Search Results Heading

MBRLSearchResults

mbrl.module.common.modules.added.book.to.shelf
Title added to your shelf!
View what I already have on My Shelf.
Oops! Something went wrong.
Oops! Something went wrong.
While trying to add the title to your shelf something went wrong :( Kindly try again later!
Are you sure you want to remove the book from the shelf?
Oops! Something went wrong.
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
    Done
    Filters
    Reset
  • Discipline
      Discipline
      Clear All
      Discipline
  • Is Peer Reviewed
      Is Peer Reviewed
      Clear All
      Is Peer Reviewed
  • Series Title
      Series Title
      Clear All
      Series Title
  • Reading Level
      Reading Level
      Clear All
      Reading Level
  • Year
      Year
      Clear All
      From:
      -
      To:
  • More Filters
      More Filters
      Clear All
      More Filters
      Content Type
    • Item Type
    • Is Full-Text Available
    • Subject
    • Country Of Publication
    • Publisher
    • Source
    • Donor
    • Language
    • Place of Publication
    • Contributors
    • Location
71,287 result(s) for "Effectiveness studies"
Sort by:
From sample average treatment effect to population average treatment effect on the treated: combining experimental with observational studies to estimate population treatment effects
Randomized controlled trials (RCTs) can provide unbiased estimates of sample average treatment effects. However, a common concern is that RCTs may fail to provide unbiased estimates of population average treatment effects. We derive the assumptions that are required to identify population average treatment effects from RCTs. We provide placebo tests, which formally follow from the identifying assumptions and can assess whether they hold. We offer new research designs for estimating population effects that use non-randomized studies to adjust the RCT data. This approach is considered in a cost-effectiveness analysis of a clinical intervention: pulmonary artery catheterization.
Organizational behaviour in sport
\"What makes a sports organization successful? How can managers working in sport improve organizational effectiveness through strategic behaviour management? This comprehensive and accessible textbook addresses these important questions and examines the theories that underpin organizational analysis in sport. Helping both students and practitioners to understand the different types of behaviour that occur within a sports organization, it also demonstrates how to develop ways of managing behaviour more effectively for the benefit of all stakeholders. The book explores behaviour on individual, interpersonal, group and whole organization levels, and presents an evidence-based framework for analysis built around key concepts such as: - motivation, rewards and incentives - power, influence and leadership - conflict, disputes and grievances - anxiety, stress and alienation - equity, diversity and inclusion. With international case studies, learning objectives, review questions and guides to further reading included in every chapter, no other textbook develops critical skills or an awareness of ethical issues in such detail and depth. Organizational Behaviour in Sport is essential reading for all students and practitioners working in sport, leisure or recreation management.\" -- Provided by publisher.
Least cost analysis of social landscapes : archaeological case studies
A growing number of archaeologists are applying Geographic Information Science (GIS) technologies to their research problems and questions. Advances in GIS and its use across disciplines allows for collaboration and enables archaeologists to ask ever more sophisticated questions and develop increasingly elaborate models on numerous aspects of past human behavior. Least cost analysis (LCA) is one such avenue of inquiry. While least cost studies are not new to the social sciences in general, LCA is relatively new to archaeology; until now, there has been no systematic exploration of its use within the field. This edited volume presents a series of case studies illustrating the intersection of archaeology and LCA modeling at the practical, methodological, and theoretical levels. Designed to be a guidebook for archaeologists interested in using LCA in their own research, it presents a wide cross-section of practical examples for both novices and experts. The contributors to the volume showcase the richness and diversity of LCA’s application to archaeological questions, demonstrate that even simple applications can be used to explore sophisticated research questions, and highlight the challenges that come with injecting geospatial technologies into the archaeological research process.  
High-dimensional propensity scores improved the control of indication bias in surgical comparative effectiveness studies
The objective of the study is to evaluate the performance of high-dimensional propensity scores (hdPSs) for controlling indication bias as compared with propensity scores (PSs) in surgical comparative effectiveness studies. Patients who underwent interventional transcatheter aortic valve implantation (TAVI) or surgical aortic valve replacement (SAVR) between 2013 and 2017 were included from the French nationwide hospitals. At each hospital level, matched pairs of patients who underwent TAVI and SAVR were formed using PSs, considering 20 patient baseline characteristics, and hdPSs, considering the same patient characteristics and 300 additional variables from procedure and diagnosis codes the year before surgery. We compared death, reoperation, and stroke up to 3 years between TAVI and SAVR using Cox or Fine and Gray models. Before matching, 12 of 20 patient characteristics were imbalanced between the included patients who underwent TAVI and SAVR. No significant imbalance persisted after matching with both methods. Hazard ratio of 1-year death, reoperation, and stroke was 1.3 [1.1; 1.4], 1.6 [1.1; 2.4], and 1.4 [1.2; 1.7] for TAVI relative to SAVR with PSs (n = 9,498 pairs) and 1.1 [1.0; 1.3], 1.3 [0.8; 2.0], and 1.3 [1.0; 1.6] with hdPSs (n = 7,157). HdPS estimations were more consistent with results seen in randomized controlled trials. The HdPS is a promising alternative for the PS to control indication bias in comparative studies of surgical procedures. •The high-dimensional propensity score is an alternative for the propensity score.•Effective approach for controlling confounding by indication in surgical comparative effectiveness studies.•Estimations were more consistent with results seen in randomized controlled trials.
A pulmonary rehabilitation program reduces hospitalizations in chronic obstructive pulmonary disease patients: A cost-effectiveness study
BACKGROUND: Although pulmonary rehabilitation (PR) is recommended in patients with chronic obstructive pulmonary disease (COPD), there is a scarcity of data demonstrating the cost-effectiveness and effectiveness of PR in reducing exacerbations. METHODS: A quasi-experimental study in 200 patients with COPD was conducted to determine the number of exacerbations 1 year before and after their participation in a PR program. Quality of life was measured using the COPD assessment test and EuroQol-5D. The costs of the program and exacerbations were assessed the year before and after participation in the PR program. The incremental cost-effectiveness ratio (ICER) was estimated in terms of quality-adjusted life years (QALYs). RESULTS: The number of admissions, length of hospital stay, and admissions to the emergency department decreased after participation in the PR program by 48.2%, 46.6%, and 42.5%, respectively (P < 0.001 for all). Results on quality of life tests improved significantly (P < 0.001 for the two tests). The cost of PR per patient and the cost of pre-PR and post-PR exacerbations were €1867.7 and €7895.2 and €4201.9, respectively. The PR resulted in a cost saving of €1826 (total, €365,200) per patient/year, and the gain in QALYs was+0.107. ICER was −€17,056. The total cost was <€20,000/QALY in 78% of patients. CONCLUSIONS: PR contributes to reducing the number of exacerbations in patients with COPD, thereby slowing clinical deterioration. In addition, it is cost-effective in terms of QALYs.
Robustness of Multiple Imputation Methods for Missing Risk Factor Data from Electronic Medical Records for Observational Studies
Evaluating appropriate methodologies for imputation of missing outcome data from electronic medical records (EMRs) is crucial but lacking for observational studies. Using US EMR in people with type 2 diabetes treated over 12 and 24 months with dipeptidyl peptidase 4 inhibitors (DPP-4i, n  = 38,483) and glucagon-like peptide 1 receptor agonists (GLP-1RA, n  = 8,977), predictors of missingness of disease biomarker (HbA1c) were explored. Robustness of multiple imputation (MI) by chained equations, two-fold MI (MI-2F) and MI with Monte Carlo Markov Chain were compared to complete case analyses for drawing inferences. Compared to younger people (age quartile Q1), those in age quartile Q3 and Q4 were less likely to have missing HbA1c by 25–32% (range of OR CI: 0.55–0.88) at 6-month follow-up and by 26–39% (range of OR CI: 0.50–0.80) at 12-month follow-up. People with HbA1c ≥ 7.5% at baseline were 12% (OR CI: 0.83, 0.93) and 14% (OR CI: 0.77, 0.97) less likely to have missing data at 6-month follow-up in the DPP-4i and GLP-1RA groups, respectively. All imputation methods provided similar HbA1c distributions during follow-up as observed with complete case analyses. The clinical inferences based on absolute change in HbA1c and by proportion of people reducing HbA1c to a clinically acceptable level (≤ 7%) were also similar between imputed data and complete case analyses. MI-2F method provided marginally smaller mean difference between observed and imputed data with relatively smaller standard error of difference, compared to other methods, while evaluating for consistency through artificial within-sample analyses. The established MI techniques can be reliably employed for missing outcome data imputations in large EMR-based relational databases, leading to efficiently designing and drawing robust clinical inferences in pharmaco-epidemiological studies.