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, Large Hadron Collider, Health care, Cancer
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26 Feb 2013TL;DR: In this article, the authors present a taxonomy of indicators and constructions for measuring emotional and physical states of a person in a group of individuals, including bullying, bullying, and homophobic teasing.
Abstract: Prologue. A Personal Introduction and What to Expect. How Statistics Came into my Life. My Approach to the Book. Key Features of the Book. Overview of the Book. Datasets and Measures Used. My Dataset with the Inventory Felt Energy and Emotion in Life (I FEEL) Measure. The I FEEL. Gallagher and Johnson's MIDUS Example. Neuroticism. Negative Affect. Dorothy Espelage's Bullying and Victimization Examples. Peer Victimization. Substance Use. Family Conflict. Family Closeness. Bullying. Homophobic Teasing. Overdue Gratitude. Prophylactic Apologies. Part I: Overview and SEM Foundations. An Overview of the Conceptual Foundations of SEM. Concepts, Constructs, and Indicators. From Concepts to Constructs to Indicators to Good Models. Sources of Variance in Measurement. Classical Test Theorem. Expanding Classical Test Theorem. Characteristics of Indicators and Constructs. Types of Indicators and Constructs. Categorical Versus Metrical Indicators and Constructs. Types of Correlation Coefficients that can be Modeled. A Simple Taxonomy of Indicators and Their Roles. Rescaling Variables. Parceling. What Changes and How? Some Advice for SEM Programming. Philosophical Issues and How I Approach Research. Summary. Key Terms and Concepts Introduced in This Chapter. Recommended Readings. Part II: Design Issues in Longitudinal Studies. Timing of Measurements and Conceptualizing Time. Cross-Sectional Design. Single-Cohort Longitudinal Design. Cross-Sequential Design. Cohort-Sequential Design. Time-Sequential Design. Other Validity Concerns. Temporal Design. Lags Within the Interval of Measurement. Episodic and Experiential Time. Missing Data Imputation and Planned Missing Designs. Missing Data Mechanisms. Recommendations and Caveats. Planned Missing Data Designs in Longitudinal Research. Modeling Developmental Processes in Context. Summary. Key Terms and Concepts Introduced in this Chapter. Recommended Readings. Part III: The Measurement Model. Drawing and Labeling Conventions. Defining the Parameters of a Construct. Scale Setting. Identification. Adding Means to the Model: Scale Setting and Identification with Means. Adding a Longitudinal Component to the CFA Model. Adding Phantom Constructs to the CFA Model. Summary. Key Terms and Concepts Introduced in this Chapter. Recommended Readings. Part IV: Model Fit, Sample Size, and Power. Model Fit and Types of Fit Indices. Statistical Rationale. Modeling Rationale. The Longitudinal Null Model. Summary and Cautions. Sample Size. Power. Summary. Key Terms and Concepts Introduced in this Chapter. Recommended Readings. Part V: The Longitudinal CFA Model. Factorial Invariance. A Small (Nearly Perfect) Data Example. Configural Factorial Invariance. Weak Factorial Invariance. Strong Factorial Invariance. Evaluating Invariance Constraints. Model Modification. Partial Invariance. A Larger Example Followed by Tests of the Latent Construct Relations. Testing the Latent Construct Parameters. An Application of a Longitudinal SEM to a Repeated-Measures Experiment. Summary. Key Terms and Concepts Introduced in this Chapter. Recommended Readings. Part VI: Specifying and Interpreting a Longitudinal Panel Model. Basics of a Panel Model. The Basic Simplex Change Process. Building a Panel Model. Covariate/Control Variables. Building the Panel Model of Positive and Negative Affect. Illustrative Examples of Manel Models. A Simplex Model of Cognitive Development. Two Simplex Models of Non-Longitudinal Data. A Panel Model of Bullying and Homophobic Teasing. Summary. Key Terms and Concepts Introduced in this Chapter. Recommended Readings. Part VII: Multiple-Group Models. Multiple-Group Longitudinal SEM. Step 1: Estimate Missing Data and Evaluate the Descriptive Statistics. Step 2: Perform Any Supplemental Analysis to Rule Out Potential Confounds. Step 3: Fit an Appropriate Multiple-Group Longitudinal Null Model. Step 4: Fit the Configurally Invariant Model Across Time and Groups. Step 5: Test for Weak Factorial (Loadings) Invariance. Step 6: Test for Strong Factorial Invariance. Step 7: Test for Mean-Level Differences in the Latent Constructs. Step 8: Test for the Homogeneity of the Variance-Covariance Matrix Among the Latent Constructs. Step 9: Test the Longitudinal SEM Model in Each Group. A Dynamic P-Technique Multiple-Group Longitudinal Model. Summary. Key Terms and Concepts Introduced in this Chapter. Recommended Readings. Part VIII: Multilevel Growth Curves and SEM. Longitudinal Growth Curve Model. Multivariate Growth Curve Models. Multilevel Longitudinal Model. Summary. Key Terms and Concepts Introduced in this Chapter. Recommended Readings. Part IX: Mediation and Moderation. Making the Distinction Between Mediators and Moderators. Cross-Sectional Mediation. Half-Longitudinal Mediation. Full Longitudinal Mediation. Moderation. Summary. Key Terms and Concepts Introduced in this Chapter. Recommended Readings. Part X: Jambalaya: Complex Construct Representations and Decompositions. Multitrait-Multimethod Models. Pseudo-MTMM Models. Bifactor and Higher Order Factor Models. Contrasting Different Variance Decompositions. Digestif. Key Terms and Concepts Introduced in this Chapter. Recommended Readings.
2,126 citations
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Clark University1, National Institutes of Health2, Louisiana State University3, CABI4, Umeå University5, Field Museum of Natural History6, Duke University7, University of Minnesota8, University of Alabama9, Oregon State University10, Centraalbureau voor Schimmelcultures11, United States Department of Agriculture12, University of Tübingen13, Max Planck Society14, University of Florida15, Pennsylvania State University16, Aberystwyth University17, Complutense University of Madrid18, University of Oslo19, University of Hong Kong20, University of Tartu21, University of Gothenburg22, University of Kansas23, University of Maine24, University of Illinois at Urbana–Champaign25, Royal Ontario Museum26, Georgia State University27, Estonian University of Life Sciences28, Washington State University29, Nova Southeastern University30, Ludwig Maximilian University of Munich31, University of Western Ontario32, Uppsala University33, Brandon University34, Royal Botanic Garden Edinburgh35, State University of New York at Purchase36, Boise State University37, Cornell University38
TL;DR: A comprehensive phylogenetic classification of the kingdom Fungi is proposed, with reference to recent molecular phylogenetic analyses, and with input from diverse members of the fungal taxonomic community.
2,096 citations
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University of Pennsylvania1, University of Chicago2, University of Melbourne3, Emory University4, University of Cologne5, University of Kansas6, Medical University of Vienna7, Ohio State University8, University of California, San Francisco9, University of Texas MD Anderson Cancer Center10, Université de Montréal11, University of Minnesota12, McMaster University13, Royal Prince Alfred Hospital14, Karolinska Institutet15, University of Würzburg16, University of Michigan17, University of Oslo18, Novartis19, University of Lyon20
TL;DR: The chimeric antigen receptor (CAR) T-cell therapy tisagenlecleucel targets and eliminates CD19-expressing B cells and showed efficacy against B-cell lymphomas in a single-center, phase 2a study.
Abstract: Background Patients with diffuse large B-cell lymphoma that is refractory to primary and second-line therapies or that has relapsed after stem-cell transplantation have a poor prognosis. The chimeric antigen receptor (CAR) T-cell therapy tisagenlecleucel targets and eliminates CD19-expressing B cells and showed efficacy against B-cell lymphomas in a single-center, phase 2a study. Methods We conducted an international, phase 2, pivotal study of centrally manufactured tisagenlecleucel involving adult patients with relapsed or refractory diffuse large B-cell lymphoma who were ineligible for or had disease progression after autologous hematopoietic stem-cell transplantation. The primary end point was the best overall response rate (i.e., the percentage of patients who had a complete or partial response), as judged by an independent review committee. Results A total of 93 patients received an infusion and were included in the evaluation of efficacy. The median time from infusion to data cutoff was 14 ...
2,086 citations
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TL;DR: The database will be useful for investigators interested in cuing, priming, recognition, network theory, linguistics, and implicit testing applications, and for evaluating the predictive value of free association probabilities as compared with other measures, such as similarity ratings and co-occurrence norms.
Abstract: Preexisting word knowledge is accessed in many cognitive tasks, and this article offers a means for indexing this knowledge so that it can be manipulated or controlled. We offer free association data for 72,000 word pairs, along with over a million entries of related data, such as forward and backward strength, number of competing associates, and printed frequency. A separate file contains the 5,019 normed words, their statistics, and thousands of independently normed rhyme, stem, and fragment cues. Other files provide n x n associative networks for more than 4,000 words and a list of idiosyncratic responses for each normed word. The database will be useful for investigators interested in cuing, priming, recognition, network theory, linguistics, and implicit testing applications. They also will be useful for evaluating the predictive value of free association probabilities as compared with other measures, such as similarity ratings and co-occurrence norms. Of several procedures for measuring preexisting strength between two words, the best remains to be determined. The norms may be downloaded from www.psychonomic.org/archive/.
2,012 citations
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TL;DR: The results quantify a trigger leading to rapid, drought-induced die-off of overstory woody plants at subcontinental scale and highlight the potential for such die-offs to be more severe and extensive for future global-change-type drought under warmer conditions.
Abstract: Future drought is projected to occur under warmer temperature conditions as climate change progresses, referred to here as global-change-type drought, yet quantitative assessments of the triggers and potential extent of drought-induced vegetation die-off remain pivotal uncertainties in assessing climate-change impacts. Of particular concern is regional-scale mortality of overstory trees, which rapidly alters ecosystem type, associated ecosystem properties, and land surface conditions for decades. Here, we quantify regional-scale vegetation die-off across southwestern North American woodlands in 2002-2003 in response to drought and associated bark beetle infestations. At an intensively studied site within the region, we quantified that after 15 months of depleted soil water content, >90% of the dominant, overstory tree species (Pinus edulis, a pinon) died. The die-off was reflected in changes in a remotely sensed index of vegetation greenness (Normalized Difference Vegetation Index), not only at the intensively studied site but also across the region, extending over 12,000 km2 or more; aerial and field surveys confirmed the general extent of the die-off. Notably, the recent drought was warmer than the previous subcontinental drought of the 1950s. The limited, available observations suggest that die-off from the recent drought was more extensive than that from the previous drought, extending into wetter sites within the tree species' distribution. Our results quantify a trigger leading to rapid, drought-induced die-off of overstory woody plants at subcontinental scale and highlight the potential for such die-off to be more severe and extensive for future global-change-type drought under warmer conditions.
1,992 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 |