Showing 1 - 19 results of 19 for search '"longitudinal data"', query time: 0.06s Refine Results
  1. 1

    An Assessment of the Utility of a Bayesian Framework to Improve Response Propensity Models in Longitudinal Data by Eliud Kibuchi, Gabriele B Durrant, Olga Maslovskaya, Patrick Sturgis

    Published 2024-12-01
    “…This paper explores whether the use of a Bayesian framework can improve the predictions of response propensity models in longitudinal data. In the Bayesian approach existing knowledge regarding model parameters is used to specify prior distributions. …”
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    Article
  2. 2

    Progression of Heart Failure in People with Type 2 Diabetes in Germany: An Analysis Using German Health Insurance Claims Data by Keni Cheng-Siang Lee, Tobias Wagner, Adee Kennedy, Michael Wilke

    Published 2024-08-01
    “…**Methods:** This descriptive, retrospective study used longitudinal data from German statutory health insurance claims. …”
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  3. 3

    Relationship between movement behaviours and life satisfaction in Chinese children: A cross-lagged panel analysis. by Xingyi Yang, Danqing Zhang, Yang Liu

    Published 2025-01-01
    “…This study examined the relationship between movement behaviours and life satisfaction (LS) using longitudinal data from a sample of primary school students. …”
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  4. 4

    Creating National Weights for a Patient-level Longitudinal Database by Onur Baser, Li Wang, Jon Maguire

    Published 2016-03-01
    “…**Objective:** To create a nationally-representative estimate from longitudinal data by controlling for sociodemographic factors and health status. …”
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  5. 5

    Prediction of Multidimensional Poverty Status With Machine Learning Classification at Household Level: Empirical Evidence From Tanzania by Ngong'Ho Bujiku Sende, Snehanshu Saha, Leon Ruganzu, Saibal Kar

    Published 2025-01-01
    “…To achieve this objective, longitudinal data from the 2014/15 and 2020/21 surveys, sourced from the Tanzania National Bureau of Statistics (NBS) were analyzed. …”
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  6. 6

    MRI-based hip cartilage measures in osteoarthritic and non-osteoarthritic individuals: a systematic review by Jacob L Jaremko, Hector N Aguilar, Michele C Battié

    Published 2017-03-01
    “…Overall, the studies consistently demonstrate the reliability and potential clinical utility of MRI-based estimates. However, no longitudinal data or reference values for hip cartilage thickness or volume have been published, limiting the ability of MRI to define or risk-stratify hip osteoarthritis. …”
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  7. 7

    Information quality and students’ academic performance: the mediating roles of perceived usefulness, entertainment and social media usage by Abdallah M. M. Badr, Badr Saleh Al-Abdi, Maged Rfeqallah, Rozilah Kasim, Faisal A. M. Ali

    Published 2024-10-01
    “…Therefore, the results of the investigation cannot be generalized as a whole, and cannot track respondents’ social media activity over time. Thus, longitudinal data may be used in future investigations. …”
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    Dynamics of perceived threat and media exposure during the COVID-19 pandemic by Talia Morstead, Nancy L. Sin, Anita DeLongis

    Published 2025-06-01
    “…In this study, we used longitudinal data from 3189 primarily North American participants, collected monthly from June 2020 through January 2021 to examine reciprocal associations among media exposure, COVID-19 thought frequency, and perceived threat of COVID-19 at the within-person level of analysis. …”
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  10. 10

    Association between exposure in the cement production industry and non-malignant respiratory effects: a systematic review by Anne Kristin Møller Fell, Karl Christian Nordby

    Published 2017-04-01
    “…Hence, no firm conclusions can be drawn. There are few longitudinal data, but recent studies report a dose–response relationship between cement production dust exposure and declining lung function indicating a causal relationship, and underlining the need to reduce exposure among workers in this industry.…”
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  11. 11

    Nurture-U student mental health longitudinal survey: a study protocol by Kate E Saunders, Samuel R Chamberlain, Jemima Dooley, Edward R Watkins, Liz Forty, Sarah Rees, Anne C Duffy, Anthony Quinn, Ellen Marshall, Lucy Dorey, Kevin A Matlock, Alexandra Newbold, Lucy J Robinson

    Published 2025-02-01
    “…This study aims to address gaps in longitudinal data on student mental health in the UK and to identify risk and protective factors across diverse student populations.Methods and analysis The current Nurture-U survey is developed from the U-Flourish biannual survey study piloted at Queen’s and Oxford universities in Canada and the UK, respectively. …”
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    Heightened demand for mental health information resources during the SARS-CoV-2 pandemic in Germany: A retrospective longitudinal analysis of helpline calls by Jil Zippelius, Simon Schreynemackers, Ulrich Hegerl, Hanna Reich

    Published 2025-04-01
    “…Methods: Based on longitudinal data from 2018 to 2022 predictive models were developed for caller trends on the Info-Telefon Depression. …”
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  14. 14

    Environmental risk factors for self-harm during imprisonment: A pilot prospective cohort study. by Thomas Stephenson, Imogen Harris, Charlotte Armstrong, Seena Fazel, Roxanna Short, Nigel Blackwood

    Published 2025-01-01
    “…<h4>Discussion</h4>This exploratory pilot study provides prospective longitudinal data regarding relationships between prison environmental factors and self-harm behaviour. …”
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  15. 15

    Comparison of time-to-event machine learning models in predicting biliary complication and mortality rate in liver transplant patients by Aref Andishgar, Sina Bazmi, Kamran B. Lankarani, Seyed Alireza Taghavi, Mohammad Hadi Imanieh, Gholamreza Sivandzadeh, Samira Saeian, Nazanin Dadashpour, Alireza Shamsaeefar, Mahdi Ravankhah, Hamed Nikoupour Deylami, Reza Tabrizi, Mohammad Hossein Imanieh

    Published 2025-02-01
    “…Abstract Post-Liver transplantation (LT) survival rates stagnate, with biliary complications (BC) as a major cause of death. We analyzed longitudinal data with a median 19-month follow-up. BC was diagnosed with ultrasounds and MRCP. …”
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  16. 16

    Health Implications of Anabolic-Androgenic Steroids: Usage, Risks, and Treatment Approaches - The Literature Review by Krzysztof Jodłowski, Ewa Dubniewicz, Paula Majewska, Alicja Staszek, Wiktoria Łoskot, Jan Szwech, Mateusz Matczak, Karol Jasiński, Aleksandra Broda, Kacper Hoksa

    Published 2025-02-01
    “…Furthermore, the review highlights significant gaps in the literature, such as the absence of comprehensive guidelines for harm reduction and the scarcity of longitudinal data on the long-term effects of AAS. The findings suggest a critical need for continued research, better medical management, and societal interventions to mitigate the risks associated with AAS use and provide effective care for affected individuals. …”
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  17. 17

    A novel model-based meta-analysis to indirectly estimate the comparative efficacy of two medications: an example using DPP-4 inhibitors, sitagliptin and linagliptin, in treatment o... by Yan Gong, James Rogers, Christian Friedrich, Sanjay Patel, Alexander Staab, Jorge Luiz Gross, Daniel Polhamus, William Gillespie, Brigitta Ursula Monz, Silke Retlich

    Published 2013-03-01
    “…For the indirect comparison, a population of 1000 patients was simulated from the model with a racial composition reflecting the average racial distribution of the linagliptin trials, and baseline HbA1c of 8%.Results The model was developed using longitudinal data from 11 234 patients (10 linagliptin, 15 sitagliptin trials), and assessed by internal evaluation techniques, demonstrating that the model adequately described the observations. …”
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    Path model explaining the association between fear of falling and health-related quality of life in (pre-)frail older adults by Tjard Sattler, Sophie Gottschalk, Hans-Helmut König, Tobias Braun, Gisela Büchele, Michael Denkinger, Tim Fleiner, Corinna Nerz, Kilian Rapp, Martina Schäufele, Christian Werner, Judith Dams

    Published 2025-02-01
    “…The proposed model should be tested on an alternative sample, using longitudinal data, and extended to include additional explanatory factors (e.g. activity avoidance). …”
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