How good are your fits? Unbinned multivariate goodness-of-fit tests in high energy physics

Multivariate analyses play an important role in high energy physics. Such analyses often involve performing an unbinned maximum likelihood fit of a probability density function (p.d.f.) to the data. This paper explores a variety of unbinned methods for determining the goodness of fit of the p.d.f. to the data. The application and performance of each method is discussed in the context of a real-life high energy physics analysis (a Dalitz-plot analysis). Several of the methods presented in this paper can also be used for the non-parametric determination of whether two samples originate from the same parent p.d.f. This can be used, e.g., to determine the quality of a detector Monte Carlo simulation without the need for a parametric expression of the efficiency.Comment: 32 pages, 12 figure

Goodness-of-Fit Tests to study the Gaussianity of the MAXIMA data

Goodness-of-Fit tests, including Smooth ones, are introduced and applied to detect non-Gaussianity in Cosmic Microwave Background simulations. We study the power of three different tests: the Shapiro-Francia test (1972), the uncategorised smooth test developed by Rayner and Best(1990) and the Neyman's Smooth Goodness-of-fit test for composite hypotheses (Thomas and Pierce 1979). The Smooth Goodness-of-Fit tests are designed to be sensitive to the presence of ``smooth'' deviations from a given distribution. We study the power of these tests based on the discrimination between Gaussian and non-Gaussian simulations. Non-Gaussian cases are simulated using the Edgeworth expansion and assuming pixel-to-pixel independence. Results show these tests behave similarly and are more powerful than tests directly based on cumulants of order 3, 4, 5 and 6. We have applied these tests to the released MAXIMA data. The applied tests are built to be powerful against detecting deviations from univariate Gaussianity. The Cholesky matrix corresponding to signal (based on an assumed cosmological model) plus noise is used to decorrelate the observations previous to the analysis. Results indicate that the MAXIMA data are compatible with Gaussianity.Comment: MNRAS, in pres

Impact of enzyme replacement therapy on survival in adults with Pompe disease: Results from a prospective international observational study

Background: Pompe disease is a rare metabolic myopathy for which disease-specific enzyme replacement therapy (ERT) has been available since 2006. ERT has shown efficacy concerning muscle strength and pulmonary function in adult patients. However, no data on the effect of ERT on the survival of adult patients are currently available. The aim of this study was to assess the effect of ERT on survival in adult patients with Pompe disease. Methods. Data were collected as part of an international observational study conducted between 2002 and 2011, in which patients were followed on an annual basis. Time-dependent Cox's proportional hazards models were used for univariable and multivariable analyses. Results: Overall, 283 adult patients with a median age of 48 years (range, 19 to 81 years) were included in the study. Seventy-two percent of patients started ERT at some time during follow-up, and 28% never received ERT. During follow-up (median, 6 years; range, 0.04 to 9 years), 46 patients died, 28 (61%) of whom had never received ERT. After adjustment for age, sex, country of residence, and disease severity (based on wheelchair and ventilator use), ERT was positively associated with survival (hazard ratio, 0.41; 95% CI, 0.19 to 0.87). Conclusion: This prospective study was the first to demonstrate the positive effect of ERT on survival in adults with Pompe disease. Given the relatively recent registration of ERT for Pompe disease, these findings further support its beneficial impact in adult patients

Randomized Pragmatic Trial of Stroke Transitional Care: The COMPASS Study

Background The objectives of this study were to develop and test in real-world clinical practice the effectiveness of a comprehensive postacute stroke transitional care (TC) management program. Methods and Results The COMPASS study (Comprehensive Post-Acute Stroke Services) was a pragmatic cluster-randomized trial where the hospital was the unit of randomization. The intervention (COMPASS-TC) was initiated at 20 hospitals, and 20 hospitals provided their usual care. Hospital staff enrolled 6024 adult stroke and transient ischemic attack patients discharged home between 2016 and 2018. COMPASS-TC was patient-centered and assessed social and functional determinates of health to inform individualized care plans. Ninety-day outcomes were evaluated by blinded telephone interviewers. The primary outcome was functional status (Stroke Impact Scale-16); secondary outcomes were mortality, disability, medication adherence, depression, cognition, self-rated health, fatigue, care satisfaction, home blood pressure monitoring, and falls. The primary analysis was intention to treat. Of intervention hospitals, 58% had uninterrupted intervention delivery. Thirty-five percent of patients at intervention hospitals attended a COMPASS clinic visit. The primary outcome was measured for 59% of patients and was not significantly influenced by the intervention. Mean Stroke Impact Scale-16 (±SD) was 80.6±21.1 in TC versus 79.9±21.4 in usual care. Home blood pressure monitoring was self-reported by 72% of intervention patients versus 64% of usual care patients (adjusted odds ratio, 1.43 [95% CI, 1.21-1.70]). No other secondary outcomes differed. Conclusions Although designed according to the best available evidence with input from various stakeholders and consistent with Centers for Medicare and Medicaid Services TC policies, the COMPASS model of TC was not consistently incorporated into real-world health care. We found no significant effect of the intervention on functional status at 90 days post-discharge. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT02588664