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Trait Models (trait + models)
Selected AbstractsSkills Diagnosis Using IRT-Based Continuous Latent Trait ModelsJOURNAL OF EDUCATIONAL MEASUREMENT, Issue 4 2007William Stout This article summarizes the continuous latent trait IRT approach to skills diagnosis as particularized by a representative variety of continuous latent trait models using item response functions (IRFs). First, several basic IRT-based continuous latent trait approaches are presented in some detail. Then a brief summary of estimation, model checking, and assessment scoring aspects are discussed. Finally, the University of California at Berkeley multidimensional Rasch-model-grounded SEPUP middle school science-focused embedded assessment project is briefly described as one significant illustrative application. [source] Lexical studies of Filipino person descriptors: adding personality-relevant social and physical attributesEUROPEAN JOURNAL OF PERSONALITY, Issue 4 2008Shellah Myra Imperio Abstract Lexical studies have focused on traits. In the Filipino language, we investigated whether additional dimensions can be identified when personality-relevant terms for social roles, statuses and effects, plus physical attributes, are included. Filipino students (N,=,496) rated themselves on 268 such terms, plus 253 markers of trait and evaluative dimensions. We identified 10 dimensions of social and physical attributes,Prominence, Uselessness, Attractiveness, Respectability, Uniqueness, Destructiveness, Presentableness, Strength, Dangerousness and Charisma. Most of these dimensions did not correspond in a one-to-one manner to Filipino or alternative trait models (Big Five, HEXACO, ML7). However, considerable redundancy was observed between the social and physical attribute dimensions and trait and evaluative dimensions. Thus, social and physical attributes communicate information about personality traits, and vice versa. Copyright © 2008 John Wiley & Sons, Ltd. [source] Limits of fine-mapping a quantitative traitGENETIC EPIDEMIOLOGY, Issue 2 2003Larry D. Atwood Abstract Once a significant linkage is found, an important goal is reducing the error in the estimated location of the linked locus. A common approach to reducing location error, called fine-mapping, is the genotyping of additional markers in the linked region to increase the genetic information. The utility of fine-mapping for quantitative trait linkage analysis is largely unknown. To explore this issue, we performed a fine-mapping simulation in which the region containing a significant linkage at a 10-centiMorgan (cM) resolution was fine-mapped at 2, 1, and 0.5 cM. We simulated six quantitative trait models in which the proportion of variation due to the quantitative trait locus (QTL) ranged from 0.20,0.90. We used four sampling designs that were all combinations of 100 and 200 families of sizes 5 and 7. Variance components linkage analysis (Genehunter) was performed until 1,000 replicates were found with a maximum lodscore greater than 3.0. For each of these 1,000 replications, we repeated the linkage analysis three times: once for each of the fine-map resolutions. For the most realistic model, reduction in the average location error ranged from 3,15% for 2-cM fine-mapping and from 3,18% for 1-cM fine-mapping, depending on the number of families and family size. Fine-mapping at 0.5 cM did not differ from the 1-cM results. Thus, if the QTL accounts for a small proportion of the variation, as is the case for realistic traits, fine-mapping has little value. Genet Epidemiol 24:99,106, 2003. © 2003 Wiley-Liss, Inc. [source] Properties of random regression models using linear splinesJOURNAL OF ANIMAL BREEDING AND GENETICS, Issue 2 2006I. Misztal Summary Properties of random regression models using linear splines (RRMS) were evaluated with respect to scale of parameters, numerical properties, changes in variances and strategies to select the number and positions of knots. Parameters in RRMS are similar to those in multiple trait models with traits corresponding to points at knots. RRMS have good numerical properties because of generally superior numerical properties of splines compared with polynomials and sparser system of equations. These models also contain artefacts in terms of depression of variances and predictions in the middle of intervals between the knots, and inflation of predictions close to knots; the artefacts become smaller as correlations corresponding to adjacent knots increase. The artefacts can be greatly reduced by a simple modification to covariables. With the modification, the accuracy of RRMS increases only marginally if the correlations between the adjacent knots are ,0.6. In practical analyses the knots for each effect in RRMS can be selected so that: (i) they cover the entire trajectory; (ii) changes in variances in intervals between the knots are approximately linear; and (iii) the correlations between the adjacent knots are at least 0.6. RRMS allow for simple and numerically stable implementations of genetic evaluations with artefacts present but transparent and easily controlled. [source] Skills Diagnosis Using IRT-Based Continuous Latent Trait ModelsJOURNAL OF EDUCATIONAL MEASUREMENT, Issue 4 2007William Stout This article summarizes the continuous latent trait IRT approach to skills diagnosis as particularized by a representative variety of continuous latent trait models using item response functions (IRFs). First, several basic IRT-based continuous latent trait approaches are presented in some detail. Then a brief summary of estimation, model checking, and assessment scoring aspects are discussed. Finally, the University of California at Berkeley multidimensional Rasch-model-grounded SEPUP middle school science-focused embedded assessment project is briefly described as one significant illustrative application. [source] Research Review: A new perspective on attention-deficit/hyperactivity disorder: emotion dysregulation and trait modelsTHE JOURNAL OF CHILD PSYCHOLOGY AND PSYCHIATRY AND ALLIED DISCIPLINES, Issue 9 2009Michelle M. Martel Attention-deficit/hyperactivity disorder (ADHD) is a common example of developmental psychopathology that might be able to be better understood by taking an emotion regulation perspective. As discussed herein, emotion regulation is understood to consist of two component processes, emotion (e.g., positive and negative emotionality) and regulation (e.g., effortful and reactive forms of control), which interact with one another at the behavioral level. Review of work to date suggests that the heterogeneous behavioral category of ADHD may encompass two distinct kinds of inputs: inattentive ADHD symptoms may be primarily associated with breakdowns in the regulation side, whereas hyperactivity-impulsive ADHD symptoms may be associated with breakdowns in the emotionality side. It is argued that breakdowns in control may be a signature for ADHD specifically, while increased negative emotionality may serve as non-specific risk factors for disruptive behavior disorders, explaining their comorbidity. Increased understanding of the interrelations and interactions of component emotion regulation processes may elucidate developmental, sex, and neural mechanisms of ADHD and associated comorbid disruptive disorders. [source] Identifying Modifier Loci in Existing Genome Scan DataANNALS OF HUMAN GENETICS, Issue 5 2008E. W. Daw Summary In many genetic disorders in which a primary disease-causing locus has been identified, evidence exists for additional trait variation due to genetic factors. These findings have led to studies seeking secondary ,modifier' loci. Identification of modifier loci provides insight into disease mechanisms and may provide additional screening and treatment targets. We believe that modifier loci can be identified by re-analysis of genome screen data while controlling for primary locus effects. To test this hypothesis, we simulated multiple replicates of typical genome screening data on to two real family structures from a study of hypertrophic cardiomyopathy. With this marker data, we simulated two trait models with characteristics similar to one measure of hypertrophic cardiomyopathy. Both trait models included 3 genes. In the first, the trait was influenced by a primary gene, a secondary ,modifier' gene, and a third very small effect gene. In the second, we modeled an interaction between the first two genes. We examined power and false positive rates to map the secondary locus while controlling for the effect of the primary locus with two types of analyses. First, we examined Monte Carlo Markov chain (MCMC) simultaneous segregation and linkage analysis as implemented in Loki, for which we calculated two scoring statistics. Second, we calculated LOD scores using an individual-specific liability class based on the quantitative trait value. We found that both methods produced scores that are significant on a genome-wide level in some replicates. We conclude that mapping of modifier loci in existing samples is possible with these methods. [source] | |||||||||||||