179,121 research outputs found
sj-xlsx-4-jicm-10.1177_08850666211053793 - Supplemental material for Reverse Bayesian Implications of p-Values Reported in Critical Care Randomized Trials
No full textSupplemental material, sj-xlsx-4-jicm-10.1177_08850666211053793 for Reverse Bayesian Implications of p-Values Reported in Critical Care Randomized Trials by Sarah Nostedt and Ari R. Joffe in Journal of Intensive Care Medicine</p
sj-docx-2-jicm-10.1177_08850666211053793 - Supplemental material for Reverse Bayesian Implications of p-Values Reported in Critical Care Randomized Trials
No full textSupplemental material, sj-docx-2-jicm-10.1177_08850666211053793 for Reverse Bayesian Implications of p-Values Reported in Critical Care Randomized Trials by Sarah Nostedt and Ari R. Joffe in Journal of Intensive Care Medicine</p
sj-docx-1-jicm-10.1177_08850666211053793 - Supplemental material for Reverse Bayesian Implications of p-Values Reported in Critical Care Randomized Trials
No full textSupplemental material, sj-docx-1-jicm-10.1177_08850666211053793 for Reverse Bayesian Implications of p-Values Reported in Critical Care Randomized Trials by Sarah Nostedt and Ari R. Joffe in Journal of Intensive Care Medicine</p
sj-docx-3-jicm-10.1177_08850666211053793 - Supplemental material for Reverse Bayesian Implications of p-Values Reported in Critical Care Randomized Trials
No full textSupplemental material, sj-docx-3-jicm-10.1177_08850666211053793 for Reverse Bayesian Implications of p-Values Reported in Critical Care Randomized Trials by Sarah Nostedt and Ari R. Joffe in Journal of Intensive Care Medicine</p
sj-docx-3-jicm-10.1177_08850666221077203 - Supplemental material for Critical Care Randomized Trials Demonstrate Power Failure: A Low Positive Predictive Value of Findings in the Critical Care Research Field
No full textSupplemental material, sj-docx-3-jicm-10.1177_08850666221077203 for Critical Care Randomized Trials Demonstrate Power Failure: A Low Positive Predictive Value of Findings in the Critical Care Research Field by Sarah Nostedt and Ari R Joffe in Journal of Intensive Care Medicine</p
sj-docx-2-jicm-10.1177_08850666221077203 - Supplemental material for Critical Care Randomized Trials Demonstrate Power Failure: A Low Positive Predictive Value of Findings in the Critical Care Research Field
No full textSupplemental material, sj-docx-2-jicm-10.1177_08850666221077203 for Critical Care Randomized Trials Demonstrate Power Failure: A Low Positive Predictive Value of Findings in the Critical Care Research Field by Sarah Nostedt and Ari R Joffe in Journal of Intensive Care Medicine</p
sj-docx-1-jicm-10.1177_08850666221077203 - Supplemental material for Critical Care Randomized Trials Demonstrate Power Failure: A Low Positive Predictive Value of Findings in the Critical Care Research Field
No full textSupplemental material, sj-docx-1-jicm-10.1177_08850666221077203 for Critical Care Randomized Trials Demonstrate Power Failure: A Low Positive Predictive Value of Findings in the Critical Care Research Field by Sarah Nostedt and Ari R Joffe in Journal of Intensive Care Medicine</p
Appropriate Similarity Measures for Author Cocitation Analysis
No full textWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
A prospective study of (18)FDG PET in the prediction of relapse in patients with high risk clinical stage I (CS1) non-seminomatous germ cell cancer (NSGCT): MRC study TE22
No full text"Closing the R&D Gap, Evaluating the Sources of R&D Spending"
No full textBoth spending and tax policies have been implemented in the United States with the goal of stimulating private sector research and development (R&D). Karier questions whether current R&D policy, especially the research and experimentation tax credit, can contribute to closing the gap between nondefense expenditures on R&D in the United States and such expenditures in other countries, such as Japan and Germany. He also explores possible changes to our current R&D policy to make it more effective.
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