Jurnal STAI Al-Hamidiyah
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Re-application to university after rejection and later income and occupational status – Using education-linked genes to predict outcomes in longitudinal register data
No full textResearch has identified socioeconomic disparity in university enrollment due to a higher likelihood to stop applying after an initial rejection among individuals from less educated families. We investigate the role of education-linked genes alongside family background and experiencing mental illness and other major life events in predicting (re-)application to university. We further examine the later socioeconomic outcomes of individuals who are more persistent in their educational goals.
Utilizing longitudinal genetically informed register data from Finland, we analyze a sample of 6,101 individuals born 1987-1990 followed up until 2018. The study uses parental polygenic scores to assess the genetic endowment to high educational attainment (EDU-PGS) combined with information on application behavior (1,683 individuals experienced rejection) and socioeconomic variables. Multinomial and binary logistic regression models and discrete time hazard models are employed.
Our findings indicate an intricate interplay of genetic endowments, income and education of the parents, (re-)application behavior, and early adulthood income and occupational status. Individuals with a higher EDU-PGS were more likely to reapply after rejection, suggesting a genetic component in persistence in educational goals and application behaviors beyond family background. Mental illness did not have an effect over and above other included indicators on stop applying, and there was no evidence for the presence of gene-environment interactions. Moreover, application behavior mediated the influence of the polygenic score on occupational status in early adulthood.
The study contributes to the broader equality of opportunity debate and shows how genes express themselves in our smaller or bigger decisions. The joint contribution of genetic and family factors has a crucial role in shaping educational trajectories and later socioeconomic outcomes
The Lifespan of “Unreliable Science”: Rice et al. (1992) and the Enduring Claim of Adverse Treatment Effects in Psychopathy
No full textParasocial Processing Short Scale
No full textThis repository contains materials for the development and validation of the Parasocial Processing Short Scale (PP-SS), a theoretically grounded nine-item measure derived from the PSI-Process Scales. The PP-SS was systematically tested in two preregistered studies using adult UK online samples: a one-factorial experiment (n = 258) and a survey study (n = 720) featuring diverse personae and participant demographics. Results demonstrate good psychometric quality, construct validity within the nomological network of parasocial processing, and measurement invariance across user groups and personae. The PP-SS provides a concise and easily applicable instrument for assessing parasocial processing in empirical research
A survey of the knowledge, perceptions of and attitudes to digital health of healthcare professionals in 14 Bulgarian hospitals: First large-scale study on digital health in Bulgarian inpatient facilities
No full textTranslation in Bulgaria
Robust Standard Errors and Confidence Intervals for Standardized Mean Difference
No full textThe standardized mean difference (SMD) is a widely used effect size metric for assessing intervention effects in experimental designs and for quantifying disparities in observational studies. Its central role in power analysis and meta-analysis demands robust standard errors (SEs) and confidence intervals (CIs) that remain reliable under unequal variances and in the presence of data contamination. To address this, I proposed heteroscedasticity-consistent (HC) estimators for the variance component of SMD and enhanced their robustness using trimmed means and Winsorized variances (TW estimators). Twenty SE and CI estimators were evaluated through extensive Monte Carlo simulations, varying effect sizes, sample sizes, variance ratios, sample size ratios, and distributional shapes. Performance was assessed using coverage, Type I error, relative bias in SE and power, and CI overlap. Additional comparisons included alternative CI construction methods (normal approximation, central t, lambda-prime distributions) and bootstrap approaches (percentile and bias-corrected accelerated). Results showed that CIs based on the lambda-prime distribution achieved the best coverage, lowest bias in power, and greatest overlap with simulation-based CIs. Performance of HC estimators depended on the sample size and variance ratios. Generally, SMD with HC2 (Welch-Satterthwaite), HC3 (Efron’s Jackknife), HC5, and their TW versions provided reliable inference under unequal variance and contamination. TW estimators were most useful under symmetric contamination but offered limited benefits for skewed or mean–variance linked distributions. Bootstrap methods combined with TW estimators worked remarkably well under all conditions. Finally, implications for inference, power, and meta-analysis were discussed
Study protocol: The Current Landscape of Relevant Drug Repositioning Methods
No full textProtocols for the Revie
Skillful Subseasonal Soil Moisture Drought Forecasts with Deep Learning-Dynamic Models
No full textAll the codes are available under the files tab
Digging for Trouble? Uncovering the Link Between Mining Booms and Crime
No full textThis paper evaluates the local effects of an exogenous economic shock, specifically, a mining boom, on crime levels and the mechanisms behind this relationship, including the effect of the boom on local economies’ labor market conditions. The paper contributes with empirical evidence to the literature on the impact of commodity booms, specifically mining, on criminal activities. Based on the exogeneity of the mining boom and the geographical location of minerals, I apply the synthetic control method using municipality-level data from Sweden for the period 1996-2015. This paper
focuses on the total number of crimes, which is then subdivided into crimes against persons and crimes against wealth. I find evidence that the mining boom improves the labor market conditions of mining municipalities, which translates into long-term (2013, 2014, and 2015) reductions in total crime. The evidence suggests that the improvement in labor market conditions (employment, wages, and disposable income) is the main mechanism by which the mining boom reduces crime. I find no evidence for the other mechanisms considered: the mining boom does not affect the population composition, the government’s crime prevention capacity, or the income inequality in mining municipalities
