This paper introduces the likelihood method for decision under uncertainty. The method allows the quantitative determination of subjective beliefs or decision weights without invoking additional separability conditions, and generalizes the Savage–de Finetti betting method. It is applied to a number of popular models for decision under uncertainty. In each case, preference foundations result from the requirement that no inconsistencies are to be revealed by the version of the likelihood method appropriate for the model considered. (...) A unified treatment of subjective decision weights results for most of the decision models popular today. Savage’s derivation of subjective expected utility can now be generalized and simplified. In addition to the intuitive and empirical contributions of the likelihood method, we provide a number of technical contributions: We generalize Savage’s nonatomiticy condition (“P6”) and his assumption of (sigma) algebras of events, while fully maintaining his flexibility regarding the outcome set. Derivations of Choquet expected utility and probabilistic sophistication are generalized and simplified similarly. The likelihood method also reveals a common intuition underlying many other conditions for uncertainty, such as definitions of ambiguity aversion and pessimism. (shrink)

Framed as a critique of David Hume’s analysis of miracles, Peirce offers a sustained argument against an approach to historical inference he calls the “Method of Balancing Likelihoods‘ (MBL). In MBL the posterior probability that a disputed historical event has occurred is computed on the basis of the prior probability of that event occurring and the probability that each purported witness of the event has given accurate testimony. Peirce’s critique of this method is hierarchical: he denies that an (...) objective probability obtains for the truthfulness of witness testimony. Conceding this point, he asserts that, even if such objective probabilities exist, it is implausible to believe that witnesses are independent of one another. Conceding the first two points, Peirce argues that the very sampling process inherent to history necessarily introduces a strong probabilistic dependence that makes MBL unreliable. Finally, irrespective of the success of his first three criticisms, Peirce argues that MBL can be shown by empirical means to fail as a reliable method of inference. I reconstruct this hierarchical critique from a handful of Peirce’s manuscripts, and emphasize its continuing relevance for modern accounts of judgment aggregation. (shrink)

Advocates of cladistic parsimony methods have invoked the philosophy of Karl Popper in an attempt to argue for the superiority of those methods over phylogenetic methods based on Ronald Fisher's statistical principle of likelihood. We argue that the concept of likelihood in general, and its application to problems of phylogenetic inference in particular, are highly compatible with Popper's philosophy. Examination of Popper's writings reveals that his concept of corroboration is, in fact, based on likelihood. Moreover, because probabilistic (...) assumptions are necessary for calculating the probabilities that define Popper's corroboration, likelihood methods of phylogenetic inference—with their explicit probabilistic basis—are easily reconciled with his concept. In contrast, cladistic parsimony methods, at least as described by certain advocates of those methods, are less easily reconciled with Popper's concept of corroboration. If those methods are interpreted as lacking probabilistic assumptions, then they are incompatible with corroboration. Conversely, if parsimony methods are to be considered compatible with corroboration, then they must be interpreted as carrying implicit probabilistic assumptions. Thus, the non-probabilistic interpretation of cladistic parsimony favored by some advocates of those methods is contradicted by an attempt by the same authors to justify parsimony methods in terms of Popper's concept of corroboration. In addition to being compatible with Popperian corroboration, the likelihood approach to phylogenetic inference permits researchers to test the assumptions of their analytical methods (models) in a way that is consistent with Popper's ideas about the provisional nature of background knowledge. (shrink)

Dr Edwards' stimulating and provocative book advances the thesis that the appropriate axiomatic basis for inductive inference is not that of probability, with its addition axiom, but rather likelihood - the concept introduced by Fisher as a measure of relative support amongst different hypotheses. Starting from the simplest considerations and assuming no more than a modest acquaintance with probability theory, the author sets out to reconstruct nothing less than a consistent theory of statistical inference in science.

Maximum likelihood (ML) estimation of categorical multitrait-multimethod (MTMM) data is challenging because the likelihood involves high-dimensional integrals over the crossed method and trait factors, with no known closed-form solution. The purpose of the study is to introduce three newly developed ML methods that are eligible for estimating MTMM models with categorical responses: Variational maximization-maximization (e.g., Rijmen and Jeon, 2013 ), alternating imputation posterior (e.g., Cho and Rabe-Hesketh, 2011 ), and Monte Carlo local likelihood (e.g., Jeon et (...) al., under revision). Each method is briefly described and its applicability for MTMM models with categorical data are discussed. (shrink)

The likelihood principle is typically understood as a constraint on any measure of evidence arising from a statistical experiment. It is not sufficiently often noted, however, that the LP assumes that the probability model giving rise to a particular concrete data set must be statistically adequate—it must “fit” the data sufficiently. In practice, though, scientists must make modeling assumptions whose adequacy can nevertheless then be verified using statistical tests. My present concern is to consider whether the LP applies to (...) these techniques of model verification. If one does view model verification as part of the inferential procedures that the LP intends to constrain, then there are certain crucial tests of model verification that no known method satisfying the LP can perform. But if one does not, the degree to which these assumptions have been verified is bracketed from the evidential evaluation under the LP. Although I conclude from this that the LP cannot be a universal constraint on any measure of evidence, proponents of the LP may hold out for a restricted version thereof, either as a kind of “ideal” or as defining one among many different forms of evidence. (shrink)

We propose a new hybrid data mining method for predicting protein-protein interactions combining Likelihood-Ratio with rule induction algorithms. In essence, the new method consists of using a rule induction algorithm to discover rules representing partitions of the data, and then the discovered rules are interpreted as “bins” which are used to compute likelihood ratios. This new method is applied to the prediction of protein-protein interactions in the Saccharomyces Cerevisiae genome, using predictive genomic features in an (...) integrated scheme. The results show that the new hybrid method outperforms a pure likelihood ratio based approach. (shrink)

Crowdfunding entails small funds or contributions collected from the public to support and develop certain services or products. It has been widely adopted as an alternative method to fund social, cultural, and technological projects. Crowdfunding platforms can capitalize the social and digital networks, making them more efficient in targeting funders with minimum operational costs. The emergence of crowdfunding platforms as social information systems attracts researchers and academicians to study their increasing acceptance. In complement to qualitative and big-data analyses, behavioral (...) models can offer robust insights into why individuals like to participate in the activities generated on these platforms. Prior research focuses on the user's acceptance of these platforms, but less attention has been given to users' engagement in crowdfunding-based social welfare projects. The study highlights people's crowdfunding intentions to fund social welfare projects based on the elaboration likelihood model. The study hypothesizes argument quality and technical advantage as central signals and shared value and reputation as peripheral signals, where outcome efficacy and social consciousness directly affect intentions to participate and moderate the relationship between signals and intentions. We collect data from 467 potential donors from China's 30 online crowdfunding platforms. The results indicate a more significant peripheral route effect on donation participation in social welfare crowdfunding. Social consciousness significantly predicts donation intentions where outcome efficacy and social consciousness strengthen the relationship between argument quality, shared values, and donation intentions to participate in socially responsible crowdfunding. The study provides implications for social collaboration for welfare projects through these platforms in light of these dynamic factors. (shrink)

The three main approaches in statistical inference—classical statistics, Bayesian and likelihood—are in current use in phylogeny research. The three approaches are discussed and compared, with particular emphasis on theoretical properties illustrated by simple thought-experiments. The methods are problematic on axiomatic grounds, extra-mathematical grounds relating to the use of a prior or practical grounds. This essay aims to increase understanding of these limits among those with an interest in phylogeny.

The most important thesis of "Of Miracles" has no special connection with miracles: I mean the perfectly general thesis that testimonial evidence should be evaluated by the method of balancing likelihoods, which is a relatively informal version of the calculus of changes (or of probabilities). C. S. Peirce argues that the method is radically unsuited to the assessment of historical testimony. In this paper, I do essentially two things: (1) set out both an informal and a formal account (...) of Hume’s method; and (2) collect, systematize, and discuss Peirce’s somewhat scattered animadversions upon Hume’s use of this method. As part of (2), I explore some lines of thought that Peirce suggests but does not develop. (shrink)

Thought-intrusions, automatic inferences, and other unintended thought are beginning to play an important role in the study of psychiatric disease as well as normal thought processes. We examine one method for study of task-unrelated imagery and thought . TUIT likelihood was shown to be reliably measured over a wide range of vigilance tasks, to have high short-term and long-term test-retest reliability, and to be sensitive to information processing demands. Likelihood of TUITs was shown to be different as (...) a function of aging, hyperactivity, time of day, and level of depression. Thus, we now can reliably measure the influence of endogenous and exogenous influences on TUITs. In addition, TUIT measurement was proposed as a minimally interfering and natural second task for determining resource utilization in a primary task. Finally, this method was offered as a reliable approach to quantification of such mental states as obsessions and drug craving and addiction. (shrink)

I present a new proof of the likelihood principle that avoids two responses to a well-known proof due to Birnbaum ([1962]). I also respond to arguments that Birnbaum’s proof is fallacious, which if correct could be adapted to this new proof. On the other hand, I urge caution in interpreting proofs of the likelihood principle as arguments against the use of frequentist statistical methods. 1 Introduction2 The New Proof3 How the New Proof Addresses Proposals to Restrict Birnbaum’s Premises4 (...) A Response to Arguments that the Proofs Are Fallacious5 Conclusion. (shrink)

Do the methods of science lead to atheism? This is different from asking whether the results of science (e.g., well‐confirmed theories in evolutionary biology or cosmology) have that consequence. In this chapter, I consider several philosophical theories about scientific reasoning and trace out their implications for atheism, theism, and agnosticism. These theories include different versions of empiricism, logical positivism, inference to the best explanation, Bayesianism, hypothetico‐deductivism, and the principle of parsimony (Ockham's razor).

The notion that an independent central bank reduces a country’s inflation is a controversial hypothesis. To date, it has not been possible to satisfactorily answer this question because the complex macroeconomic structure that gives rise to the data has not been adequately incorporated into statistical analyses. We develop a causal model that summarizes the economic process of inflation. Based on this causal model and recent data, we discuss and identify the assumptions under which the effect of central bank independence on (...) inflation can be identified and estimated. Given these and alternative assumptions, we estimate this effect using modern doubly robust effect estimators, i.e., longitudinal targeted maximum likelihood estimators. The estimation procedure incorporates machine learning algorithms and is tailored to address the challenges associated with complex longitudinal macroeconomic data. We do not find strong support for the hypothesis that having an independent central bank for a long period of time necessarily lowers inflation. Simulation studies evaluate the sensitivity of the proposed methods in complex settings when certain assumptions are violated and highlight the importance of working with appropriate learning algorithms for estimation. (shrink)

Maximum Parsimony (MP) and Maximum Likelihood (ML) are two methods for evaluating which phlogenetic tree is best supported by data on the characteristics of leaf objects (which may be species, populations, or individual organisms). MP has been criticized for assuming that evolution proceeds parsimoniously -- that if a lineage begins in state i and ends in state j, the way it got from i to j is by the smallest number of changes. MP has been criticized for needing to (...) assume some model or other of the evolutionary process even though biologists often do not know what that process really is. This paper critically evaluates both criticisms. (shrink)

We examine collective decision-making in a jury voting game under the unanimity rule when voters have ambiguous beliefs. Unlike in existing studies (Ellis in Theoretical Economics 11:865–895, 2016; Fabrizi et al., in: AUT Economics Working Paper, 2021; Ryan in Theory and Decision 90:543–577, 2021), the locus of ambiguity is the likelihood function (signal precision) rather than the prior. This significantly alters the properties of symmetric equilibria. While prior ambiguity may induce multiple equilibria (Fabrizi et al., in: AUT Economics Working (...) Paper, 2021; Ryan in Theory and Decision 90:543–577, 2021) we show that, under likelihood ambiguity, there exists a unique non-trivial symmetric responsive equilibrium that takes the same form as in the absence of ambiguity (Feddersen and Pesendorfer in The American Political Science Review 92:23–35, 1998). Moreover, likelihood ambiguity partially offsets the pernicious effects of pivotality on decision quality: the frequency of Type I error (convicting the innocent) is typically lower than in the absence of ambiguity. (shrink)

A SEM-based approach using likelihood-based confidence interval has been proposed to form confidence intervals for unstandardized and standardized indirect effect in mediation models. However, when used with the maximum likelihood estimation, this approach requires that the variables are multivariate normally distributed. This can affect the LBCIs of unstandardized and standardized effect differently. In the present study, the robustness of this approach when the predictor is not normally distributed but the error terms are conditionally normal, which does not violate (...) the distributional assumption of ordinary least squares estimation, is compared to four other approaches: nonparametric bootstrapping, two variants of LBCI, LBCI assuming the predictor is fixed and LBCI based on ADF estimation, and Monte Carlo. A simulation study was conducted using a simple mediation model and a serial mediation model, manipulating the distribution of the predictor. The Monte Carlo method performed worst among the methods. LBCI and LBCI-Fixed-X had suboptimal performance when the distributions had high kurtosis and the population indirect effects were medium to large. In some conditions, the problem was severe even when the sample size was large. LBCI-ADF and nonparametric bootstrapping had coverage probabilities close to the nominal value in nearly all conditions, although the coverage probabilities were still suboptimal for the serial mediation model when the sample size was small with respect to the model. Implications of these findings in the context of this special case of nonnormal data were discussed. (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)

We consider a confidence parametrization of binary information sources in terms of appropriate likelihood ratios. This parametrization is used for Bayesian belief updates and for the equivalent comparison of binary experiments. In contrast to the standard parametrization of a binary information source in terms of its specificity and its sensitivity, one of the two confidence parameters is sufficient for a Bayesian belief update conditional on a signal realization. We introduce a confidence-augmented receiver operating characteristic for comparisons of binary experiments (...) for a class of “balanced” decision problems, relative to which the confidence order offers a higher resolution than Blackwell’s informativeness order. Where observation is concerned, Chance favors only the prepared mind.—Louis Pasteur (1822–1895). (shrink)

To what extent does payment method (managed care vs. out of pocket) influence the likelihood that an independent practitioner will assign a Diagnostic and Statistical Manual of Mental Disorders (American Psychiatric Association, 1994) diagnosis to a client? When a practitioner does diagnose, how does payment method influence the specific choice of a diagnostic category? Independent practitioners responded to a vignette describing a fictitious client with symptoms of depression or anxiety. In half of the vignettes, the fictitious client (...) intended to pay via managed care; in the other half, the fictitious client intended to pay out of pocket. Payment method had a very significant impact on diagnosis such that relative to out-of-pocket clients, managed care clients were much more likely to receive diagnoses and more likely to receive adjustment disorder diagnoses in particular. We discuss implications involving informed consent and other ethical issues. (shrink)

BackgroundDepression is a serious mental disorder often accompanied by emotional and physiological disorders. Visceral fat index is the current standard method in the evaluation of visceral fat deposition. In this study, we explored the association between VAI and depression in the American population using NHANES data.MethodsA total of 2,577 patients were enrolled for this study. Data were collected through structured questionnaires. Subgroup analysis for the relationship between VAI and depression was evaluated using multivariate regression analysis after adjustment for potential (...) confounding factors.ResultsFor every 1 unit increase in VAI, the clinical depression increased by 14%. High VAI scores increased the highest risk of developing depression. Subgroup analysis demonstrated a strong and stable association between VAI and the development of depression.ConclusionOur study showed that depressive symptoms are associated with a high ratio of visceral adiposity index after controlling confounding factors. (shrink)

Three related intuitions are explicated in this paper. The first is the idea that there must be some kind of probabilistic version of the HD-method, a 'Hypothetico-Probabilistic method', in terms of something like probabilistic consequences, instead of deductive consequences. According to the second intuition, the comparative application of this method should also be functional for some probabilistic kind of empirical progress, and according to the third intuition this should be functional for something like probabilistic truth approximation. In (...) all three cases, the guiding idea is to explicate these intuitions by explicating the crucial notions as appropriate 'concretizations' of their deductive analogs, being 'idealizations'. It turns out that the comparative version of the proposed HP-method amounts to the likelihood comparison method applied to the cumulated evidence. This method turns out to be not only functional for probabilistic empirical progress but also for probabilistic truth approximation. The latter is based on a probabilistic threshold theorem constituting for this reason the analog of the deductive success theorem. (shrink)

Robots are increasingly envisaged as our future cohabitants. However, while considerable progress has been made in recent years in terms of their technological realization, the ability of robots to inter-act with humans in an intuitive and social way is still quite limited. An important challenge for social robotics is to determine how to design robots that can perceive the user’s needs, feelings, and intentions, and adapt to users over a broad range of cognitive abilities. It is conceivable that if robots (...) were able to adequately demonstrate this, humans would eventually accept them as social companions. We argue that the best way to achieve this is using a systematic experimental approach based on behavioral and physiological neuroscience methods such as motion/eye tracking, electroencephalography (EEG), or functional near-infrared spectroscopy (fNIRS) embedded in interactive human-robot paradigms. This approach requires understanding how humans interact with each other, how they perform tasks together and how they develop feelings of social connection over time, and using these insights to formulate design principles that make social robots attuned to the workings of the human brain. In this review, we put forward the argument that the likelihood of artificial agents being perceived as social companions can be increased by designing them in a way that they are perceived as intentional agents that activate areas in the human brain involved in social-cognitive processing. We first review literature related to social-cognitive mechanisms involved in human-human interactions, and high-light the importance of perceiving others as intentional agents to activate these brain areas. We then discuss how attribution of intentionality can positively affect human-robot interaction by (a) fostering feelings of social connection, empathy and prosociality, and by (b) enhancing performance on joint human-robot tasks. Lastly, we describe circumstances under which attribution of intentionality to robot agents might be disadvantageous, and discuss challenges associated with designing social robots that are inspired by neuroscientific principles. (shrink)

This paper introduces the new novel four-parameter Weibull distribution named as the Marshall–Olkin alpha power Weibull distribution. Some statistical properties of the distribution are examined. Based on Type-I censored and Type-II censored samples, maximum likelihood estimation, maximum product spacing, and Bayesian estimation for the MOAPW distribution parameters are discussed. Numerical analysis using real data sets and Monte Carlo simulation are accomplished to compare various estimation methods. This novel model’s supremacy upon some famous distributions is explained using two real data (...) sets and it is shown that the MOAPW model can achieve better fits than other competitive distributions. (shrink)

Thomas Nickles challenges my thesis that innovative discoveries can be based on deliberately chosen problems and research strategies. He suggests that all significant innovation can be seen as such only in retrospect and that its generation must be serendipitous. Here I argue in response that significant innovations can and do often arise from self conscious critical appraisal of orthodox practice combined with regulated though speculative abductive argumentation to alternative explanatory schemata. Orthodox practice is not based upon monolithic systems of belief (...) about the subject of inquiry. Rather major domains of scientific practice often are approached from different conceptualizations that provide grounds for critical dialectic and consilient empirical information. Abductive arguments that meet appropriate conditions of likelihood, probability and analogy are an important means of justifying allocating resources to innovative practices that have yet to produce products that can rival those of established orthodoxy. (shrink)

Change blindness provides a new technique for mapping visual attention with unprecedented spatial and temporal resolution. Change blindness can occur when a brief full‐field blank interferes with the detection of changes in a scene that occur during the blank. This interference can be overcome by attending to the location of a change. Because changes are detected at attended locations, but not at unattended locations, detection accuracy provides an indirect measure of the distribution of visual attention. The likelihood of detecting (...) a new element in a scene provides a measure of the occurrence of attention at that element's location. Potential new directions, advantages, and problems with this method are considered. (shrink)

Reilly approaches his topic by presenting the spirit of science and the phases of scientific inquiry as Peirce saw it, keeping before the reader, at all times, Peirce’s overarching view of man and the universe. The two prevailing themes guiding Peirce’s thought are 1) that there is a special conformity of the human mind to nature and of nature to God, and 2) that there is an architectonic qualifying all the various types and levels of treatment which occupy the philosopher’s (...) interest. The first question examined is the nature of the scientific concern. For Peirce, the scientist’s spirit is marked by the pure love of knowledge. It is important to note the theoretical aspect because it explains the possibility of holding belief in abeyance while examining nature: the purity of motive allows that proper questions will be asked and errors will be readily corrected. The scientist’s purpose is the real truth of things; he begins with questions about the world. There are four stages of scientific method: 1) The scientist observes nature as a thinking, analytic inquirer. Observation presupposes that nature is intelligibly structured. 2) He formulates an explanatory hypothesis which is a process of bringing a manifold of characters to a unified whole. 3) By deduction, the inquirer gathers experiential consequents of the hypothesis. 4) By induction the question is put to nature and observed phenomena are matched to the predicted phenomena, resulting in either truth or a modified hypothesis. Peirce’s principle of the kinship of man’s mind to nature supports his dictum to follow instinct over reasoned likelihood in choosing hypotheses. Also important is the doctrine of moderate fallibilism which holds that there is a convergence upon the truth founded upon the regularity of nature, but that chance is a real factor due to nature’s evolution. Reilly’s book gives an adequate account of the aspects of Peirce’s scientific method sacrificing specific and detailed analysis to a more general approach wherein he shows the unity operative throughout Peirce’s thinking. A good index and copious notes are provided.—W. A. F. (shrink)

This study develops an internal–external institutional framework that explains why firms act in socially responsible ways in the emerging country context of China. Utilizing a mixed method of in-depth interviews and a survey study of 225 Chinese firms, the author found that internal institutional factors, including ethical corporate culture and top management commitment, and external institutional factors, including globalization pressure, political embeddedness, and normative social pressure, will affect the likelihood of firms to act in socially responsible ways. In (...) particular, implicit ethical corporate culture plays a key role in predicting different aspects of corporate social responsibility, while external institutional mechanisms mainly predict market-oriented CSR initiatives. This study contributes to the research on CSR antecedents by showing that in the emerging economy of China, CSR toward nonmarket stakeholders is more closely intertwined with corporate tradition and values, while legitimacy-seeking CSR activities are still limitedly rewarded. (shrink)

A new continuous version of the inverse flexible Weibull model is proposed and studied. Some of its properties such as quantile function, moments and generating functions, incomplete moments, mean deviation, Lorenz and Bonferroni curves, the mean residual life function, the mean inactivity time, and the strong mean inactivity time are derived. The failure rate of the new model can be “increasing-constant,” “bathtub-constant,” “bathtub,” “constant,” “J-HRF,” “upside down bathtub,” “increasing,” “upside down-increasing-constant,” and “upside down.” Different copulas are used for deriving many (...) bivariate and multivariate type extensions. Different non-Bayesian well-known estimation methods under uncensored scheme are considered and discussed such as the maximum likelihood estimation, Anderson Darling estimation, ordinary least square estimation, Cramér-von-Mises estimation, weighted least square estimation, and right tail Anderson Darling estimation methods. Simulation studies are performed for comparing these estimation methods. Finally, two real datasets are analyzed to illustrate the importance of the new model. (shrink)

This article contributes to our understanding of how communication of ethical guidelines by managers may reduce the likelihood of employee unethical behavior. We conduct two vignette experiments to assess the impact of communicating two types of ethical guidelines—general and specific. The second study employs mixed methods experimental design, collecting qualitative data during the experiment. We find that communicating ethical guidelines by managers reduces the likelihood of unethical behavior, but contrary to our hypothesis and prior literature, we observe that (...) general ethical guidelines are more effective than specific ethical guidelines. We conduct thematic coding of open-ended qualitative responses and integrate the findings of qualitative analysis with the quantitative analyses to provide insights into the counter-hypothetical finding. With specific guidelines, we observe that participants use specific details to negate or rationalize ethical concerns, and with general guidelines, participants recognize ethical concerns and are less likely to downplay them. We conclude by discussing the implications of these findings for research on ethical leadership. (shrink)

Existing scholarship grapples with how impact investors measure positive impacts, but little attention has been paid to negative impact or limitations to positive impact, indicating a need to study “impact risk.” Impact risk refers to the likelihood that impact will be different than expected. In this paper, we study how impact risk is considered in practice. First, through a yearlong data collection effort including interviews with 124 impact investors, we are the first, to our knowledge, to document the consideration (...) of impact risk by practitioners. From this qualitative study, we develop two hypotheses about cognitive mechanisms related to impact risk. Second, we test these hypotheses through a vignette-based experiment with an online sample (N = 435). We find that win–win views of business, exemplified by the impact investing industry, can lead to inadequate consideration of impact risk. Inadequate consideration of impact risk matters for ethical reasons: with beneficiaries—people and planet—in urgent need of real solutions, investors and academics should take impact risk seriously. (shrink)

Results: We analyzed 1,402 surveys and 15 in-depth interviews. Many (32%) CL participants reported greater difficulty refilling medications and a minority (14%) reported greater difficulty accessing HIV care during the pandemic. Most (99%) Opt4Mamas participants reported no difficulty refilling medications or accessing HIV/pregnancy care. Among the CL participants, older women were less likely (aOR = 0.95, 95% CI: 0.92–0.98) and women with more children were more likely (aOR = 1.13, 95% CI: 1.00–1.28) to report difficulty refilling medications. Only 2% of (...) CL participants reported greater difficulty managing FP and most (95%) reported no change in likelihood of using FP or desire to get pregnant. Qualitative analysis revealed three major themes: (1) adverse organizational/economic implications of the pandemic, (2) increased importance of pregnancy prevention during the pandemic, and (3) fear of contracting COVID-19. (shrink)

This volume brings together for the first time the diverse threads within the growing field of serendipity research, to reflect both on the origins of this emerging field within different disciplines as well as its increasing influence as its own field with foundational texts and emerging practices. The phenomenon of serendipity has been described in many ways since Horace Walpole initially coined the term in 1754 to categorize those discoveries that happen by “both accidents and sagacity”. This book offers a (...) sampling of perspectives from experts in serendipity research from organizational studies, management theory, information science and library studies, psychology, literature, computer science, social science, ethics, and the history and philosophy of science. Considerations about the importance and role of serendipity are being raised now across science (both empirical and theoretical) as well as practice (from art and innovation to leadership and governance), with ever more eyes looking closer at its significance in human history and the likelihood it will play a key, while unpredictable, role in forming our future. Serendipity Science represents an emerging, and also important and potentially necessary field of study, if we are to deal well as a society with our complex times and uncertain future. (shrink)

In this article, a highly effective Bayesian sampling algorithm based on auxiliary variables is proposed to analyze aberrant response and response time data. The new algorithm not only avoids the calculation of multidimensional integrals by the marginal maximum likelihood method but also overcomes the dependence of the traditional Metropolis–Hastings algorithm on the tuning parameter in terms of acceptance probability. A simulation study shows that the new algorithm is accurate for parameter estimation under simulation conditions with different numbers of (...) examinees, items, and speededness levels. Based on the sampling results, the powers of the two proposed Bayesian assessment criteria are tested in the simulation study. Finally, a detailed analysis of a high-state and large-scale computerized adaptive test dataset is carried out to illustrate the proposed methodology. (shrink)

In ecology, if the considered area or space is large, the spatial distribution of individuals of a given plant species is never homogeneous; plants form different patches. The homogeneity change in space or in time (in particular, the related change-point problem) is an important research subject in mathematical statistics. In the paper, for a given data system along a straight line, two areas are considered, where the data of each area come from different discrete distributions, with unknown parameters. In the (...) paper a method is presented for the estimation of the distribution change-point between both areas and an estimate is given for the distributions separated by the obtained change-point. The solution of this problem will be based on the maximum likelihood method. Furthermore, based on an adaptation of the well-known bootstrap resampling, a method for the estimation of the so-called change-interval is also given. The latter approach is very general, since it not only applies in the case of the maximum-likelihood estimation of the change-point, but it can be also used starting from any other change-point estimation known in the ecological literature. The proposed model is validated against typical ecological situations, providing at the same time a verification of the applied algorithms. (shrink)

Akaike’s framework for thinking about model selection in terms of the goal of predictive accuracy and his criterion for model selection have important philosophical implications. Scientists often test models whose truth values they already know, and they often decline to reject models that they know full well are false. Instrumentalism helps explain this pervasive feature of scientific practice, and Akaike’s framework helps provide instrumentalism with the epistemology it needs. Akaike’s criterion for model selection also throws light on the role of (...) parsimony considerations in hypothesis evaluation. I explain the basic ideas behind Akaike’s framework and criterion; several biological examples, including the use of maximum likelihood methods in phylogenetic inference, are considered. (shrink)

The studies show a positive and direct relationship between basic psychological needs satisfaction and intrinsic motivation of the students. However, there is a lack of studies that analyze the psychological processes that affect these relationships. For this reason, the purpose of this study was to investigate the mediating role of academic integration on the relationship between basic psychological needs satisfaction and intrinsic motivation of Chilean university students. The participants were a total of 580 students from a university in northern Chile, (...) 359 women and 221 men. The mediation analysis was performed by structural equations modeling, using the maximum likelihood method and the bootstrapping procedure with 10,000 iterations. The results indicated that academic integration partially mediated the relationship between basic psychological needs satisfaction and intrinsic motivation of the students. Therefore, the basic psychological needs satisfaction had an indirect effect on the intrinsic motivation of the students through academic integration. It is concluded that the academic integration constitutes a psychological process that promotes the development of intrinsic motivation for learning. The practical implications are discussed along with the limitations of the study and recommendations for future research. (shrink)

This study aimed to analyze the mediating effect of tolerance of uncertainty and trait anxiety on future self-continuity and intention to use Internet wealth management systems. A questionnaire survey was distributed online and a total of 388 participants completed questionnaire, The questionnaire included the following scales: Chinese version of the FSC, Intention to Use the Internet Wealth Management, TU, and TA. Pearson correlation was used to investigate the correlation coefficient between variables while the sequential regression method was used to (...) analyze relationship between variables. To analyze the collected data, the SPSS 26.0 was used. A two-step procedure was applied to analyze the mediation effect. Confirmatory factor analysis was conducted to test the measurement model. Afterward, the Maximum Likelihood method was used for path analysis, and the Bias-corrected Bootstrap method was used to investigate determine the estimated value and confidence interval of the mediating effect. To analyze the mediation effect, the Mplus 7.0 was used. The results showed that FSC positively predicted individuals’ Internet wealth management systems. Furthermore, TU and TA played complete serial multiple mediating roles between FSC and IUIWM. The role of TA and TU have negative impact on intention to use. This study provides a theoretical basis in personality psychology that Internet financial product suppliers can use to improve the attractiveness of their products. Product managers can subdivide users according to these personality traits to provide customized products. (shrink)

We propose a method for estimating subjective beliefs, viewed as a subjective probability distribution. The key insight is to characterize beliefs as a parameter to be estimated from observed choices in a well-defined experimental task and to estimate that parameter as a random coefficient. The experimental task consists of a series of standard lottery choices in which the subject is assumed to use conventional risk attitudes to select one lottery or the other and then a series of betting choices (...) in which the subject is presented with a range of bookies offering odds on the outcome of some event that the subject has a belief over. Knowledge of the risk attitudes of subjects conditions the inferences about subjective beliefs. Maximum simulated likelihood methods are used to estimate a structural model in which subjects employ subjective beliefs to make bets. We present evidence that some subjective probabilities are indeed best characterized as probability distributions with non-zero variance. (shrink)

The COVID-19 pandemic is an unprecedented time in history. Surrounding this pandemic are many enormous uncertainties across the globe. Severe consequences have assessed for the incomes of almost 84% of employers and 68% of self-employed who are working and living in countries that are or have went through a phase of closing workplaces. Similarly, the global rate of unemployment is also expected to be increased in the coming years as 54% of employers worldwide are running their businesses in the hardest-hit (...) sectors. All of these clearly show the uneven impact of the Coronavirus crisis which will remarkably compound already present inequalities, difficulties, and vulnerabilities. The economic ramifications for 186 countries under the crunch of the COVID-19 pandemic is also considered tremendous for Pakistan. The core aim of this research was to test a new conceptual framework depicting the ramifications of restructuring processes carried out by management for their organizations amidst the COVID-19 pandemic on an Institute’s reputation as an employer brand. It also investigates the impact of perceived restructuring on a corporate brand promise made by the university or institute from the viewpoints of other key stakeholders and potential job seekers. The current study had proposed four hypotheses and according to the results of Structural Equation Modeling, the direct hypothesis based upon the relationship between restructuring and employer branding has been rejected. This study shows that restructuring and employer branding has a negative and insignificant effect on each other. The second direct hypothesis of the study that measures the effect of restructuring on corporate branding has been accepted. A corporate brand is a kind of a hub and it considers how an institute treats and deals with all of its stakeholders. It is different from employer brand as the perceptions of employees were the main focus. So, according to the results restructuring did not cause massive damage to the overall outlook of the institute. Furthermore, for the purpose of mediation analysis, the maximum likelihood method by bootstrapping was adopted to test the indirect hypotheses of the study. Crowdsourcing was introduced as a mediator in this study with restructuring, employer, and corporate brand all together in one framework, which is the novel aspect of this study. There are two indirect hypotheses and according to the results both of them did not show any insignificant results. Firstly, the study analyzed mediation among crowdsourcing, restructuring, and employer branding which was fully accepted as the results showed full mediation between these constructs. Secondly, the study analyzed mediation among crowdsourcing, restructuring, and corporate branding which was partially accepted as results showed partial mediation between these constructs. (shrink)

This study investigated the impact of three prior distributions: matched, standard vague, and hierarchical in Bayesian estimation parameter recovery in two and one parameter models. Two Bayesian estimation methods were utilized: Markov chain Monte Carlo (MCMC) and the relatively new, Variational Bayesian (VB). Conditional (CML) and Marginal Maximum Likelihood (MML) estimates were used as baseline methods for comparison. Vague priors produced large errors or convergence issues and are not recommended. For both MCMC and VB, the hierarchical and matched priors (...) showed the lowest root mean squared errors (RMSEs) for ability estimates; RMSEs of difficulty estimates were similar across estimation methods. For the standard errors (SEs), MCMC-hierarchical displayed the largest values across most conditions. SEs from the VB estimation were among the lowest in all but one case. Overall, VB-hierarchical, VB-matched, and MCMC-matched performed best. VB with hierarchical priors are recommended in terms of their accuracy, and cost and (subsequently) time effectiveness. (shrink)

In the existing Reinforcement Learning, it is difficult and time consuming to find appropriate the meta-parameters such as learning rate, eligibility traces and temperature for exploration, in particular on a complicated and large-scale problem, the delayed reward often occurs and causes a difficulty in solving the problem. In this paper, we propose a novel method introducing a temperature distribution for reinforcement learning. In addition to the acquirement of policy based on profit sharing, the temperature is given to each state (...) and is trained by hill-climbing method using likelihood function based on success and failure of the task. The proposed method can reduce the parameter setting according to the given problems. We showed the performance on the grid world problem and the control of Acrobot. (shrink)

It is well known that Bayes’ theorem (with likelihood ratios) can be used to calculate the impact of evidence, such as a ‘match’ of some feature of a person. Typically the feature of interest is the DNA profile, but the method applies in principle to any feature of a person or object, including not just DNA, fingerprints, or footprints, but also more basic features such as skin colour, height, hair colour or even name. Notwithstanding concerns about the extensiveness (...) of databases of such features, a serious challenge to the use of Bayes in such legal contexts is that its standard formulaic representations are not readily understandable to non-statisticians. Attempts to get round this problem usually involve representations based around some variation of an event tree. While this approach works well in explaining the most trivial instance of Bayes’ theorem (involving a single hypothesis and a single piece of evidence) it does not scale up to realistic situations. In particular, even with a single piece of match evidence, if we wish to incorporate the possibility that there are potential errors (both false positives and false negatives) introduced at any stage in the investigative process, matters become very complex. As a result we have observed expert witnesses (in different areas of speciality) routinely ignore the possibility of errors when presenting their evidence. To counter this, we produce what we believe is the first full probabilistic solution of the simple case of generic match evidence incorporating both classes of testing errors. Unfortunately, the resultant event tree solution is too complex for intuitive comprehension. And, crucially, the event tree also fails to represent the causal information that underpins the argument. In contrast, we also present a simple-to-construct graphical Bayesian Network (BN) solution that automatically performs the calculations and may also be intuitively simpler to understand. Although there have been multiple previous applications of BNs for analysing forensic evidence—including very detailed models for the DNA matching problem, these models have not widely penetrated the expert witness community. Nor have they addressed the basic generic match problem incorporating the two types of testing error. Hence we believe our basic BN solution provides an important mechanism for convincing experts—and eventually the legal community—that it is possible to rigorously analyse and communicate the full impact of match evidence on a case, in the presence of possible errors. (shrink)

Model validation in computational cognitive psychology often relies on methods drawn from the testing of theories in experimental physics. However, applications of these methods to computational models in typical cognitive experiments can hide multiple, plausible sources of variation arising from human participants and from stochastic cognitive theories, encouraging a “model fixed, data variable” paradigm that makes it difficult to interpret model predictions and to account for individual differences. This article proposes a likelihood‐based, “data fixed, model variable” paradigm in which (...) models are treated as stochastic processes in experiments with participant‐to‐participant variation that can be applied to a broad range of mechanistic cognitive architectures. This article discusses the implementation and implications of this view in model validation, with a concrete focus on a simple class of ACT‐R models of cognition. This article is not intended as a recipe for broad application of these preliminary, proof‐of‐concept methods, but as a framework for communication between statisticians searching for interesting problems in the cognitive modeling sphere, and cognitive modelers interested in generalizing from deterministic to stochastic model validation, in the face of random variation in human experimental data. (shrink)

Conceptual engineering is a philosophical method that aims to design and spread conceptual and linguistic devices to cause meaningful changes in the world. So far, however, conceptual engineers have struggled to successfully spread the conceptual and linguistic entities they have designed to their target communities. This paper argues that conceptual engineering is far more likely to succeed if it incorporates empirical data and empirical methods. Because the causal factors influencing successful propagation of linguistic or conceptual devices are as complicated (...) and interwoven as they are, proper empirical research will greatly boost the likelihood that propagation is successful. In arguing for the superiority of empirical conceptual engineering over armchair-based conceptual engineering, this paper proposes a framework for understanding the causal forces at play in propagation. This is a three-part framework between the label of a lexical item, the psychological states associated with the lexical item, and the worldly things associated with the lexical item. By understanding the way causal forces affecting propagation play out at these three levels, conceptual engineers can better conceptualize, study, and harness the different causal forces affecting the success of their conceptual engineering projects. (shrink)

Causal processes can give rise to distinctive distributions in the linguistic variables that they affect. Consequently, a secure understanding of a variable's distribution can hold a key to understanding the forces that have causally shaped it. A storied distribution in linguistics has been Zipf's law, a kind of power law. In the wake of a major debate in the sciences around power-law hypotheses and the unreliability of earlier methods of evaluating them, here we re-evaluate the distributions claimed to characterize phoneme (...) frequencies. We infer the fit of power laws and three alternative distributions to 166 Australian languages, using a maximum likelihood framework. We find evidence supporting earlier results, but also nuancing them and increasing our understanding of them. Most notably, phonemic inventories appear to have a Zipfian-like frequency structure among their most-frequent members (though perhaps also a lognormal structure) but a geometric (or exponential) structure among the least-frequent. We compare these new insights the kinds of causal processes that affect the evolution of phonemic inventories over time, and identify a potential account for why, despite there being an important role for phonetic substance in phonemic change, we could still expect inventories with highly diverse phonetic content to share similar distributions of phoneme frequencies. We conclude with priorities for future work in this promising program of research. (shrink)

Categorical loudness scaling (CLS) measures provide useful information about an individual’s loudness perception across the dynamic range of hearing. A probability model of CLS categories has previously been described as a multi-category psychometric function (MCPF). In the study, a representative “catalog” of potential listener MCPFs was used in conjunction with maximum-likelihood estimation to derive CLS functions for participants with normal hearing and with hearing loss. The approach of estimating MCPFs for each listener has the potential to improve the accuracy (...) of the CLS measurements, particularly when a relatively low number of data points are available. The present study extends the MCPF approach by using Bayesian inference to select stimulus parameters that are predicted to yield maximum expected information (MEI) during data collection. The accuracy and reliability of the MCPF-MEI approach were compared to the standardized CLS measurement procedure (ISO16832:2006). A non-adaptive, fixed-level, paradigm served as a “gold-standard” for this comparison. The test time required to obtain measurements in the standard procedure is a major barrier to its clinical uptake. Test time was reduced from approximately 15 minutes to approximately 3 minutes with the MEI-adaptive procedure. Results indicated that the test-retest reliability and accuracy of the MCPF-MEI adaptive procedures were similar to the standardized CLS procedure. Computer simulations suggest that the reliability and accuracy of the MEI procedure were limited by intrinsic uncertainty of the listeners represented in the MCPF catalog. In other words, the MCPF provided insufficient predictive power to significantly improve adaptive-tracking efficiency under practical conditions. Concurrent optimization of both the MCPF catalog and the MEI-adaptive procedure have the potential to produce better results. Regardless of the adaptive-tracking method used in the CLS procedure, the MCPF catalog remains clinically useful for enabling maximum-likelihood determination of loudness categories. (shrink)

Studies of how scientists select research problems suggest the process involves weighing a number of factors, including funding availability, likelihood of success versus failure, and perceived publishability of likely results, among others. In some fields, a strong personal interest in conducting science to bring about particular social and environmental outcomes plays an important role. Conservation biologists are frequently motivated by a desire that their research will contribute to improved conservation outcomes, which introduces a pair of challenging questions for managers (...) of science and scholars of policies governing science: 1) How do scientists integrate that goal into their processes of research priority evaluation, and 2) How can managers and funders of science utilize that knowledge in designing and administering funding programs? I use Q method to uncover four distinct schools of thought amongst researchers and knowledge-users about the merits of possible research priorities for coral reefs; one of the axes along which these schools of thought differ is in their interpretation of how science can and should interact with policy. The results reveal that perceived severity of reef stressors plays a role for some participants. Disciplinary training does not appear to be a major influence on research priority evaluation, but individual participants indicated professional expediency does prevent some researchers from pursuing or advocating that others pursue topics outside of that disciplinary specialty. Influences on and processes in research prioritization uncovered in this study have the potential to lead to counter-productive disciplinary path dependencies. From these results and building on outside literature, I conclude that better coordination and communication about research priorities across disciplines and with broader stakeholders – including knowledge users – could improve the research enterprise’s ability to contribute to meaningful societal and conservation goals. These findings are relevant to researchers and research administrators across disciplines that seek to conduct or fund science that is useful in addressing specific goals. (shrink)

In all likelihood, the Bush Administration’s aim is to continue abusive interrogation methods that on any reasonable definition amount to torture (methods such as waterboarding,” for example, in which a detainee is laid on his back and choked with water until he believes he is drowning). This new law, however, is both foolish and immoral: foolish, because torture won’t make Americans safer; and immoral, because torture is the grossest of affronts to human dignity.