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1.
Front Psychol ; 14: 1298534, 2023.
Artículo en Inglés | MEDLINE | ID: mdl-38222847

RESUMEN

Monte Carlo simulation is a common method of providing empirical evidence to verify statistics used in psychological studies. A representative set of conditions should be included in simulation studies. However, several recently published Monte Carlo simulation studies have not included the conditions of the null distribution of the statistic in their evaluations or comparisons of statistics and, therefore, have drawn incorrect conclusions. This present study proposes a design based on a common statistic evaluation procedure in psychology and machine learning, using a confusion matrix with four cells: true positive, true negative, false negative modified, and false positive modified. To illustrate this design, we employ an influential Monte Carlo simulation study by Trizano-Hermosilla and Alvarado (2016), which concluded that the Omega-indexed internal consistency should be preferred over other alternatives. Our results show that Omega can report an acceptable level of internal consistency (i.e., > 0.7) in a population with no relationship between every two items in some conditions, providing novel empirical evidence for comparing internal consistency indices.

2.
Autism ; 25(2): 516-528, 2021 02.
Artículo en Inglés | MEDLINE | ID: mdl-33153314

RESUMEN

LAY ABSTRACT: With professional training and regular opportunities to observe children interacting with their peers, preschool teachers are in a good position to notice children's autism spectrum disorder symptomatology. Yet even when a preschool teacher suspects that a child may have autism spectrum disorder, fear of false alarm may hold the teacher back from alerting the parents, let alone suggesting them to consider clinical assessment for the child. A valid and convenient screening tool can help preschool teachers make more informed and hence more confident judgment. We set out to develop a screening tool that capitalizes on peer interaction as a naturalistic "stress test" to identify children more likely than their peers to have autism spectrum disorder. A total of 304 3- to 4-year-olds were observed at school with an 84-item preliminary checklist; data-driven item reduction yielded a 13-item Classroom Observation Scale. The Classroom Observation Scale scores correlated significantly with Autism Diagnostic Observation Schedule-2 scores. To validate the scale, another 322 2- to 4-year-olds were screened using the Classroom Observation Scale. The screen-positive children and randomly selected typically developing peers were assessed for autism spectrum disorder 1.5 years later. The Classroom Observation Scale as used by teachers and researchers near preschool onset predicted autism spectrum disorder diagnoses 1.5 years later. This user-friendly 13-item Classroom Observation Scale enables teachers and healthcare workers with little or no clinical training to identify, with reliable and valid results, preschoolers more likely than their peers to have autism spectrum disorder.


Asunto(s)
Trastorno del Espectro Autista , Trastorno Autístico , Trastorno del Espectro Autista/diagnóstico , Preescolar , Humanos , Tamizaje Masivo , Padres , Maestros
3.
Front Psychol ; 9: 1657, 2018.
Artículo en Inglés | MEDLINE | ID: mdl-30254594

RESUMEN

In psychological science, there is an increasing concern regarding the reproducibility of scientific findings. For instance, Replication Project: Psychology (Open Science Collaboration, 2015) found that the proportion of successful replication in psychology was 41%. This proportion was calculated based on Cumming and Maillardet (2006) widely employed capture procedure (CPro) and capture percentage (CPer). Despite the popularity of CPro and CPer, we believe that using them may lead to an incorrect conclusion of (a) successful replication when the population effect sizes in the original and replicated studies are different; and (b) unsuccessful replication when the population effect sizes in the original and replicated studies are identical but their sample sizes are different. Our simulation results show that the performances of CPro and CPer become biased, such that researchers can easily make a wrong conclusion of successful/unsuccessful replication. Implications of these findings are considered in the conclusion.

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