A realistic situation, proposed from data generated within the GeOrder Simulator to elicit the statistical reasoning.

Construction and handling of important statistical concepts, such as statistical estimators computing, or organization of data in graphs and tables, are oftenly taught in a strict algorithmic manner. As consequence, students abilities regarding experimentation, data sampling, data collecting, data organization and results interpretation, are limited and their solutions lack of statistical sustain. In this work, in study class consisting in students of the Logistic and Transport Engineering program, it is developed and implemented a realistic problem situation: a sales e-commerce company has to decide, by analyzing received orders, whether to implement its own delivery system or hire a third-party delivery company. The software GeOrder Simulator is employed to generate random data for weight and location of simulated orders and the data are presented to students in tabular and iconic, onto a map geolocation, semiotic representation registers. The research aim of this work, is to analyze, from the perspective of Semiotic Representation Theory, the effect onto the statistical reasoning that is provoked in students when they solve the realistic problem situation with the data generated by the GeOrder Simulator. The results show that the addressing of the realistic problem situation together with the usage of the GeOrder Simulator, elicited the statistical reasoning in the students since it is observed the integration of statistical concepts within their argumentation, by means of the coordination of tabular, graphical and numerical semiotic representation registers.

Propuesta de un modelo de la ideación suicida en estudiantes de Medicina en Colombia: un estudio de simulación / Proposal for a Model of Suicidal Ideation in Medical Students in Colombia: A Simulation Study

RESUMEN La conducta suicida es un problema de salud pública mundial, y una población en la que se presentan altos índices de prevalencia es la de estudiantes de Medicina, especialmente en el componente de ideación. Diversos modelos han intentado explicarla, pero son pocos los estudios inferenciales en población colombiana. Los modelos de ecuaciones estructurales utilizados en ciencias sociales resultan apropiados para explicar este problema y su poder analítico permite realizar generalizaciones con cierto grado de precisión. Estos análisis requieren una gran cantidad de datos para una estimación robusta, lo que limita su utilidad cuando hay restricciones para acceder a los datos, como sucede actualmente a causa de la COVID-19, y una cuestión que destaca en estos modelos es la evaluación del ajuste. Mediante un conjunto de 1.200 datos simulados, se encontró un adecuado ajuste del modelo a los datos (x2 524) = 1.732, 300; p< 0, 001; CFI = 0,97; GFI0= 0,97; TLI = 0,97; RMSEA = 0,04 [0,042-0,046]; SRMR = 0,06) para los predictores depresión y carga percibida, cuyos análisis se realizaron en el programa JASP. Se discute el papel de la pertenencia frustrada, la conveniencia del instrumento para evaluarla y consideraciones de seguimiento, evaluación e intervención de la ideación suicida en estudiantes de Medicina. © 2020 Asociación Colombiana de Psiquiatría. Publicado por Elsevier España, S.L.U. Todos los derechos reservados.

ABSTRACT Suicidal behavior is a global public health problem, and one population group with high prevalence rates is medical students, especially in the ideation component. Various models have tried to explain it, but there are few inferential studies in the Colombian population. The structural equation models used in controlled social sciences to explain this problem and their analytical power allow generalizations to be made with a certain degree of precision. These analyses require a large amount of data for robust estimation, which limits their usability when there are restrictions to access the data, as is the case today due to Covid-19, and a question that stands out in these models is the evaluation of the fit. Through a set of 1,200 simulated data, an appropriate model fit was found (x2 524) = 1.732, 300; p< 0, 001, CFI = 0.97, GFI = 0.97, TLI = 0.97, RMSEA = 0.04[0.042-0.046], SRMR = 0.06) for the predictors of depression and perceived burdensomeness, which were analyzed using the JASP pro-gram. The role of thwarted belongingness is discussed, as well as the appropriateness of the assessment instrument used to evaluate it an considerations regarding suicidal ideation monitoring, evaluation and intervention in medical students.

Proposal for a Model of Suicidal Ideation in Medical Students in Colombia: A Simulation Study.

Suicidal behaviour is a global public health problem, and one population group with high prevalence rates is medical students, especially in the ideation component. Various models have tried to explain it, but there are few inferential studies in the Colombian population. The structural equation models used in controlled social sciences to explain this problem and their analytical power allow generalisations to be made with a certain degree of precision. These analyses require a large amount of data for robust estimation, which limits their usability when there are restrictions to access the data, as is the case today due to Covid-19, and a question that stands out in these models is the evaluation of the fit. Through a set of 1,200 simulated data, an appropriate model fit was found (x5242 = 1.732,300, p < 0,001, CFI = 0.97, GFI = 0.97, TLI = 0.97, RMSEA = 0.04[0.042-o.046], SRMR = 0.06) for the predictors of depression and perceived burdensomeness, which were analysed using the JASP program. The role of thwarted belongingness is discussed, as well as the appropriateness of the assessment instrument used to evaluate it an considerations regarding suicidal ideation monitoring, evaluation and intervention in medical students.

Proposal for a Model of Suicidal Ideation in Medical Students in Colombia: A Simulation Study. / Propuesta de un modelo de la ideación suicida en estudiantes de Medicina en Colombia: un estudio de simulación.

Suicidal behaviour is a global public health problem, and one population group with high prevalence rates is medical students, especially in the ideation component. Various models have tried to explain it, but there are few inferential studies in the Colombian population. The structural equation models used in controlled social sciences to explain this problem and their analytical power allow generalisations to be made with a certain degree of precision. These analyses require a large amount of data for robust estimation, which limits their usability when there are restrictions to access the data, as is the case today due to Covid-19, and a question that stands out in these models is the evaluation of the fit. Through a set of 1,200 simulated data, an appropriate model fit was found (x5242=1.732,300;p<0,001, CFI = 0.97, GFI = 0.97, TLI = 0.97, RMSEA = 0.04[0.042-0.046], SRMR = 0.06) for the predictors of depression and perceived burdensomeness, which were analysed using the JASP program. The role of thwarted belongingness is discussed, as well as the appropriateness of the assessment instrument used to evaluate it an considerations regarding suicidal ideation monitoring, evaluation and intervention in medical students.

Effects of statistical models and items difficulties on making trait-level inferences: A simulation study / Efeitos dos modelos estatísticos e da dificuldade dos itens na avaliação do nível de traço latente dos indivíduos: Um estudo de simulação de dados

Researchers dealing with the task of estimating locations of individuals on continuous latent variables may rely on several statistical models described in the literature. However, weighting costs and benefits of using one specific model over alternative models depends on empirical information that is not always clearly available. Therefore, the aim of this simulation study was to compare the performance of seven popular statistical models in providing adequate latent trait estimates in conditions of items difficulties targeted at the sample mean or at the tails of the latent trait distribution. Results suggested an overall tendency of models to provide more accurate estimates of true latent scores when using items targeted at the sample mean of the latent trait distribution. Rating Scale Model, Graded Response Model, and Weighted Least Squares Mean- and Variance-adjusted Confirmatory Factor Analysis yielded the most reliable latent trait estimates, even when applied to inadequate items for the sample distribution of the latent variable. These findings have important implications concerning some popular methodological practices in Psychology and related areas. (AU)

Pesquisadores interessados em estimar a localização de indivíduos em variáveis latentes contínuas podem se beneficiar de diversos modelos estatísticos disponíveis na literatura. Entretanto, ponderar os custos e os benefícios de usar um modelo em detrimento de outros depende de informações empíricas que nem sempre estão diretamente disponíveis. Em virtude disso, o objetivo deste estudo foi comparar o desempenho de sete modelos estatísticos populares quanto a proporcionar adequadas estimativas de traço latente em condições de itens com dificuldades condizentes com a distribuição latente amostral versus apenas condizentes com as caudas dessa distribuição. Os resultados sugeriram uma tendência de todos os modelos de proporcionar estimativas mais precisas ao serem usados itens adequados para o nível de traço latente da amostra. Os modelos da Teoria de Resposta ao Item Rating Scale e Graded Response e a análise fatorial confirmatória com estimação Weighted Least Squares Mean- and Variance-adjusted forneceram as estimativas mais fidedignas de traço latente, mesmo quando os itens utilizados, de fato, correspondiam ao nível latente de poucos casos da amostra. Os resultados possuem importantes implicações no que diz respeito a algumas práticas metodológicas populares na Psicologia e em áreas próximas. (AU)