come together to end the pandemic. (Recorded April 16, 2020)

London : Macmillan, 1892.

Wednesday's collection of links.

Daniel R. Kowal, Antonio Canale.

Source: Electronic Journal of Statistics, Volume 14, Number 1, 1744--1772.

Abstract:
We propose a simple yet powerful framework for modeling integer-valued data, such as counts, scores, and rounded data. The data-generating process is defined by Simultaneously Transforming and Rounding (STAR) a continuous-valued process, which produces a flexible family of integer-valued distributions capable of modeling zero-inflation, bounded or censored data, and over- or underdispersion. The transformation is modeled as unknown for greater distributional flexibility, while the rounding operation ensures a coherent integer-valued data-generating process. An efficient MCMC algorithm is developed for posterior inference and provides a mechanism for adaptation of successful Bayesian models and algorithms for continuous data to the integer-valued data setting. Using the STAR framework, we design a new Bayesian Additive Regression Tree model for integer-valued data, which demonstrates impressive predictive distribution accuracy for both synthetic data and a large healthcare utilization dataset. For interpretable regression-based inference, we develop a STAR additive model, which offers greater flexibility and scalability than existing integer-valued models. The STAR additive model is applied to study the recent decline in Amazon river dolphins.

Zhengwei Liu, Qi Li, Fukang Zhu.

Source: Brazilian Journal of Probability and Statistics, Volume 34, Number 2, 251--272.

Abstract:
To predict time series of counts with small values and remarkable fluctuations, an available model is the $r$ states random environment process based on the negative binomial thinning operator and the geometric marginal. However, we argue that the aforementioned model may suffer from the following two drawbacks. First, under the condition of no prior information, the overdispersed property of the geometric distribution may cause the predictions fluctuate greatly. Second, because of the constraints on the model parameters, some estimated parameters are close to zero in real-data examples, which may not objectively reveal the correlation relationship. For the first drawback, an $r$ states random environment process based on the binomial thinning operator and the Poisson marginal is introduced. For the second drawback, we propose a generalized $r$ states random environment integer-valued autoregressive model based on the binomial thinning operator to model fluctuations of data. Yule–Walker and conditional maximum likelihood estimates are considered and their performances are assessed via simulation studies. Two real-data sets are conducted to illustrate the better performances of the proposed models compared with some existing models.

Flávio B. Gonçalves, Bárbara C. C. Dias.

Source: Brazilian Journal of Probability and Statistics, Volume 33, Number 4, 782--800.

Abstract:
Educational assessment usually considers a contextual questionnaire to extract relevant information from the applicants. This may include items related to socio-economical profile as well as items to extract other characteristics potentially related to applicant’s performance in the test. A careful analysis of the questionnaires jointly with the test’s results may evidence important relations between profiles and test performance. The most coherent way to perform this task in a statistical context is to use the information from the questionnaire to help explain the variability of the abilities in a joint model-based approach. Nevertheless, the responses to the questionnaire typically present missing values which, in some cases, may be missing not at random. This paper proposes a statistical methodology to model the abilities in dichotomous IRT models using the information of the contextual questionnaires via linear regression. The proposed methodology models the missing data jointly with the all the observed data, which allows for the estimation of the former. The missing data modelling is flexible enough to allow the specification of missing not at random structures. Furthermore, even if those structures are not assumed a priori, they can be estimated from the posterior results when assuming missing (completely) at random structures a priori. Statistical inference is performed under the Bayesian paradigm via an efficient MCMC algorithm. Simulated and real examples are presented to investigate the efficiency and applicability of the proposed methodology.

Ivana Ilić, Vladica M. Veličković.

Source: Brazilian Journal of Probability and Statistics, Volume 33, Number 1, 192--203.

Abstract:
Financial returns are known to be nonnormal and tend to have fat-tailed distribution. Also, the dependence of large values in a stochastic process is an important topic in risk, insurance and finance. In the presence of missing values, we deal with the asymptotic properties of a simple “median” estimator of the tail index based on random variables with the heavy-tailed distribution function and certain dependence among the extremes. Weak consistency and asymptotic normality of the proposed estimator are established. The estimator is a special case of a well-known estimator defined in Bacro and Brito [ Statistics & Decisions 3 (1993) 133–143]. The advantage of the estimator is its robustness against deviations and compared to Hill’s, it is less affected by the fluctuations related to the maximum of the sample or by the presence of outliers. Several examples are analyzed in order to support the proofs.

Norbert Hirschauer, Sven Grüner, Oliver Mußhoff, Claudia Becker, Antje Jantsch.

Source: Statistics Surveys, Volume 14, 71--91.

Abstract:
Besides the inferential errors that abound in the interpretation of $p$-values, the probabilistic pre-conditions (i.e. random sampling or equivalent) for using them at all are not often met by observational studies in the social sciences. This paper systematizes different sampling designs and discusses the restrictive requirements of data collection that are the indispensable prerequisite for using $p$-values.

Norbert Hirschauer, Sven Grüner, Oliver Mußhoff, Claudia Becker.

Source: Statistics Surveys, Volume 12, 136--172.

Abstract:
Data on how many scientific findings are reproducible are generally bleak and a wealth of papers have warned against misuses of the $p$-value and resulting false findings in recent years. This paper discusses the question of what we can(not) learn from the $p$-value, which is still widely considered as the gold standard of statistical validity. We aim to provide a non-technical and easily accessible resource for statistical practitioners who wish to spot and avoid misinterpretations and misuses of statistical significance tests. For this purpose, we first classify and describe the most widely discussed (“classical”) pitfalls of significance testing, and review published work on these misuses with a focus on regression-based “confirmatory” study. This includes a description of the single-study bias and a simulation-based illustration of how proper meta-analysis compares to misleading significance counts (“vote counting”). Going beyond the classical pitfalls, we also use simulation to provide intuition that relying on the statistical estimate “$p$-value” as a measure of evidence without considering its sample-to-sample variability falls short of the mark even within an otherwise appropriate interpretation. We conclude with a discussion of the exigencies of informed approaches to statistical inference and corresponding institutional reforms.

Heat waves resulting from prolonged extreme temperatures pose a significant risk to human health globally. Given the limitations of observations of extreme temperature, climate models are often used to characterize extreme temperature globally, from which one can derive quantities like return values to summarize the magnitude of a low probability event for an arbitrary geographic location. However, while these derived quantities are useful on their own, it is also often important to apply a spatial statistical model to such data in order to, e.g., understand how the spatial dependence properties of the return values vary over space and emulate the climate model for generating additional spatial fields with corresponding statistical properties. For these objectives, when modeling global data it is critical to use a nonstationary covariance function. Furthermore, given that the output of modern global climate models can be on the order of $mathcal{O}(10^4)$, it is important to utilize approximate Gaussian process methods to enable inference. In this paper, we demonstrate the application of methodology introduced in Risser and Turek (2020) to conduct a nonstationary and fully Bayesian analysis of a large data set of 20-year return values derived from an ensemble of global climate model runs with over 50,000 spatial locations. This analysis uses the freely available BayesNSGP software package for R.

Zhou Fan, Iain M. Johnstone.

Source: The Annals of Statistics, Volume 47, Number 5, 2855--2886.

Abstract:
We study the spectra of MANOVA estimators for variance component covariance matrices in multivariate random effects models. When the dimensionality of the observations is large and comparable to the number of realizations of each random effect, we show that the empirical spectra of such estimators are well approximated by deterministic laws. The Stieltjes transforms of these laws are characterized by systems of fixed-point equations, which are numerically solvable by a simple iterative procedure. Our proof uses operator-valued free probability theory, and we establish a general asymptotic freeness result for families of rectangular orthogonally invariant random matrices, which is of independent interest. Our work is motivated in part by the estimation of components of covariance between multiple phenotypic traits in quantitative genetics, and we specialize our results to common experimental designs that arise in this application.

Hong Zhang, Tiejun Tong, John Landers, Zheyang Wu.

Source: The Annals of Applied Statistics, Volume 14, Number 1, 178--201.

Abstract:
The $p$-value combination approach is an important statistical strategy for testing global hypotheses with broad applications in signal detection, meta-analysis, data integration, etc. In this paper we extend the classic Fisher’s combination method to a unified family of statistics, called TFisher, which allows a general truncation-and-weighting scheme of input $p$-values. TFisher can significantly improve statistical power over the Fisher and related truncation-only methods for detecting both rare and dense “signals.” To address wide applications, analytical calculations for TFisher’s size and power are deduced under any two continuous distributions in the null and the alternative hypotheses. The corresponding omnibus test (oTFisher) and its size calculation are also provided for data-adaptive analysis. We study the asymptotic optimal parameters of truncation and weighting based on Bahadur efficiency (BE). A new asymptotic measure, called the asymptotic power efficiency (APE), is also proposed for better reflecting the statistics’ performance in real data analysis. Interestingly, under the Gaussian mixture model in the signal detection problem, both BE and APE indicate that the soft-thresholding scheme is the best, the truncation and weighting parameters should be equal. By simulations of various signal patterns, we systematically compare the power of statistics within TFisher family as well as some rare-signal-optimal tests. We illustrate the use of TFisher in an exome-sequencing analysis for detecting novel genes of amyotrophic lateral sclerosis. Relevant computation has been implemented into an R package TFisher published on the Comprehensive R Archive Network to cater for applications.

Some Democrats took "Believe Women" literally until Joe Biden was accused. Now they're relearning that guilt-by-accusation doesn't serve justice.

Apple's new iPhone SE delivers incredible value and performance, has a surprisingly good camera, and handles videos well. Reviewers were impressed by the phone's A13 chipset. However, criticisms include insufficient battery life, absence of night mode, and lack of 5G support. "For those of us concerned about money ... the SE provides the greatest bang for the buck," said tech analyst Rob Enderle.