Institution
University of Kansas
Education•Lawrence, Kansas, United States•
About: University of Kansas is a education organization based out in Lawrence, Kansas, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 38183 authors who have published 81381 publications receiving 2986312 citations. The organization is also known as: KU & Univ of Kansas.
Topics: Population, Poison control, Health care, Context (language use), Cancer
Papers published on a yearly basis
Papers
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TL;DR: A simulation study compared the performance of robust normal theory maximum likelihood (ML) and robust categorical least squares (cat-LS) methodology for estimating confirmatory factor analysis models with ordinal variables and found cat-LS to be more sensitive to sample size and to violations of the assumption of normality of the underlying continuous variables.
Abstract: A simulation study compared the performance of robust normal theory maximum likelihood (ML) and robust categorical least squares (cat-LS) methodology for estimating confirmatory factor analysis models with ordinal variables. Data were generated from 2 models with 2-7 categories, 4 sample sizes, 2 latent distributions, and 5 patterns of category thresholds. Results revealed that factor loadings and robust standard errors were generally most accurately estimated using cat-LS, especially with fewer than 5 categories; however, factor correlations and model fit were assessed equally well with ML. Cat-LS was found to be more sensitive to sample size and to violations of the assumption of normality of the underlying continuous variables. Normal theory ML was found to be more sensitive to asymmetric category thresholds and was especially biased when estimating large factor loadings. Accordingly, we recommend cat-LS for data sets containing variables with fewer than 5 categories and ML when there are 5 or more categories, sample size is small, and category thresholds are approximately symmetric. With 6-7 categories, results were similar across methods for many conditions; in these cases, either method is acceptable.
1,472 citations
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TL;DR: DendroPy uses a splits-hash mapping to perform rapid calculations of tree distances, similarities and shape under various metrics, and contains rich simulation routines to generate trees under a number of different phylogenetic and coalescent models.
Abstract: Summary: DendroPy is a cross-platform library for the Python programming language that provides for object-oriented reading, writing, simulation and manipulation of phylogenetic data, with an emphasis on phylogenetic tree operations. DendroPy uses a splits-hash mapping to perform rapid calculations of tree distances, similarities and shape under various metrics. It contains rich simulation routines to generate trees under a number of different phylogenetic and coalescent models. DendroPy’s data simulation and manipulation facilities, in conjunction with its support of a broad range of phylogenetic data formats (NEXUS, Newick, PHYLIP, FASTA, NeXML, etc.), allow it to serve a useful role in various phyloinformatics and phylogeographic pipelines. Availability: The stable release of the library is available for download and automated installation through the Python Package Index site (http://pypi.python.org/pypi/DendroPy), while the active development source code repository is available to the public from GitHub (http://github.com/jeetsukumaran/DendroPy).
1,462 citations
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Stanford University1, Indiana University – Purdue University Indianapolis2, Emory University3, University of Oklahoma4, University of Kansas5, Cornell University6, Thomas Jefferson University7, Marshfield Clinic8, Veterans Health Administration9, University of California, Los Angeles10, St. Joseph's Hospital and Medical Center11, Rush University Medical Center12, University of Pennsylvania13, University of California, San Francisco14, University of Virginia15, Columbia University16, Harvard University17, Medtronic plc18
TL;DR: A multicenter, double‐blind, randomized trial of bilateral stimulation of the anterior nuclei of the thalamus for localization‐related epilepsy is reported.
Abstract: Summary
Purpose: We report a multicenter, double-blind, randomized trial of bilateral stimulation of the anterior nuclei of the thalamus for localization-related epilepsy
Methods: Participants were adults with medically refractory partial seizures, including secondarily generalized seizures Half received stimulation and half no stimulation during a 3-month blinded phase; then all received unblinded stimulation
Results: One hundred ten participants were randomized Baseline monthly median seizure frequency was 195 In the last month of the blinded phase the stimulated group had a 29% greater reduction in seizures compared with the control group, as estimated by a generalized estimating equations (GEE) model (p = 0002) Unadjusted median declines at the end of the blinded phase were 145% in the control group and 404% in the stimulated group Complex partial and “most severe” seizures were significantly reduced by stimulation By 2 years, there was a 56% median percent reduction in seizure frequency; 54% of patients had a seizure reduction of at least 50%, and 14 patients were seizure-free for at least 6 months Five deaths occurred and none were from implantation or stimulation No participant had symptomatic hemorrhage or brain infection Two participants had acute, transient stimulation-associated seizures Cognition and mood showed no group differences, but participants in the stimulated group were more likely to report depression or memory problems as adverse events
Discussion: Bilateral stimulation of the anterior nuclei of the thalamus reduces seizures Benefit persisted for 2 years of study Complication rates were modest Deep brain stimulation of the anterior thalamus is useful for some people with medically refractory partial and secondarily generalized seizures
1,444 citations
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University of Connecticut Health Center1, University of California, Berkeley2, Lawrence Berkeley National Laboratory3, National Institutes of Health4, Washington University in St. Louis5, Indiana University6, Cold Spring Harbor Laboratory7, Life Technologies8, Amgen9, Stowers Institute for Medical Research10, University of Kansas11, University of California, Santa Cruz12, Howard Hughes Medical Institute13, Affymetrix14
TL;DR: 111,195 new elements are identified, including thousands of genes, coding and non-coding transcripts, exons, splicing and editing events and inferred protein isoforms that previously eluded discovery using established experimental, prediction and conservation-based approaches.
Abstract: Drosophila melanogaster is one of the most well studied genetic model organisms; nonetheless, its genome still contains unannotated coding and non-coding genes, transcripts, exons and RNA editing sites. Full discovery and annotation are pre-requisites for understanding how the regulation of transcription, splicing and RNA editing directs the development of this complex organism. Here we used RNA-Seq, tiling microarrays and cDNA sequencing to explore the transcriptome in 30 distinct developmental stages. We identified 111,195 new elements, including thousands of genes, coding and non-coding transcripts, exons, splicing and editing events, and inferred protein isoforms that previously eluded discovery using established experimental, prediction and conservation-based approaches. These data substantially expand the number of known transcribed elements in the Drosophila genome and provide a high-resolution view of transcriptome dynamics throughout development.
1,427 citations
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TL;DR: This component analysis used meta-analytic techniques to synthesize the results of 77 published evaluations of parent training programs to enhance behavior and adjustment in children aged 0–7 and found components consistently associated with larger effects included increasing positive parent–child interactions and emotional communication skills.
Abstract: This component analysis used meta-analytic techniques to synthesize the results of 77 published evaluations of parent training programs (i.e., programs that included the active acquisition of parenting skills) to enhance behavior and adjustment in children aged 0-7. Characteristics of program content and delivery method were used to predict effect sizes on measures of parenting behaviors and children's externalizing behavior. After controlling for differences attributable to research design, program components consistently associated with larger effects included increasing positive parent-child interactions and emotional communication skills, teaching parents to use time out and the importance of parenting consistency, and requiring parents to practice new skills with their children during parent training sessions. Program components consistently associated with smaller effects included teaching parents problem solving; teaching parents to promote children's cognitive, academic, or social skills; and providing other, additional services. The results have implications for selection and strengthening of existing parent training programs.
1,418 citations
Authors
Showing all 38401 results
Name | H-index | Papers | Citations |
---|---|---|---|
Gordon H. Guyatt | 231 | 1620 | 228631 |
Krzysztof Matyjaszewski | 169 | 1431 | 128585 |
Wei Li | 158 | 1855 | 124748 |
David Tilman | 158 | 340 | 149473 |
Tomas Hökfelt | 158 | 1033 | 95979 |
Pete Smith | 156 | 2464 | 138819 |
Daniel J. Rader | 155 | 1026 | 107408 |
Melody A. Swartz | 148 | 1304 | 103753 |
Kevin Murphy | 146 | 728 | 120475 |
Carlo Rovelli | 146 | 1502 | 103550 |
Stephen Sanders | 145 | 1385 | 105943 |
Marco Zanetti | 145 | 1439 | 104610 |
Andrei Gritsan | 143 | 1531 | 135398 |
Gunther Roland | 141 | 1471 | 100681 |
Joseph T. Hupp | 141 | 731 | 82647 |