How causal is a reciprocal effect? Contrasting traditional and new methods to investigate the reciprocal effects model of self-concept and achievement

The relationship between students’ subject-specific academic self-concept and their academic achievement is one of the most widely researched topics in educational psychology. A large body of this research has considered cross-lagged panel models (CLPMs), oftentimes synonymously referred to as reciprocal effects models (REMs), as a gold standard to investigate the causal relations between the two variables and has reported evidence for a reciprocal relationship between self-concept and achievement. However, more recent methodological research questioned the plausibility of assumptions that need to be satisfied in order to interpret results from traditional CLPMs causally. In this substantive-methodological synergy, we aimed at contrasting traditional and more recently developed methods to investigate reciprocal effects of students’ academic self-concept and achievement. Specifically, we compared results from CLPMs, from full forward CLPMs (FF-CLPMs), and from random intercept CLPMs (RI-CLPMs) with two weighting approaches developed to study causal effects of continuous treatment variables. To estimate these different models, we used rich longitudinal data of N = 3,757 students from lower secondary schools in Germany. Results from CLPMs, FF-CLPMs, and weighting methods support the reciprocal effects model, particularly when considering math self-concept and grades. In contrast, results from the RI-CLPMs were less consistent. Implications from our study for the interpretation of effects from the different models and methods as well as for school motivation theory are discussed.

Evaluation of methods incorporating biological function and GWAS summary statistics to accelerate discovery

Where sufficiently large genome-wide association study (GWAS) samples are not currently available or feasible, methods that leverage increasing knowledge of the biological function of variants may illuminate discoveries without increasing sample size. We comprehensively evaluated 18 functional weighting methods for identifying novel associations. We assessed the performance of these methods using published results from multiple GWAS waves across each of five complex traits. Although no method achieved both high sensitivity and positive predictive value (PPV) for any trait, a subset of methods utilizing pleiotropy and expression quantitative trait loci nominated variants with high PPV (>75%) for multiple traits. Application of functionally weighting methods to enhance GWAS power for locus discovery is unlikely to circumvent the need for larger sample sizes in truly underpowered GWAS, but these results suggest that applying functional weighting to GWAS can accurately nominate additional novel loci from available samples for follow-up studies.

Comparative investigation of coherence factor weighting methods for an annular array photoacoustic microscope

To achieve fine visualization of the peripheral microvascular networks, we have developed a photoacoustic (PA) microscope equipped with a four-channel annular array transducer. The quality of PA images processed with Delay-and-Sum (DAS) method is degraded by off-axis signals. Thus, to achieve higher image quality for the PA microscope, this study evaluated the efficacy of the five coherence factor weighting methods: coherence factor, sign coherence factor, phase coherence factor, circular coherence factor, and vector coherence factor. Using PA signals acquired from a 100 µm microtube and the skin microvessels, we generated PA images with DAS and one of the weighting methods, and quantitatively evaluated the image quality by calculating the sharpness, contrast ratio, and contrast-to-noise ratio. The results showed the phase coherence factor and the vector coherence factor methods were more effective to clearly visualize the microvascular structure, in terms of vessel sharpening and noise suppression performances, than the other methods.

Performance Evaluation of Contract Employees Using the Best-Worst and Simple Additive Weighting Methods

All companies need qualified employees to ensure the continuity and progress of the company. Therefore, some companies are very selective in evaluating employee performance based on the criteria set by the company. However, because of the many criteria used in the assessment, a large number of contract employees to be evaluated, and the evaluation that must be proportional, the Human Resources department has difficulty evaluating the performance of contract employees. Therefore, this study aimed to develop a system for evaluating the performance of contract employees by integrating the Best-Worst (BW) and Simple Additive Weight (SAW) methods. The BW method is used to determine the weight of each criterion related to the performance appraisal of contract employees, and the SAW method is used to evaluate the performance of contract employees. The results showed that the system developed can provide a more proportional evaluation. So, this study contributes as a recommendation system for HR managers in determining eligible contract employees to have their work contracts extended based on criteria determined by the company.

Estimating Regionalized Hydrological Impacts of Climate Change Over Europe by Performance-Based Weighting of CORDEX Projections

Ensemble projections of future changes in discharge over Europe show large variation. Several methods for performance-based weighting exist that have the potential to increase the robustness of the change signal. Here we use future projections of an ensemble of three hydrological models forced with climate datasets from the Coordinated Downscaling Experiment - European Domain (EURO-CORDEX). The experiment is set-up for nine river basins spread over Europe that hold different climate and catchment characteristics. We evaluate the ensemble consistency and apply two weighting approaches; the Climate model Weighting by Independence and Performance (ClimWIP) that focuses on meteorological variables and the Reliability Ensemble Averaging (REA) in our study applied to discharge statistics per basin. For basins with a strong climate signal, in Southern and Northern Europe, the consistency in the set of projections is large. For rivers in Central Europe the differences between models become more pronounced. Both weighting approaches assign high weights to single General Circulation Models (GCMs). The ClimWIP method results in ensemble mean weighted changes that differ only slightly from the non-weighted mean. The REA method influences the weighted mean more, but the weights highly vary from basin to basin. We see that high weights obtained through past good performance can provide deviating projections for the future. It is not apparent that the GCM signal dominates the overall change signal, i.e., there is no strong intra GCM consistency. However, both weighting methods favored projections from the same GCM.

Assessment of Heatwave Vulnerability in Korea Considering Socio-economic Indices

The rising heatwave occurrences in recent times due to climate change have resulted in increased mortalities and socio-economic damage. Consequently, several studies have been conducted to examine heatwave vulnerability in Korea. However, most of these studies used the IPCC vulnerability framework and weighting techniques, such as the equal weight and AHP methods, which lacked objectivity in the process of calculating vulnerability. This study employed socio-economic data to measure the heatwave vulnerability index for individual local governments in Korea using the principal component analysis and entropy weighting methods. These techniques ensure that the aggregation of proxies and the weighting process remain objective, unlike previous studies. According to the obtained results, rural areas such as Jeollanam-do, Jeollabuk-do, Gyeongsangnam-do, and Gyeongsangbuk-do, and relatively decrepit urban areas demonstrated high vulnerability scores. In addition, a positive correlation was found between the calculated vulnerability index and mortalities from the recent heatwaves. The heatwave vulnerability index developed in this study can therefore be used to form effective heatwave response policies suited to the conditions of each local government.

Similarity Analysis of Methods for Objective Determination of Weights in Multi-Criteria Decision Support Systems

Decision support systems (DSS) are currently developing rapidly and are increasingly used in various fields. More often, those systems are inseparable from information-based systems and computer systems. Therefore, from a methodical point of view, the algorithms implemented in the DSS play a critical role. In this aspect, multi-criteria decision support (MCDA) methods are widely used. As research progresses, many MCDA methods and algorithms for the objective identification of the significance of individual criteria of the MCDA models were developed. In this paper, an analysis of available objective methods for criteria weighting is presented. Additionally, the authors presented the implementation of the system that provides easy and accessible weight calculations for any decision matrix with the possibility of comparing results of different weighting methods. The results of weighting methods were compared using carefully selected similarity coefficients to emphasise the correlation of the resulting weights. The performed research shows that every method should provide distinctive weights considering input data, emphasising the importance of choosing the correct method for a given multi-criteria decision support model and DSS.

Sistem Informasi Penilaian Kinerja Dosen dengan MVC Framework menggunakan Simple Additive Weighting Methods

Kinerja dosen dalam melaksanakan Tri Darma adalah suatu hal untuk mendukung pengambilan keputusan Pimpinan dalam kenaikan jabatan seorang Dosen di Perguruan Tinggi. Decisions Support System (DSS) dengan metode Simple Additive Weighting (SAW) dapat membantu dalam proses pengolahan data dan memperbaiki kekurangan seperti kesalahan dalam perhitungan dan dalam penyajian laporan selama ini. Tujuan dari penelitian ini adalah untuk memanfaatkan metode SAW dalam penilaian kinerja dosen. Metodologi yang digunakan dalam melakukan penelitian adalah diawali dengan pengumpulan data dan dilanjutkan dengan tahap mengembangkan menjadi suatu sistem informasi. Hasil penelitian ini adalah menghasilkan Sistem Informasi Penilaian Kinerja Dosen memanfaatkan teknologi MVC Framework dengan metode SAW sebagai sarana penunjang pengambilan keputusan di AMIK Umel Mandiri.

The application of the analytical hierarchy process and simple additive weighting methods in making decisions for high achieving students in vocational high schools.

Vocational High School is a formal education unit that organizes vocational education that prepares students, especially to work in certain fields. In determining students who excel in certain fields, it is necessary to have a decision support system to improve the quality of decisions in determining students who excel from the highest average score. However, using the highest average score does not get optimal results because it is not adjusted to the existing needs in determining outstanding students. In this study, it can be used as a reference in making decisions for outstanding students by applying the Analytical Hierarchy Process and Simple Additive Weighting methods. The steps taken are: Data collection, Data Preprocessing, Ranking and Comparison of Results between Analytical Hierarchy Process, Simple Additive Weighting with manual weighting results. The results of the ranking comparison show that there are 6 students with the top ranking who are recommended to be outstanding students in the linguistic group.