https://nova.newcastle.edu.au/vital/access/ /manager/Index en-au 5 Model-based data fitting https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:8586 Wed 24 Jul 2013 22:42:54 AEST ]]> Spectroscopic imaging and chemometrics: a powerful combination for global and local sample analysis https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:3222 Wed 24 Jul 2013 22:20:07 AEST ]]> The aggregate association index and its extensions https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:22504 Wed 11 Apr 2018 10:26:22 AEST ]]> Real-world occupational epidemiology, Part 3: an aggregate data analysis of Selikoff's '20-year rule' https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:15654 Wed 11 Apr 2018 10:16:40 AEST ]]> Chemical process analysis: chemometrics; instrument control; applications in equilibrium and kinetic investigations https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:6077 Wed 11 Apr 2018 10:06:37 AEST ]]> Managing missing and erroneous data in nurse staffing surveys https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:54073 Tue 30 Jan 2024 14:10:35 AEDT ]]> Data analysis guidelines for single-cell RNA-seq in biomedical studies and clinical applications https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:52015 Tue 26 Sep 2023 11:42:58 AEST ]]> Giving voice to teachers through interpretative phenomenological research: a methodological consideration https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:43895 Tue 04 Oct 2022 13:59:52 AEDT ]]> ‘What’s going on here?’: The pedagogy of a data analysis session https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:31917 Thu 12 Apr 2018 11:56:51 AEST ]]> Synthetic Data as a Strategy to Resolve Data Privacy and Confidentiality Concerns in the Sport Sciences: Practical Examples and an R Shiny Application https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:52138 .05). Further, there was distributional similarity (ie, low standardized propensity mean squared error) between the original observed and synthetic data sets. Conclusions: These findings highlight the potential use of synthetic data as a practical solution to privacy and confidentiality issues. Synthetic data can unlock previously inaccessible data sets for exploratory analysis and facilitate multiteam or multicenter collaborations. Interested sport scientists, practitioners, and researchers should consider utilizing the shiny web application (SYNTHETIC DATA—available at https://assetlab.shinyapps.io/SyntheticData/).]]> Thu 09 Nov 2023 15:59:48 AEDT ]]> Scientific models for qualitative research: a textual thematic analysis coding system - Part 1 https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:52235 Thu 05 Oct 2023 11:40:51 AEDT ]]> Two-way data analysis: evolving factor analysis https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:8599 Sat 24 Mar 2018 08:38:35 AEDT ]]> Automated versus manual audit in the emergency department https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:5330 Sat 24 Mar 2018 07:45:58 AEDT ]]> Prevalence of celiac disease in 52,721 youth with type 1 diabetes: international comparison across three continents https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:30983 1c, height SD score [SDS], overweight/obesity) and type 1 diabetes/CD versus type 1 diabetes, adjusting for sex, age, and diabetes duration. Results: Biopsy-confirmed CD was present in 1,835 youths (3.5%) and was diagnosed at a median age of 8.1 years (interquartile range 5.3–11.2 years). Diabetes duration at CD diagnosis was <1 year in 37% of youths, >1–2 years in 18% of youths, >3–5 years in 23% of youths, and >5 years in 17% of youths. CD prevalence ranged from 1.9% in the T1DX to 7.7% in the ADDN and was higher in girls than boys (4.3% vs. 2.7%, P < 0.001). Children with coexisting CD were younger at diabetes diagnosis compared with those with type 1 diabetes only (5.4 vs. 7.0 years of age, P < 0.001) and fewer were nonwhite (15 vs. 18%, P < 0.001). Height SDS was lower in those with CD (0.36 vs. 0.48, adjusted P < 0.001) and fewer were overweight/obese (34 vs. 37%, adjusted P < 0.001), whereas mean HbA1c values were comparable: 8.3 ± 1.5% (67 ± 17 mmol/mol) versus 8.4 ± 1.6% (68 ± 17 mmol/mol). Conclusions: CD is a common comorbidity in youth with type 1 diabetes. Differences in CD prevalence may reflect international variation in screening and diagnostic practices, and/or CD risk. Although glycemic control was not different, the lower height SDS supports close monitoring of growth and nutrition in this population.]]> Sat 24 Mar 2018 07:27:34 AEDT ]]> Guest authorship, mortality reporting, and integrity in rofecoxib studies (letter) https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:4461 Sat 24 Mar 2018 07:18:29 AEDT ]]> Climate change drivers https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:42936 Mon 12 Sep 2022 08:48:35 AEST ]]> Educational interventions for health professionals managing chronic obstructive pulmonary disease in primary care https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:51412 Mon 04 Sep 2023 14:52:36 AEST ]]> Socioeconomic disadvantage as a driver of non-urgent emergency department presentations: a retrospective data analysis https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:40596 Fri 15 Jul 2022 11:14:14 AEST ]]> Interdisciplinary Sport Science in Individual Sports - A Framework for Implementation https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:54675 Fri 08 Mar 2024 11:38:40 AEDT ]]> A design concept of big data analytics model for managers in hospitality industries https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:54650 Fri 08 Mar 2024 09:46:28 AEDT ]]> Diagnosing https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:24036 Fri 04 Nov 2016 15:50:56 AEDT ]]>