University of Kansas

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.

Transverse-Momentum and Pseudorapidity Distributions of Charged Hadrons in pp Collisions at root s=7 TeV

Abstract: Charged-hadron transverse-momentum and pseudorapidity distributions in proton-proton collisions at root s = 7 TeV are measured with the inner tracking system of the CMS detector at the LHC. The charged-hadron yield is obtained by counting the number of reconstructed hits, hit pairs, and fully reconstructed charged-particle tracks. The combination of the three methods gives a charged-particle multiplicity per unit of pseudorapidity dN(ch)/d eta vertical bar(vertical bar eta vertical bar<0.5) = 5.78 +/- 0.01(stat) +/- 0.23(stat) for non-single-diffractive events, higher than predicted by commonly used models. The relative increase in charged-particle multiplicity from root s = 0.9 to 7 TeV is [66.1 +/- 1.0(stat) +/- 4.2(syst)]%. The mean transverse momentum is measured to be 0.545 +/- 0.005(stat) +/- 0.015(syst) GeV/c. The results are compared with similar measurements at lower energies.

Measurement of psychological disorders using cognitive diagnosis models.

Abstract: Cognitive diagnosis models are constrained (multiple classification) latent class models that characterize the relationship of questionnaire responses to a set of dichotomous latent variables. Having emanated from educational measurement, several aspects of such models seem well suited to use in psychological assessment and diagnosis. This article presents the development of a new cognitive diagnosis model for use in psychological assessment--the DINO (deterministic input; noisy "or" gate) model--which, as an illustrative example, is applied to evaluate and diagnose pathological gamblers. As part of this example, a demonstration of the estimates obtained by cognitive diagnosis models is provided. Such estimates include the probability an individual meets each of a set of dichotomous Diagnostic and Statistical Manual of Mental Disorders (text revision [DSM-IV-TR]; American Psychiatric Association, 2000) criteria, resulting in an estimate of the probability an individual meets the DSM-IV-TR definition for being a pathological gambler. Furthermore, a demonstration of how the hypothesized underlying factors contributing to pathological gambling can be measured with the DINO model is presented, through use of a covariance structure model for the tetrachoric correlation matrix of the dichotomous latent variables representing DSM-IV-TR criteria.

A Non-arbitrary Method of Identifying and Scaling Latent Variables in SEM and MACS Models

Abstract: A non-arbitrary method for the identification and scale setting of latent variables in general structural equation modeling is introduced This particular technique provides identical model fit as traditional methods (eg, the marker variable method), but it allows one to estimate the latent parameters in a nonarbitrary metric that reflects the metric of the measured indicators This technique, therefore, is particularly useful for mean and covariance structures (MACS) analyses, where the means of the indicators and latent constructs are of key interest By introducing this alternative method of identification and scale setting, researchers are provided with an additional tool for conducting MACS analyses that provides a meaningful and nonarbitrary scale for the estimates of the latent variable parameters Importantly, this tool can be used with single-group single-occasion models as well as with multiple-group models, multiple-occasion models, or both

An additional antecedent of empathic concern: valuing the welfare of the person in need.

Abstract: Two experiments examined the role of valuing the welfare of a person in need as an antecedent of empathic concern. Specifically, these experiments explored the relation of such valuing to a well-known antecedent--perspective taking. In Experiment 1, both perspective taking and valuing were manipulated, and each independently increased empathic concern, which, in turn, increased helping behavior. In Experiment 2, only valuing was manipulated. Manipulated valuing increased measured perspective taking and, in part as a result, increased empathic concern, which, in turn, increased helping. Valuing appears to be an important, largely overlooked, situational antecedent of feeling empathy for a person in need.