- Research Article
1
- 10.1111/rssa.12723
A Computational Approach to Statistical Learning
- Jul 01, 2021
- Journal of the Royal Statistical Society Series A: Statistics in Society
- Stanley E Lazic
Publications from 2021 to 2026
Showing 8 of 8 papers
A Computational Approach to Statistical Learning
The ARRIVE guidelines 2.0: Updated guidelines for reporting animal research*
Reproducible science requires transparent reporting. The ARRIVE guidelines (Animal Research: Reporting of In Vivo Experiments) were originally developed in 2010 to improve the reporting of animal research. They consist of a checklist of information to include in publications describing in vivo experiments to enable others to scrutinise the work adequately, evaluate its methodological rigour, and reproduce the methods and results. Despite considerable levels of endorsement by funders and journals over the years, adherence to the guidelines has been inconsistent, and the anticipated improvements in the quality of reporting in animal research publications have not been achieved. Here, we introduce ARRIVE 2.0. The guidelines have been updated and information reorganised to facilitate their use in practice. We used a Delphi exercise to prioritise and divide the items of the guidelines into 2 sets, the “ARRIVE Essential 10,” which constitutes the minimum requirement, and the “Recommended Set,” which describes the research context. This division facilitates improved reporting of animal research by supporting a stepwise approach to implementation. This helps journal editors and reviewers verify that the most important items are being reported in manuscripts. We have also developed the accompanying Explanation and Elaboration document, which serves (1) to explain the rationale behind each item in the guidelines, (2) to clarify key concepts, and (3) to provide illustrative examples. We aim, through these changes, to help ensure that researchers, reviewers, and journal editors are better equipped to improve the rigour and transparency of the scientific process and thus reproducibility.
Read moreThe ARRIVE guidelines 2.0: Updated guidelines for reporting animal research.
Reproducible science requires transparent reporting. The ARRIVE guidelines (Animal Research: Reporting of In Vivo Experiments) were originally developed in 2010 to improve the reporting of animal research. They consist of a checklist of information to include in publications describing in vivo experiments to enable others to scrutinise the work adequately, evaluate its methodological rigour, and reproduce the methods and results. Despite considerable levels of endorsement by funders and journals over the years, adherence to the guidelines has been inconsistent, and the anticipated improvements in the quality of reporting in animal research publications have not been achieved. Here, we introduce ARRIVE 2.0. The guidelines have been updated and information reorganised to facilitate their use in practice. We used a Delphi exercise to prioritise and divide the items of the guidelines into 2 sets, the "ARRIVE Essential 10," which constitutes the minimum requirement, and the "Recommended Set," which describes the research context. This division facilitates improved reporting of animal research by supporting a stepwise approach to implementation. This helps journal editors and reviewers verify that the most important items are being reported in manuscripts. We have also developed the accompanying Explanation and Elaboration document, which serves (1) to explain the rationale behind each item in the guidelines, (2) to clarify key concepts, and (3) to provide illustrative examples. We aim, through these changes, to help ensure that researchers, reviewers, and journal editors are better equipped to improve the rigour and transparency of the scientific process and thus reproducibility.
Read moreSUN-377 Efficacy of Low Dose Denosumab in Maintaining Bone Mineral Density in Postmenopausal Women with Osteoporosis: A Real World, Prospective Observational Study
Introduction: Denosumab, a fully human monoclonal antibody to RANK-ligand, has been shown to increase bone mineral density (BMD) and reduce the risk of hip, vertebral and non-vertebral fractures in postmenopausal women with osteoporosis (1-3). Varying doses of denosumab including 30mg/3months have demonstrated a decrease in bone remodelling in a dose-dependent manner (2,4-6). The primary objective of this study is to evaluate the efficacy of low dose denosumab (30mg/6 months) in postmenopausal women with osteoporosis who are reluctant to consider or continue the full dose of denosumab due to adverse events (AE) or concerns of potential AE. Methods: Following informed consent, postmenopausal women with a T-score of ≤ -2.5 at the lumbar spine (LS) or at the total hip (TH) received denosumab 30mg/6months. Patients with an additional skeletal disorder, prior fragility fracture, or on oral steroids (daily in the past 12 months) were excluded. The primary endpoint was the percent change in BMD at the lumbar spine (LS), total hip (HP), femoral neck (FN) and 1/3 radius (1/3R) at 12 months. Secondary outcomes were 1) percent change in BMD at the LS, TH, FN, and 1/3R at 24 months and 2) AE. Results: We enrolled 183 patients. The mean age was 69 years (SD= 7.07), 80% of patients had a moderate fracture risk (CAROC tool), 3% were current smokers and 9% consumed alcohol daily. 14.4% of patients were on SSRI/SNRI, 9.6% were on PPI, and no patient was on an aromatase inhibitor. At 12 months (n=125), the mean BMD significantly increased by +2.0% (95% CI 2.8%-1.3%) at the LS (p<0.001). There was no significant change in BMD at the FN, TH, AND 1/3R. At 24 months (n=65), the percent change in BMD was +3.4% (95% CI 4.8%-2.0%: p<0.001) at the LS, +1.5% (95% CI 2.9%-0.15%: p=0.031) at the FN, +1.9% (95% CI 3.5%-0.24%: p=0.025) at the 1/3R. There was no significant change in BMD at the TH. Conclusion: Low dose denosumab appears to be effective in maintaining BMD in postmenopausal women with a moderate fracture risk and may be of benefit in individuals who are experiencing side effects or concerns of side effects. This may also be of value following 10 years of therapy in order to maintain BMD.
Read moreA Bayesian predictive approach for dealing with pseudoreplication
Pseudoreplication occurs when the number of measured values or data points exceeds the number of genuine replicates, and when the statistical analysis treats all data points as independent and thus fully contributing to the result. By artificially inflating the sample size, pseudoreplication contributes to irreproducibility, and it is a pervasive problem in biological research. In some fields, more than half of published experiments have pseudoreplication – making it one of the biggest threats to inferential validity. Researchers may be reluctant to use appropriate statistical methods if their hypothesis is about the pseudoreplicates and not the genuine replicates; for example, when an intervention is applied to pregnant female rodents (genuine replicates) but the hypothesis is about the effect on the multiple offspring (pseudoreplicates). We propose using a Bayesian predictive approach, which enables researchers to make valid inferences about biological entities of interest, even if they are pseudoreplicates, and show the benefits of this approach using two in vivo data sets.
Read moreParity and lactation are not associated with incident fragility fractures or radiographic vertebral fractures over 16years of follow-up: Canadian Multicentre Osteoporosis Study (CaMos).
Pregnancy and especially lactation cause loss of bone mass and microarchitectural changes, which temporarily increase fracture risk. After weaning, aBMD increases but skeletal microarchitecture may be incompletely restored. Most retrospective clinical studies found neutral or even protective associations of parity and lactation with fragility fractures, but prospective data are sparse. CaMos is a randomly selected observational cohort that includes ~ 6500 women followed prospectively for over 16years. We determined whether parity or lactation were related to incident clinical fragility fractures over 16years, radiographic (morphometric and morphologic) vertebral fractures over 10years, and aBMD change (spine, total hip, and femoral neck) over 10years. Parity and lactation duration were analyzed as continuous variables in predicting these outcomes using univariate and multivariate regression analyses. Three thousand four hundred thirty-seven women completed 16years of follow-up for incident clinical fractures, 3839 completed 10years of morphometric vertebral fracture assessment, 3788 completed 10years of morphologic vertebral fracture assessment, and 4464 completed 10years of follow-up for change in aBMD. In the multivariate analyses, parity and lactation duration showed no associations with clinical fragility fractures, radiographic vertebral fractures, or change in aBMD, except that parity associated with a probable chance finding of a slightly greater decline in femoral neck aBMD. Parity and lactation have no adverse associations with clinical fragility or radiographic vertebral fractures, or the rate of BMD decline over 10years, in this prospective, multicenter study of a randomly selected, population-based cohort of women.
Read moreWestern Osteoporosis Alliance Clinical Practice Series: Evaluating the Balance of Benefits and Risks of Long-Term Osteoporosis Therapies
Minimizing the expected response time of an idled server on a line
We address the problem of where to locate an idle server in a one-dimensional system where the arrival of demands for service have both spatial and temporal uncertainty. In such a system it is reasonable to have an idle server make an anticipatory move in order to better position itself for the next demand. However, moving all the way to its home base, or even moving at all, might delay the service for a demand which arrives during the move. We develop an analytical model to optimize the destination of an anticipatory move based upon the location of the server. Insights into the impact of system parameters as well as empirical examples are given.
Read more