Showing 181 - 200 results of 208 for search '"missing data"', query time: 0.09s Refine Results
  1. 181
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    Characteristics associated with career self-reliance behaviors of nurses working in nursing homes in Japan: A cross-sectional study by Ayako Nakayama, Junko Hoshino, Masashi Hotta, Mayuri Hashimoto, Naomi Furukawa

    Published 2025-01-01
    “…Results: Consequently, a total of 336 questionnaires were collected, of which 289 without missing data were analyzed. Of the 289 participants, 79 (27.3%) had certifications or licenses other than those for nursing or had completed graduate school. …”
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    Article
  3. 183

    Core Outcome Set Development for Tension-Type Headache Treatment Using Traditional Chinese Medicine: Protocol for a Delphi Consensus Study by Guojing Fu, Yunmeng Chen, Xiao Liang, Chunli Guo, Xueming Fan, Xiao Gong, Wenjie Chen, Jing Teng, Jun Tang, Xing Liao, Jingjing Wei, Yunling Zhang

    Published 2025-02-01
    “…However, the lack of standardized evidence—such as inconsistencies in outcome selection and reporting in clinical studies, a lack of consensus on outcomes and measures, high risks of selective reporting bias, and missing data—has limited the development of robust evidence supporting the efficacy of TCM in treating TTH. …”
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  4. 184

    Investigating Smartphone-Based Sensing Features for Depression Severity Prediction: Observation Study by Yannik Terhorst, Eva-Maria Messner, Kennedy Opoku Asare, Christian Montag, Christopher Kannen, Harald Baumeister

    Published 2025-01-01
    “…Depression severity was assessed using the 8-item Patient Health Questionnaire. Missing data were handled by multiple imputations. Correlation analyses were conducted for bivariate associations; stepwise linear regression analyses were used to find the best prediction models for depression severity. …”
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    Article
  5. 185

    Long-Chain Polyunsaturated Fatty Acids and Painful Temporomandibular Disorder in the Hispanic Community Health Study/Study of Latinos by Anne E. Sanders, Jianwen Cai, Martha L. Daviglus, Olga Garcia-Bedoya, Gary D. Slade

    “…Participants: 13,870 participants with non-missing data. Results: In analysis adjusted for covariates, each standard deviation increase in dietary intake of C20:4n-6, AA was associated with 12% higher odds of TMD (OR=1.12, CL:1.01, 1.24). …”
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  6. 186

    Use of Cesarean Birth among Robson Groups 2 and 4 at Mizan-Tepi University Hospital, Ethiopia by Margo S. Harrison, Tewodros Liyew, Ephrem Kirub, Biruk Teshome, Andrea Jimenez-Zambrano, Margaret Muldrow, Teklemariam Yarinbab

    Published 2020-01-01
    “…In Robson Group 4, all 4 women delivered by prelabor cesarean had a maternal indication (one was missing data), and 3 of the intrapartum cesareans were indicated by “failed induction or augmentation.” …”
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  7. 187

    Takeaway food consumption and depressive symptoms in Chinese university students: mediating effects of physical activity by Jianyu Tan, Jianyu Tan, Rui Wang, Rui Wang, Zhewei Su, Zhewei Su, Yiting Kong, Yiting Kong, Pan Ran, Pan Ran, Andrew Greenshaw, Su Hong, Qi Zhang, Qi Zhang, Wo Wang, Ming Ai, Ming Ai, Li Kuang, Li Kuang

    Published 2025-01-01
    “…Multiple imputations were used to fill in missing data through sensitivity analyses.ResultsAmong 6417 participants, 2,606 (40.6%) students ordered takeaway at least once a week, with 235 (3.7%) of them ordering takeaway food every day. …”
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  8. 188

    Survival in patients with CKD 3–5 after 12 months of exercise training – a post-hoc analysis of the RENEXC trial by Sara Denguir, Matthias Hellberg, Martin Almquist, Naomi Clyne

    Published 2025-01-01
    “…Patients were categorized into five groups: improved ≥ 5%, unchanged, deteriorated ≥ 5%, non-completers, missing data. Univariate and multivariate Cox regression analyses were used and adjusted for age, sex, comorbidity, time on dialysis and time with a kidney transplant. …”
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  9. 189

    Relationship between obesity indicators and hypertension–diabetes comorbidity among adults: a population study from Central China by Li Li, Ling Li, Ying Wang, Wenwen Wu, Xiaodong Tan, Fen Yang, Jinru Yang, Yifan Wu, Donghan Sun, Ziling Ni, Yaofei Xie

    Published 2022-07-01
    “…Objective To identify the relationship between obesity indicators and hypertension–diabetes comorbidity (HDC) among adults in central China.Design and setting A cross-sectional study was conducted from 1 June 2015 to 30 September 2018 in 11 districts of Hubei Province, China.Participants A total of 29 396 participants aged 18 years or above were enrolled in the study. 2083 subjects with missing data were excluded. Eventually, 25 356 participants were available for the present analysis.Main outcome measures Data were subjected to univariable and multivariable logistic regression to examine the association between obesity indicators (body mass index (BMI), waist circumference (WC) and waist-to-height ratio (WHtR)) and HDC prevalence. …”
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  10. 190

    Mortality Prediction Using SaO2/FiO2 Ratio Based on eICU Database Analysis by Sharad Patel, Gurkeerat Singh, Samson Zarbiv, Kia Ghiassi, Jean-Sebastien Rachoin

    Published 2021-01-01
    “…Exploratory data analysis was performed in Python. Missing data was imputed with Sklearn Iterative Imputer. …”
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  11. 191

    Risk prediction models for feeding intolerance in patients with enteral nutrition: a systematic review and meta-analysis by Huijiao Chen, Jin Han, Jing Li, Jianhua Xiong, Dong Wang, Mingming Han, Yuehao Shen, Wenli Lu

    Published 2025-01-01
    “…The data from the selected studies should be extracted, including study design, subjects, duration of follow-up, data sources, outcome measures, sample size, handling of missing data, continuous variable handling methods, variable selection, final predictors, model development and performance, and form of model presentation. …”
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  12. 192

    Cohort profile: the Western Cape Pregnancy Exposure Registry (WCPER) by Landon Myer, Amy L Slogrove, Ushma Mehta, Mary-Ann Davies, Max Kroon, Greg Petro, Alexa Heekes, Andrew Boulle, Karen Fieggen, Chantal Stewart, Ayesha Osman, Natasha Rhoda, Emma Kalk, Florence Phelanyane, Jonathan Euvrard, Stefan Gebhardt, Kim Anderson

    Published 2022-06-01
    “…This relationship limits the missing data in the PER, allows validation and avoids misclassification in the population-level data set.Findings to date Approximately 5000 and 3500 pregnant women enter the data set annually at the urban and rural sites, respectively. …”
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    Obtaining patient phenotypes in SARS-CoV-2 pneumonia, and their association with clinical severity and mortality by Fernando García-García, Dae-Jin Lee, Mónica Nieves-Ermecheo, Olaia Bronte, Pedro Pablo España, José María Quintana, Rosario Menéndez, Antoni Torres, Luis Alberto Ruiz Iturriaga, Isabel Urrutia, COVID-19 & Air Pollution Working Group

    Published 2024-06-01
    “…We proposed a sequence of machine learning stages: feature scaling, missing data imputation, reduction of data dimensionality via Kernel Principal Component Analysis (KPCA), and clustering with the k-means algorithm. …”
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    The association between metabolomic profiles of lifestyle and the latent phase of incident chronic kidney disease in the UK Population by Tingting Jin, Yunqi Wu, Siyi Zhang, Ya Peng, Yao Lin, Saijun Zhou, Hongyan Liu, Pei Yu

    Published 2025-01-01
    “…The study enrolled approximately 500,000 participants from the UK Biobank (UKB) between 2006 and 2010, excluding 447,163 individuals with missing data for any metabolite in the NMR metabolomics, any biomarker in the blood chemistry (including eGFR, albumin, or cystatin C), any factor required for constructing the lifestyle score, or a baseline diagnosis of CKD. …”
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  19. 199

    Modern perspective of the Rice Diet for hypertension and other metabolic diseases by Anthony Kuo, Pao-Hwa Lin, Yi-Ju Li, Friedrich C Luft, David López, Romeo Sommerfeld, Paul Ermler, Jana Fehr, Benjamin Bergner, Scott Sanoff, Francis Neelon, William McDowell, Smilla Fox, Abdullatif Ghajar, Elena Gensch, Cedric Lorenz, Martin Preiss, Tom Richter, Philip Klemmer, Anastacia Bohannon, Christoph Lippert

    “…The data also permit examining the safety of extreme dietary sodium reduction.The database has numerous strengths (large patient population; extensive, long-term measurements and the use of UCl excretion to document dietary adherence) and limitations (missing data; temporal changes in methodologies over 50 years and lack of control subjects).Conclusion The RDDP database allows exploration of the effects of a diet extremely low in sodium, protein, fat and cholesterol on health indicators and patient survival. …”
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