Bayesian approaches for estimating multilevel latent variable models can be beneficial in small samples. Prior distributions can be used to overcome small sample problems, for example, when priors that increase the accuracy of estimation are chosen. This article discusses two different but not mutually exclusive approaches for specifying priors. Both approaches aim at stabilizing estimators in such a way that the Mean Squared Error of the estimator of the between-group slope will be small. In the first (...) approach, the MSE is decreased by specifying a slightly informative prior for the group-level variance of the predictor variable, whereas in the second approach, the decrease is achieved directly by using a slightly informative prior for the slope. Mathematical and graphical inspections suggest that both approaches can be effective for reducing the MSE in small samples, thus rendering them attractive in these situations. The article also discusses how these approaches can be implemented in Mplus. (shrink)

This paper presents ethical dilemmas concerning the termination of pregnancy, the management of childbirth, and the withdrawal of life-support from infants in special care, for a small sample of British Pakistani Muslim parents of babies diagnosed with fatal abnormalities. Case studies illustrating these dilemmas are taken from a qualitative study of 66 families of Pakistani origin referred to a genetics clinic in Southern England. The paper shows how parents negotiated between the authoritative knowledge of their doctors, religious experts, and (...) senior family members in response to the ethical dilemmas they faced. There was little knowledge or open discussion of the view that Islam permits the termination of pregnancy for serious or fatal abnormality within 120 days and there was considerable disquiet over the idea of ending a pregnancy. For some parents, whether their newborn baby would draw breath was a main worry, with implications for the baby's Muslim identity and for the recognition of loss the parents would receive from family and community. This concern sometimes conflicted with doctors' concerns to minimize risk to future pregnancies by not performing a Caesarean delivery if a baby is sure to die. The paper also identifies parents' concerns and feelings of wrong-doing regarding the withdrawal of artificial life-support from infants with multiple abnormalities. The conclusion considers some of the implications of these observations for the counselling and support of Muslim parents following the pre- or neo-natal diagnosis of fatal abnormalities in their children. (shrink)

Conventional methods for fault diagnosis typically require a substantial amount of training data. However, for equipment with high reliability, it is arduous to form a large-scale well-annotated dataset due to the expense of data acquisition and costly annotation. Besides, the generated data have a large number of redundant features which degraded the performance of models. To overcome this, we proposed a feature transfer scenario that transfers knowledge from similar fields to enhance the accuracy of fault diagnosis with small sample. (...) To reduces the redundant information, data were filtered according to manifold consistency. Then, features were extracted based on CNN and feature transfer was conducted. For adequate fitness, the joint adaptation of conditional distribution and marginal distribution was used between the two domains. Minimum structural risk and MMD of adaptation were two indicators weighted for training the model. To test the efficiency of the model, we built an airborne fuel pump testbed, and contributed a new dataset that contained 15 categories of fault data, which serves as the small sample dataset in this research. Then the proposed model was applied in our experimental data. As a result, the fault diagnosis rate increases by 28.6% through our proposed model, which is more precise than other classical methods. The results of feature visualization further demonstrate that the features are more distinguished through the proposed method. All code and data are accessible on my GitHub. (shrink)

When Bayesian estimation is used to analyze Structural Equation Models, prior distributions need to be specified for all parameters in the model. Many popular software programs offer default prior distributions, which is helpful for novel users and makes Bayesian SEM accessible for a broad audience. However, when the sample size is small, those prior distributions are not always suitable and can lead to untrustworthy results. In this tutorial, we provide a non-technical discussion of the risks associated with the use (...) of default priors in small sample contexts. We discuss how default priors can unintentionally behave as highly informative priors when samples are small. Also, we demonstrate an online educational Shiny app, in which users can explore the impact of varying prior distributions and sample sizes on model results. We discuss how the Shiny app can be used in teaching; provide a reading list with literature on how to specify suitable prior distributions; and discuss guidelines on how to recognize behaving priors. It is our hope that this tutorial helps to spread awareness of the importance of specifying suitable priors when Bayesian SEM is used with small samples. (shrink)

The aberrations of a gene can influence it and the functions of its neighbour genes in gene interaction network, leading to the development of carcinogenesis of normal cells. In consideration of gene interaction network as a complex network, previous studies have made efforts on the driver attribute filling of genes via network properties of nodes and network propagation of mutations. However, there are still obstacles from problems of small size of cancer samples and the existence of drivers without (...) property of network neighbours, limiting the discovery of cancer driver genes. To address these obstacles, we propose an efficient modularity subspace based concept learning model. Our model can overcome the curse of dimensionality due to small samples via dimension reduction in the task of attribute concept learning and explore the features of genes through modularity subspace beyond the network neighbours. The evaluation analysis also demonstrates the superiority of our model in the task of driver attribute filling on two gene interaction networks. Generally, our model shows a promising prospect in the application of interaction network analysis of tumorigenesis. (shrink)

With small to modest sample sizes and complex models, maximum likelihood estimation of confirmatory factor analysis models can show serious estimation problems such as non-convergence or parameter estimates outside the admissible parameter space. In this article, we distinguish different Bayesian estimators that can be used to stabilize the parameter estimates of a CFA: the mode of the joint posterior distribution that is obtained from penalized maximum likelihood estimation, and the mean, median, or mode of the marginal posterior distribution that (...) are calculated by using Markov Chain Monte Carlo methods. In two simulation studies, we evaluated the performance of the Bayesian estimators from a frequentist point of view. The results show that the EAP produced more accurate estimates of the latent correlation in many conditions and outperformed the other Bayesian estimators in terms of root mean squared error. We also argue that it is often advantageous to choose a parameterization in which the main parameters of interest are bounded, and we suggest the four-parameter beta distribution as a prior distribution for loadings and correlations. Using simulated data, we show that selecting weakly informative four-parameter beta priors can further stabilize parameter estimates, even in cases when the priors were mildly misspecified. Finally, we derive recommendations and propose directions for further research. (shrink)

Using data on submitted and published manuscripts in Feminist Economics from 1995 to 2019, we examine differences in method and scope used by authors residing in the Global North and Global South. We specifically focus on research methods, intersectional analyses, region of analysis, and co-authorship status. Further, using logistic regression models, we examine the relationship between authors’ location and use of research methods. We find authors in the Global South are more likely to engage in empirical and mixed-methods papers compared (...) to Global North authors in our sample. Moreover, a greater share of Global South authors engage in intersectional analysis and exhibit geographical focus on developing countries. Drawing insights from the Feminist Economics manuscripts data, we argue that encouraging Global South research can contribute to the goals of the field of feminist economics – aimed at inclusivity, diversity of standpoints, and plurality in research methods, thereby improving overall economic research. (shrink)

Hilary Kornblith (1993) has recently offered a reliabilist defense of the use of the Law of Small Numbers in inductive inference. In this paper I argue that Kornblith's defense of this inferential rule fails for a number of reasons. First, I argue that the sort of inferences that Kornblith seeks to justify are not really inductive inferences based on small samples. Instead, they are knowledge-based deductive inferences. Second, I address Kornblith's attempt to find support in the work (...) of Dorrit Billman and I try to show that close attention to the workings of her computational model reveals that it does not support Kornblith's argument. While the knowledge required to ground the inferences in question is perhaps inductively derived, Billman's work does not support the notion that small samples provide a reliable basis for our generalizing inferences. (shrink)

To date researchers planning experiments have always lived by the mantra that 'using equal sample sizes gives the best results' and although unequal groups are also used in experimentation, it is not the preferred method of many and indeed actively discouraged in literature. However, during live study planning there are other considerations that we must take into account such as availability of study participants, statistical power and, indeed, the cost of the study. These can all make allocating equal sample sizes (...) difficult, and sometimes near impossible. This, some might say, means that the study would not adhere to rigorous statistical standard (Rosenbaum and Rubin, 1985). However, here we present evidence that, not only is this a false assumption, but that we may actually gain more power in the study by actually using unequal groups. Here, data from a Sepsis Biomarker study is used, in which the aim is to predict, by biomarker level and presence, whether the patient would go on to develop sepsis. It was found that larger control groups may give more power to studies looking for an effect in the mid range but not for large or small effects. This study shows merit in the hypothesis that more power can be achieved when a larger control group is used. Published by the Ministry of Defence at dstl - Reference DSTLTR92592 P2PP2R-2016-02-23T13:39:45. (shrink)

Text classification involves deciding whether or not a document is about a given topic. It is an important problem in machine learning, because automated text classifiers have enormous potential for application in information retrieval systems. It is also an interesting problem for cognitive science, because it involves real world human decision making with complicated stimuli. This paper develops two models of human text document classification based on random walk and accumulator sequential sampling processes. The models are evaluated using data from (...) an experiment where participants classify text documents presented one word at a time under task instructions that emphasize either speed or accuracy, and rate their confidence in their decisions. Fitting the random walk and accumulator models to these data shows that the accumulator provides a better account of the decisions made, and a “balance of evidence” measure provides the best account of confidence. Both models are also evaluated in the applied information retrieval context, by comparing their performance to established machine learning techniques on the standard Reuters‐21578 corpus. It is found that they are almost as accurate as the benchmarks, and make decisions much more quickly because they only need to examine a small proportion of the words in the document. In addition, the ability of the accumulator model to produce useful confidence measures is shown to have application in prioritizing the results of classification decisions. (shrink)

The small sample properties of estimators and tests are frequently too complex to be useful or are unknown. Much econometric theory is therefore developed for very large or asymptotic samples where it is assumed that the behaviour of estimators and tests will adequately represent their properties in small samples. Refined asymptotic methods adopt an intermediate position by providing improved approximations to small sample behaviour using asymptotic expansions. Dedicated to the memory of Michael Magdalinos, whose work (...) is a major contribution to this area, this book contains chapters directly concerned with refined asymptotic methods. In addition, there are chapters focusing on new asymptotic results; the exploration through simulation of the small sample behaviour of estimators and tests in panel data models; and improvements in methodology. With contributions from leading econometricians, this collection will be essential reading for researchers and graduate students concerned with the use of asymptotic methods in econometric analysis. (shrink)

Recent research governance documents say that the body of research evidence must reflect population diversity. The response to this needs to be more sophisticated than simply ensuring minorities are present in samples. For quantitative research looking primarily at treatment effects of drugs and devices four suggestions are made. First, identify where the representation of minorities in samples matters—for example, where ethnicity may cause different treatment effects. Second, where the representation of a particular group matters then subgroup analysis of (...) the results will usually be necessary. Third, ensuring representation and subgroup analysis will have costs; deciding on whether such representation is worthwhile will involve cost benefit analysis. Fourth, the representation of minorities should not be seen as mainly a locality issue. For qualitative research it is argued that the representation of diversity is often important. Given the small samples of many qualitative projects, however, the best way to ensure representation occurs is to allow a proliferation of such research, not to stipulate such representation in samples. (shrink)

In this study three different techniques suitable to recover high molecular weight genomic DNA from small blood samples of different species of malagasy primates are compared: we suggest the use of a very simple phenol-chlorophorm DNA extraction for badly stored or coagulated blood as for samples collected under difficult field conditions. Furthermore we briefly describe the use of this DNA in determining RLFP patterns and DNA fingerprints.

Yesterday I was reading about sampling issues in psychiatry intensely flagged by anthropologists, in Oxford Textbook of Migrant Psychiatry (a book which also cites one of my papers: the citation is from Rachel Tribe). In addition to being admitted to hospital for mental disorder in 2023, I have psoriasis. It began in 2007. I beat psoriasis completely in 2008 or 9, then it returned in 2010. I was beating it before hospital admission except on the head, by very unusual means: (...) amongst other things I found that writing Milan Kundera imitations reduces psoriasis. In 2024, I was given some medicine called Enstillar once again after not using psoriasis medicine for 5 years. I only properly tried Enstillar for 3 weeks before because I broke it. What I have found is that it works well on the head. It has got rid of very persistent and large lesions on the nape of my neck, or one massive lesion. Also it has worked very well towards the top of my forehead, reducing a large lesion (to nothing if I use it regularly). But the small lesions on the body (about 40? rest of the body, to be precise?) return quickly after its use. I found a similar bodily persistence in the 3 week period before Covid, but never used it on the head back then. My worry is that the sample who tried Enstillar are headocentric: a new term devised by myself. What they really care about is that their head should be free of psoriasis lesions. The head is prioritized over the body. "Who cares if the body has lesions? It is covered by clothes." The headocentrism of the West (including Muslim countries even?)! The headocentrism of Monty Python's Black Knight! (shrink)

We suggest an equilibrium concept for a strategic model with a large number of players in which each player observes the actions of only a small number of the other players. The concept fits well situations in which each player treats his sample as a prediction of the distribution of actions in the entire population, and responds optimally to this prediction. We apply the concept to a strategic voting model and investigate the conditions under which a centrist candidate can (...) win the popular vote although his strength in the population is smaller than the strengths of the right and left candidates.  2003 Elsevier Inc. All rights reserved. (shrink)

We present a theory of decision by sampling (DbS) in which, in contrast with traditional models, there are no underlying psychoeconomic scales. Instead, we assume that an attribute’s subjective value is constructed from a series of binary, ordinal comparisons to a sample of attribute values drawn from memory and is its rank within the sample. We assume that the sample reflects both the immediate distribution of attribute values from the current decision’s context and also the background, real-world distribution of attribute (...) values. DbS accounts for concave utility functions; losses looming larger than gains; hyperbolic temporal discounting; and the overestimation of small probabilities and the underestimation of large probabilities. Ó 2005 Elsevier Inc. All rights reserved. (shrink)

Researchers in the social and behavioral sciences often have clear expectations about the order/direction of the parameters in their statistical model. For example, a researcher might expect that regression coefficient β 1 is larger than β 2 and β 3. The corresponding hypothesis is H : β 1 > {β 2, β 3 } and this is known as an (order) constrained hypothesis. A major advantage of testing such a hypothesis is that power can be gained and inherently a smaller (...) sample size is needed. This article discusses this gain in sample size reduction, when an increasing number of constraints is included into the hypothesis. The main goal is to present sample-size tables for constrained hypotheses. A sample-size table contains the necessary sample-size at a pre-specified power (say, 0.80) for an increasing number of constraints. To obtain sample-size tables, two Monte Carlo simulations were performed, one for ANOVA and one for multiple regression. Three results are salient. First, in an ANOVA the needed sample-size decreases with 30–50% when complete ordering of the parameters is taken into account. Second, small deviations from the imposed order have only a minor impact on the power. Third, at the maximum number of constraints, the linear regression results are comparable with the ANOVA results. However, in the case of fewer constraints, ordering the parameters (e.g., β 1 > β 2 ) results in a higher power than assigning a positive or a negative sign to the parameters (e.g., β 1 > 0). (shrink)

Why was Hensen unsuccesful in the quantification of ecological sampling? No aspect of plankton research itself seems to have hindered quantification; both collecting methods and taxonomy were sufficiently advanced. The reason is probably that at the time he began sampling, Hensen had to devise his own statistical methods for expressing the reproducibility and validity of samples. Hensen might have succeeded in this if he had overcome prevalent nineteenth-century attitudes toward randomness.The statistical literature of medicine and physics with which Hensen (...) was probably familiar gave methods for expressing reproducibility and for comparing differences between means of different sets of observations. For example, a student of Poisson writing on medical statistics advocated using Poisson's limit (standard error 2√2) to test the difference between two means56. Other authors suggested that differences between means were most meaningful if very large numbers of observations were used.57 In his laboratory subsampling, Hensen used the propable error as a limit about means. In this and other ways, he seems most indebted to the physicist Ernst Abbe for statistical methods.58 However, all the methodology available to Hensen had been developed for situations in which errors are a property of the measurement or sampling process, and not of the phenomena themselves. The available methods for measuring reproducibility were based on the assumption that differences from the average were small and that they tended to accumulate about the mean in a bell-shaped pattern. Hensen constantly reinvestigated the distribution of plankton numbers about the average using a different method each time. Westergaard points out that medical statisticians did not make such investigations with their biological data.59To a considerable extent, biological sampling problems forced development of theory because samples afforded the only information on a pattern in water or soil which could not be directly observed. The sampling methods of Laplace and the late nineteenth-century government statisticians contrasted strongly with Hensen's because, either through subjective knowledge of the population sampled or through censuses, they attempted to choose representative or typical samples.60 The high reproducibility and validity of representative sampling is attained by knowing more about a population than a biologist can ordinarily know. The uncertain reproducibility and validity of biological sampling spurred the development of formal sampling theory.A formal sampling theory developed only after change in the general intellectual attitude toward randomness, which was reflected in nineteenth-century statistics.61 The ninteenth-century attitude that randomness is not part of nature changed in the twentieth century to a view of randomness as a property of nature.62 The physicist's incorporation of randomness into physical models in response to this intellectual change late in the nineteenth-century is discussed by Bork.63 In biology, the change was initiated by the attention Darwin focused on morphological variation. The English biometricians — Francis Galton and W. F. R. Weldon, for example — were prominent in developing methods for the analysis of biological variation.64 Most pertinent to the development of sampling theory was Karl Pearson's use of frequency distributions as models of biological variation. In ecology, quantification was brought about by Ronald Fisher more than by anyone else; he incorporated randomness into sampling plans and built upon the methods developed earlier for analysis of individual variation. Fisher's use of random sampling allowed comparison between the sample collections and the collections expected from a model population of known patterning (calculated with a frequency distribution). This is a much more efficient method of determining the validity of a sample than Hensen's comparison of collections with a model uniform collection. Intellectual background and accumulated biological information caused Fisher to find variability where Hensen had seen uniformity.In summary, Victor Hensen became interested in fisheries research because of the economic importance of fishing to Germany. Hensen had considerable understanding of the prerequisites for valid sampling, but the value of his quantitative approach was limited by the general preconceptions shared by most nineteenth-century biologists. Through Hensen's efforts many other biologists were stimulated to undertake quantitative samples, even though the statistical methods for analyzing variation among populations developed only after methods for analyzing variation among individuals had been developed. *** DIRECT SUPPORT *** A8402011 00003. (shrink)

BackgroundSample size calculations are critical in clinical trial design, yet hypothesised effect sizes are often overly optimistic, leading to underpowered studies. Research ethics committees (RECs) assess trial protocols, including sample size justification, but their role in mitigating optimism bias in sample size calculations is not well studied.MethodsWe descriptively analysed 50 clinical trial protocols approved by a Dutch REC (2015–2018) with available primary outcome results. We examined REC comments on sample size calculations, protocol modifications during ethics review and amendments, and discrepancies (...) between target and observed effect sizes. For comparability, effect sizes were standardised.ResultsNine (18%) trials received REC comments on sample size calculations, mainly addressing calculation errors (n = 5), missing parameters (n = 2), or other methodological considerations (n = 3), with only three comments (6%) requesting effect size justification. Seven (14%) trials modified their sample size calculation during ethics review, mostly in response to REC comments, and 10 (20%) trials made modifications in amendments. In total, 40 (80%) trials overestimated their target effect size. Across all trials, the target effect size was overestimated by a median of 0.22 [IQR: 0.03 – 0.41]. Changes during ethics review led to less overestimation for only one trial, which reflected the correction of a calculation error rather than a reassessment of assumptions.ConclusionsOptimism in sample size calculations is common, but the influence of REC feedback on reducing overestimation appears limited. As this was a small, descriptive study from a single Dutch REC in 2015–2018, findings may not generalise to other settings or more recent practice. Future research should validate these findings and may help identify characteristics associated with overestimation, supporting RECs in recognising trials at risk of being underpowered. (shrink)

We report on the small-scale (0.5 13 h - 1M, a large-scale bias of ~2.0 and a satellite fraction of 12 ± 2 per cent. Thus, these galaxies occupy haloes with average masses in between those of the higher redshift BOSS CMASS sample and the original SDSS I/II luminous red galaxy sample © 2012 The Authors Published by Oxford University Press on behalf of the Royal Astronomical Society © doi:10.1093/mnras/sts314.

In recent years, supply chain finance is exploited to solve the financing difficulties of small- and medium-sized enterprises. SME credit risk assessment is a critical part in the SCF system. The diffusion of SME credit risk may cause serious consequences, leading the whole supply chain finance system unstable and insecure. Compared with traditional credit risk assessment models, the supply chain relationship, credit condition of SME, and core enterprises should all be considered to rate SME credit risk in SCF. Traditional (...) methods mix all indicators from different index systems. They cannot give a quantitative result on how these index systems work. Furthermore, traditional credit risk assessment models are heavily dependent on the number of annotated SME data. However, it is implausible to accumulate enough credit risky SMEs in advance. In this paper, we propose an adaptive heterogenous multiview graph learning method to tackle the small sample size problem for SMEs’ credit risk forecasting. Three graphs are constructed by using indicators from supply chain operation, SME financial indicator, and nonfinancial indicator individually. All the graphs are integrated in an adaptive manner, providing a quantitative explanation on how the three parts cooperate. The experimental analysis shows that the proposed method has good performance for determining whether SME is risky or nonrisky in SCF. From the perspective of SCF, SME financing ability is still the main factor to determine the credit risk of SME. (shrink)

Vast research has sought to better understand the origins and development of rape myth beliefs given the problematic influence of such misconceptions throughout global societies and criminal justice pathways. The current research aims to build on this body of literature by examining the contribution that psychopathic personality traits (affective responsiveness, cognitive responsiveness, interpersonal manipulation, egocentricity) and emotional intelligence may have upon rape myth beliefs. Furthermore, this study will investigate the extent to which sociodemographic characteristics (age, gender, ethnicity, education), and prior (...) experience of sexual victimisation, contribute to variance in rape myth acceptance scores. In total 251 participants (M Age = 31.66) completed an online, self-report questionnaire which included contemporary measures of psychopathy and rape myth acceptance, never previously tested in combination. Results of a hierarchical multiple regression analysis indicate that egocentricity, age, and gender were significantly associated with rape myth beliefs. Emotional intelligence, as well as affective and interpersonal traits of psychopathy, were not directly related with rape mythology. Findings are interpreted alongside previous research, where we suggest there is an urgent need for larger, nationally representative samples, systematically recruited from the general population to help clarify uncertainty in existing literature emerging from small-scale opportunistic datasets. (shrink)

In this paper, the approaches of a sample of small firms to environmental issues in the UK and the Netherlands are compared.The study makes a contribution by addressing the lack of research on small firms and the environment, as well as offering insights intothe influence that cultural. institutional, and political frameworks can have on small firm owner-managers' attitudes to external issues. The environment is considered here as an ethical issue, drawing on work on the environmental responsibility of (...) business by both Bowie (1990) and Hoffman (1991). It is argued that the approaches to the environment identified in this study by Dutch and UK small firm owner-managers do not fit in with the positions of either Bowie or Hoffman. The concept of stakeholder cooperation is proposed as a more realistic alternative. (shrink)

The statistics of small samples are often quite different from those of large samples, and this needs to be taken into account in assessing the rationality of human behavior. Specifically, in evaluating human responses to environmental statistics, it is the effective environment that matters; that is, the environment actually experienced by the agent needs to be considered, not simply long‐run frequencies. Significant deviations from long‐run statistics may arise through experiential limitations of the agent that stem from resource (...) constraints and/or information‐processing bounds. The article draws together recent work from a number of areas in judgment and decision making ranging from randomness perception (Hahn & Warren, ), information sampling (Hertwig & Pleskac, ; Kareev et al., ), and consequences of choice for exploration or exploitation (e.g., Denrell, ) to demonstrate how proper consideration of these deviations leads to reevaluation of behaviors that are otherwise deemed irrational. (shrink)

Ethical issues regarding research biobanks continue to be a topic of intense debate, especially issues of confidentiality, informed consent, and child participation. Although considerable empirical literature concerning research biobank ethics exists, very little information is available regarding the opinions of medical professionals doing genetics research from the Middle East, especially Arabic speaking countries. Ethical guidelines for research biobanks are critically needed as some countries in the Middle East are starting to establish national research biobanks. Islam is the dominant religion in (...) these countries, and it affects people’s behavior and influences their positions. Moreover, communities in these countries enjoy a set of customs, traditions and social norms, and have social and familial structures that must be taken into account when developing research policies. We interviewed 12 medical professionals from the Middle East currently working with stored tissue samples to document their opinions. We found general agreement. Participants’ primary concerns were similar to the views of researchers internationally. Since children tend to represent a high percentage of Middle Eastern populations, and because children’s bodies are not just small adult bodies, the interviewed professionals strongly believed that it is imperative to include children in biobank research. Participants generally believed that protecting confidentiality is socially very important and that informed consent/assent must be obtained from both adult and child participants. This study provides a starting point for additional studies. (shrink)

The jumping to conclusions bias (JTC) refers to making a decision before collecting a sufficient amount of information to warrant doing so. Very little research has been conducted on the ways in which mood influences JTC in schizophrenia and healthy individuals along the continuum of risk for psychosis. It was hypothesized that elevations in schizotypal traits will be associated with greater JTC, and that negative affect will moderate the relationship between schizotypal traits and JTC. 100 undergraduate students enrolled at the (...) University of Toronto Scarborough (UTSC) were recruited for this study. The study employed an experience-sampling approach. Positive affect demonstrated a small positive relationship to JTC, meaning that as an individual’s positive affect increased so too did their JTC tendency, regardless of their elevations on schizotypal traits. While a significant negative relationship was found between schizotypal traits and JTC, the effect size was negligible, which may highlight the need for effort testing in undergraduate populations and evaluating the sensitivity of experimental tasks to increase data quality. Overall, identifying the influence of mood on metacognition is critical in determining how JTC functions within the illness. (shrink)

For enhancing the stability of the microgrid operation, this paper proposes an optimization model considering the small-signal stability constraint. Due to the nonsmooth property of the spectral abscissa function, the droop controller parameters’ optimization is a nonsmooth optimization problem. The Sequential Quadratic Programming with Gradient Sampling is implemented to optimize the droop controller parameters for solving the nonsmooth problem. The SQP-GS method can guarantee the solution of the optimization problem globally and efficiently converges to stationary points with probability of (...) one. In the current iteration, the gradient of the nonsmooth function can be evaluated on a set of randomly generated nearby points by computing closed-form sensitivities. A test on the microgrid system shows that the optimality and the efficiency of the SQP-GS are better than those of the heuristic algorithms. (shrink)

The persistent pervasiveness of inappropriately small studies in empirical fields is regu-larly deplored in scientific discussions. Consensually, taken individually, higher-powered studies are more likely to be truth-conducive. However, are they also beneficial for the wider performance of truth-seeking communities? We study the impact of sample sizes on collective exploration dynamics under ordinary conditions of resource limita-tion. We find that large collaborative studies, because they decrease diversity, can have detrimental effects in certain realistic circumstances that we characterize precisely. We show (...) how limited inertia mechanisms may partially solve this pooling dilemma and dis-cuss our findings briefly in terms of editorial policies. (shrink)

The number of elements in a small set of items is appraised in a fast and exact manner, a phenomenon called subitizing. In contrast, humans provide imprecise responses when comparing larger numerosities, with decreasing precision as the number of elements increases. Estimation is thought to rely on a dedicated system for the approximate representation of numerosity. While previous behavioral and neuroimaging studies associate subitizing to a domain-general system related to object tracking and identification, the nature of small numerosity (...) processing is still debated. We investigated the neural processing of numerosity across subitizing and estimation ranges by examining electrophysiological activity during the memory retention period in a delayed numerical match-to-sample task. We also assessed potential differences in the neural signature of numerical magnitude in a fully non-symbolic or cross-format comparison. In line with behavioral performance, we observed modulation of parietal-occipital neural activity as a function of numerosity that differed in two ranges, with distinctive neural signatures of small numerosities showing clear similarities with those observed in visuospatial working memory tasks. We also found differences in neural activity related to numerical information in anticipation of single vs. cross-format comparison, suggesting a top-down modulation of numerical processing. Finally, behavioral results revealed enhanced performance in the mixed-format conditions and a significant correlation between task performance and symbolic mathematical skills. Overall, we provide evidence for distinct mechanisms related to small and large numerosity and differences in numerical encoding based on task demands. (shrink)

Purpose This study aims to identify and analyse the issues faced by internet-based small businesses in developing countries regarding cybersecurity and document how these businesses address the risks. Design/methodology/approach This study used the qualitative method. Respondents were internet-based small businesses selected by using theoretical sampling. Data were collected by using interviews and observations. The validity of the analysis was ensured by using triangulation and member checking. Findings This study reveals that small businesses managed to identify the loss (...) of physical and monetary assets as possible damage. However, only a few businesses identified loss of intangible assets as possible cyber risks. Most small businesses had used basic cybersecurity measures to protect data access and some primary business activities. Unfortunately, they rarely take initiatives in preventing and early detecting cyber risks. Research limitations/implications Findings of this study cannot be generalised as it aims to obtain new insights and document unexplored findings. Thus, if this study’s findings are going to be generalised, it is necessary to conduct an additional study. Secondly, this study did not assess how far small business had fulfilled the relevant information security framework as assessment required additional research, and this study only aimed to map the current situation in small businesses. Practical implications This study emphasised the importance of identifying valuable assets or resources when implementing cybersecurity measures. Focusing on security measures to protect identified assets from cyber risk will make the efforts more efficient and effective than using standardised cybersecurity measures. Third-party developers can also use this study to understand small businesses’ current cybersecurity implementation and their characters to design online platforms that suit these needs. Governments can also design educational activities that address small businesses’ lack of knowledge. Originality/value Most studies which focus on small businesses and information technology (IT) usually only discuss how they use IT. This study also brings new contributions by focusing on developing countries and specifically addresses internet-based technology cyber risk faced by e-commerce businesses. The qualitative method is used as most studies in e-commerce adoption were positivistic in nature, and inductive-based studies were rarely found on the topic. (shrink)

Big social data have enabled new opportunities for evaluating the applicability of social science theories that were formulated decades ago and were often based on small- to medium-sized samples. Big Data coupled with powerful computing has the potential to replace the statistical practice of sampling and estimating effects by measuring phenomena based on full populations. Preparing these data for analysis and conducting analytics involves a plethora of decisions, some of which are already embedded in previously collected data and (...) built tools. These decisions refer to the recording, indexing and representation of data and the settings for analysis methods. While these choices can have tremendous impact on research outcomes, they are not often obvious, not considered or not being made explicit. Consequently, our awareness and understanding of the impact of these decisions on analysis results and derived implications are highly underdeveloped. This might be attributable to occasional high levels of over-confidence in computational solutions as well as the possible yet questionable assumption that Big Data can wash out minor data quality issues, among other reasons. This article provides examples for how to address this issue. It argues that checking, ensuring and validating the quality of big social data and related auxiliary material is a key ingredient for empowering users to gain reliable insights from their work. Scrutinizing data for accuracy issues, systematically fixing them and diligently documenting these processes can have another positive side effect: Closely interacting with the data, thereby forcing ourselves to understand their idiosyncrasies and patterns, can help us to move from being able to precisely model and formally describe effects in society to also understand and explain them. (shrink)

Evidence of risk aversion in laboratory settings over small stakes leads to a priori implausible levels of risk aversion over large stakes under certain assumptions. One core assumption in statements of this calibration puzzle is that small-stakes risk aversion is observed over all levels of wealth, or over a â sufficiently largeâ range of wealth. Although this assumption is viewed as self-evident from the vast experimental literature showing risk aversion over laboratory stakes, it actually requires that lab wealth (...) be varied for a given subject as one evaluates the risk attitudes of the subject. We consider evidence from a simple design that tests this assumption, and find that the assumption is strikingly rejected for a large sample of subjects from a population of college students. We conclude that the implausible predictions that flow from these assumptions do not apply to one specialized population widely used to study economic behavior in laboratory experiments. (shrink)

Background The growing diffusion of artificial intelligence, data science and digital health has highlighted the role of collection of data and biological samples, thus raising legal and ethical concerns regarding its use and dissemination. Further, the expansion of biobanking, from the basic collection of frozen specimens to the virtual biobanks of specimens and associated data that exist today, has given a revolutionary potential on healthcare systems, particularly in the field of neurological diseases, due to the inaccessibility of central nervous (...) system and the need of non-invasive investigation approaches. Informed Consent (IC) is considered mandatory in all research studies and specimen collections, and must specifically take into account the ethical respect to the individuals to whom the used biological material and data belong. Methods We evaluated the attitudes of patients with neurological diseases (NP) and healthy volunteers (HV) towards the donation of biological samples to a biobank for future research studies on neurological diseases, and limitations on the use of data, related to the requirements set by the General Data Protection Regulation (GDPR). The study involved a total of 1454 subjects, including 502 HVs and 952 NPs, recruited at Santa Lucia Foundation IRCCS, Rome, from 2020 to 2024. Results We found that (i) almost all subjects agreed with the participation in biobanking (ii) and authorization to genetic studies (HV = 99.1%; NP = 98.3%); Regarding the return of results, (iii) we found a statistically significant difference between NP and HV, the latter preferring not to be informed of potential results (HV = 43%; NP = 11.3%; p < 0.0001); (iv) a small number limited the sharing inside European Union (EU) (HV = 4.6%; NP = 6.6%), whereas patients were more likely to refuse transfer outside EU (HV = 7.4%; NP = 10.7% p = 0.05); (v) nearly all patients agreed with the use of additional health data from EMR for research purposes (98.9%). Conclusions Consent for the donation of material for research purposes is crucial for biobanking and biomedical research studies that use biological material of human origin. Here, we have shown that choices regarding participation in a neurological biobank can be different between HVs and NPs, even if the benefit for research and scientific progress is recognized. NP have a strong interest in being informed of possible results but limit sharing of samples, highlighting a perception of greater individual or relative benefit, while HV prefer a wide dissemination and sharing of data but not to have the return of the results, favoring a possible benefit for society and knowledge. The results underline the need to carefully manage biological material and data collected in biobanks, in compliance with the GDPR and the specific requests of donors. (shrink)

The requirement of randomization in experimental design was first stated by R. A. Fisher, statistician and geneticist, in 1925 in his book Statistical Methods for Research Workers. Earlier designs were systematic and involved the judgment of the experimenter; this led to possible bias and inaccurate interpretation of the data. Fisher's dictum was that randomization eliminates bias and permits a valid test of significance. Randomization in experimenting had been used by Charles Sanders Peirce in 1885 but the practice was not continued. (...) Fisher developed his concepts of randomizing as he considered the mathematics of small samples, in discussions with "Student," William Sealy Gosset. Fisher published extensively. His principles of experimental design were spread worldwide by the many "voluntary workers" who came from other institutions to Rothamsted Agricultural Station in England to learn Fisher's methods. (shrink)