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Institution

University of Kansas

EducationLawrence, 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.


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Book
26 Feb 2013
TL;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

Journal ArticleDOI
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

Journal ArticleDOI
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

Journal ArticleDOI
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

Journal ArticleDOI
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

NameH-indexPapersCitations
Gordon H. Guyatt2311620228631
Krzysztof Matyjaszewski1691431128585
Wei Li1581855124748
David Tilman158340149473
Tomas Hökfelt158103395979
Pete Smith1562464138819
Daniel J. Rader1551026107408
Melody A. Swartz1481304103753
Kevin Murphy146728120475
Carlo Rovelli1461502103550
Stephen Sanders1451385105943
Marco Zanetti1451439104610
Andrei Gritsan1431531135398
Gunther Roland1411471100681
Joseph T. Hupp14173182647
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202391
2022358
20214,211
20204,204
20193,766
20183,485