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Prior Beliefs (prior + belief)

Distribution by Scientific Domains

Business, Economics, Finance and Accounting	52%
Medical Sciences	15%
Mathematics and Statistics	15%

Selected Abstracts

Evidence for improved conclusion accuracy after reading about rather than conducting a belief-inconsistent simple physics experiment

APPLIED COGNITIVE PSYCHOLOGY, Issue 6 2010
Maggie DeHart Renken
Prior beliefs that contradict data may interfere with the ability to draw accurate conclusions; however, evidence shows that through engaged activity individuals may learn new information. In Experiment 1, undergraduates performed or read about two physics experiments involving a ball and ramp. The first experiment was consistent with most people's prior beliefs, while the second was inconsistent with most people's prior beliefs. Participants' predictions, experimentation adequacy, conclusions and ability to generalize knowledge were measured to determine the effects of prior belief bias depending on whether participants conducted or read about the experiment. In Experiment 2, a structured hands-on condition was included and developmental trends across adolescence and adulthood were examined. In both Experiments, reading about a belief-inconsistent experiment led to improved conclusion accuracy and ability to generalize knowledge as compared to performing the experiment. This was the case when experiments were performed well and after a 12-week delay for adolescents. Copyright © 2009 John Wiley & Sons, Ltd. [source]

At what degree of belief in a research hypothesis is a trial in humans justified?

JOURNAL OF EVALUATION IN CLINICAL PRACTICE, Issue 2 2002
Benjamin Djulbegovic MD
Abstract Rationale, aims and objectives,Randomized controlled trials (RCTs) have emerged as the most reliable method of assessing the effects of health care interventions in clinical medicine. However, RCTs should be undertaken only if there is substantial uncertainty about which of the trial treatments would benefit a patient most. The purpose of this study is to determine the degree of uncertainty in a research hypothesis before it can empirically be tested in an RCT. Methods,We integrated arguments from three independent lines of research , on ethics, principles of the design and conduct of clinical trials, and medical decision making , to develop a decision model to help solve the dilemma of under which circumstances innovative treatments should be tested in an RCT. Results,We showed that RCTs are the preferable option to resolve uncertainties about competing treatment alternatives whenever we desire reliable, undisputed, high-quality evidence with a low likelihood of false-positive or false-negative results. Conclusions When the expected benefit : risk ratio of a new treatment is small, an RCT is justified to resolve uncertainties over a wide range of prior belief (e.g. 10,90%) in the accuracy of the research hypothesis. Randomized controlled trials represent the best means for resolving uncertainties about health care interventions. [source]

Application of Markov chain Monte Carlo methods to projecting cancer incidence and mortality

JOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES C (APPLIED STATISTICS), Issue 2 2002
Isabelle Bray
Summary. Projections based on incidence and mortality data collected by cancer registries are important for estimating current rates in the short term, and public health planning in the longer term. Classical approaches are dependent on questionable parametric assumptions. We implement a Bayesian age,period,cohort model, allowing the inclusion of prior belief concerning the smoothness of the parameters. The model is described by a directed acyclic graph. Computations are carried out by using Markov chain Monte Carlo methods (implemented in BUGS) in which the degree of smoothing is learnt from the data. Results and convergence diagnostics are discussed for an exemplary data set. We then compare the Bayesian projections with other methods in a range of situations to demonstrate its flexibility and robustness. [source]

Design efficiency for non-market valuation with choice modelling: how to measure it, what to report and why,

AUSTRALIAN JOURNAL OF AGRICULTURAL & RESOURCE ECONOMICS, Issue 3 2008
Riccardo Scarpa
We review the basic principles for the evaluation of design efficiency in discrete choice modelling with a focus on efficiency of WTP estimates from the multinomial logit model. The discussion is developed under the realistic assumption that researchers can plausibly define a prior belief on the range of values for the utility coefficients. D -, A- , B- , S- and C- errors are compared as measures of design performance in applied studies and their rationale is discussed. An empirical example based on the generation and comparison of fifteen separate designs from a common set of assumptions illustrates the relevant considerations to the context of non-market valuation, with particular emphasis placed on C- efficiency. Conclusions are drawn for the practice of reporting in non-market valuation and for future work on design research. [source]

A Bayesian Approach to Surrogacy Assessment Using Principal Stratification in Clinical Trials

BIOMETRICS, Issue 2 2010
Yun Li
Summary A surrogate marker (S) is a variable that can be measured earlier and often more easily than the true endpoint (T) in a clinical trial. Most previous research has been devoted to developing surrogacy measures to quantify how well,S,can replace,T,or examining the use of,S,in predicting the effect of a treatment (Z). However, the research often requires one to fit models for the distribution of,T,given,S,and,Z. It is well known that such models do not have causal interpretations because the models condition on a postrandomization variable,S. In this article, we directly model the relationship among,T,,S, and,Z,using a potential outcomes framework introduced by Frangakis and Rubin (2002,,Biometrics,58, 21,29). We propose a Bayesian estimation method to evaluate the causal probabilities associated with the cross-classification of the potential outcomes of,S,and,T,when,S,and,T,are both binary. We use a log-linear model to directly model the association between the potential outcomes of,S,and,T,through the odds ratios. The quantities derived from this approach always have causal interpretations. However, this causal model is not identifiable from the data without additional assumptions. To reduce the nonidentifiability problem and increase the precision of statistical inferences, we assume monotonicity and incorporate prior belief that is plausible in the surrogate context by using prior distributions. We also explore the relationship among the surrogacy measures based on traditional models and this counterfactual model. The method is applied to the data from a glaucoma treatment study. [source]

Ex Post Voluntary Disclosure Strategies for Insiders,

CONTEMPORARY ACCOUNTING RESEARCH, Issue 4 2003
Carolyn B. Levine
Abstract Asymmetric information between corporate insiders and other market participants can lead to large bid-ask spreads or even a collapse of trade in financial markets. In this paper, we discuss how voluntary disclosure by insiders can remedy this problem. When insiders make disclosure decisions after they become informed, other market participants update their prior beliefs on the basis of both the information disclosed and the information not disclosed. Insiders then give up some or all of their information advantage to weakly increase their profits. These results do not rely on ex ante commitments on the part of the insiders. [source]

A Bayesian model for estimating the effects of drug use when drug use may be under-reported

ADDICTION, Issue 11 2009
Garnett P. McMillan
ABSTRACT Aims We present a statistical model for evaluating the effects of substance use when substance use might be under-reported. The model is a special case of the Bayesian formulation of the ,classical' measurement error model, requiring that the analyst quantify prior beliefs about rates of under-reporting and the true prevalence of substance use in the study population. Design Prospective study. Setting A diversion program for youths on probation for drug-related crimes. Participants A total of 257 youths at risk for re-incarceration. Measurements The effects of true cocaine use on recidivism risks while accounting for possible under-reporting. Findings The proposed model showed a 60% lower mean time to re-incarceration among actual cocaine users. This effect size is about 75% larger than that estimated in the analysis that relies only on self-reported cocaine use. Sensitivity analysis comparing different prior beliefs about prevalence of cocaine use and rates of under-reporting universally indicate larger effects than the analysis that assumes that everyone tells the truth about their drug use. Conclusion The proposed Bayesian model allows one to estimate the effect of actual drug use on study outcome measures. [source]

European Momentum Strategies, Information Diffusion, and Investor Conservatism

EUROPEAN FINANCIAL MANAGEMENT, Issue 3 2005
John A. Doukas
G1; G11; G14 Abstract In this paper we conduct an out-of-sample test of two behavioural theories that have been proposed to explain momentum in stock returns. We test the gradual-information-diffusion model of Hong and Stein (1999) and the investor conservatism bias model of Barberis et al. (1998) in a sample of 13 European stock markets during the period 1988 to 2001. These two models predict that momentum comes from the (i) gradual dissemination of firm-specific information and (ii) investors' failure to update their beliefs sufficiently when they observe new public information. The findings of this study are consistent with the predictions of the behavioural models of Hong and Stein's (1999) and Barberis et al. (1998). The evidence shows that momentum is the result of the gradual diffusion of private information and investors' psychological conservatism reflected on the systematic errors they make in forming earnings expectations by not updating them adequately relative to their prior beliefs and by undervaluing the statistical weight of new information. [source]

The influences on women joining and participating in unions

INDUSTRIAL RELATIONS JOURNAL, Issue 5 2005
Gill Kirton
ABSTRACT This article brings gender to the centre of concepts used to explore union joining and participation, demonstrating that a gender-sensitive analysis adds to our understanding. Using qualitative data from a study of women in two large male-dominated UK trade unions, the article explores four key influences on women's union joining and participation,family, union, work and feminism. While prior beliefs and values played a role in promoting joining and participation, gendered experiences of unions and the workplace had a more profound influence. Feminism affected the nature of participation in that self-identified feminists were more critical of the masculine character of trade unionism. [source]

SHAKEOUTS AND MARKET CRASHES,

INTERNATIONAL ECONOMIC REVIEW, Issue 2 2007
Alessandro Barbarino
This article provides a microfoundation for the rise in optimism that seems to precede market crashes. Small, young markets are more likely to experience stock-price run-ups and crashes. We use a Zeira,Rob type of model in which demand size is uncertain. Optimism then grows rationally if traders' prior distribution over market size has a decreasing hazard. Such prior beliefs are appropriate if most new markets are duds and only a few reach a large size. The crash occurs when capacity outstrips demand. As an illustration, for the period 1971,2001 we fit the model to the Telecom sector. [source]

Primetime Spin: Media Bias and Belief Confirming Information

JOURNAL OF ECONOMICS & MANAGEMENT STRATEGY, Issue 3 2008
Jeremy Burke
This paper develops a model of media bias in which rational agents acquire all their news from the source that is most likely to confirm their prior beliefs. Despite only wishing to make the correct decision, agents act as if they enjoy receiving news that supports their preconceptions. By exclusively gathering information from a source biased towards his prior, there is little chance an agent will be persuaded to change his mind. Moreover, it is shown that even an unbiased agent prefers to receive biased news as it is unlikely to produce conflicting reports. The media caters to the informational demands of consumers and accordingly slants its reporting. It is shown that competition may not decrease bias, but may actually enhance it. Finally, even when it increases bias, competition may improve welfare by expanding the market for news. [source]

Can forecasting performance be improved by considering the steady state?

JOURNAL OF FORECASTING, Issue 1 2008
An application to Swedish inflation, interest rate
Abstract This paper investigates whether the forecasting performance of Bayesian autoregressive and vector autoregressive models can be improved by incorporating prior beliefs on the steady state of the time series in the system. Traditional methodology is compared to the new framework,in which a mean-adjusted form of the models is employed,by estimating the models on Swedish inflation and interest rate data from 1980 to 2004. Results show that the out-of-sample forecasting ability of the models is practically unchanged for inflation but significantly improved for the interest rate when informative prior distributions on the steady state are provided. The findings in this paper imply that this new methodology could be useful since it allows us to sharpen our forecasts in the presence of potential pitfalls such as near unit root processes and structural breaks, in particular when relying on small samples.,,Copyright © 2008 John Wiley & Sons, Ltd. [source]

Work Requirements and Long-Term Poverty

JOURNAL OF PUBLIC ECONOMIC THEORY, Issue 3 2005
FRED SCHROYEN
We study how work requirements can be used to target transfers to the long-term poor. Without commitment, time consistency requires all screening measures to be concentrated in the first phase of the program. We show that this increases the effectiveness of workfare; it is optimal to use work requirements for a wider range of prior beliefs about the size of the poor population, and work requirements are used more intensively. We compare these results with the optimal policy under commitment. [source]

A Bayesian hierarchical distributed lag model for estimating the time course of risk of hospitalization associated with particulate matter air pollution

JOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES C (APPLIED STATISTICS), Issue 1 2009
Roger D. Peng
Summary., Time series studies have provided strong evidence of an association between increased levels of ambient air pollution and increased hospitalizations, typically at a single lag of 0, 1 or 2 days after an air pollution episode. Two important scientific objectives are to understand better how the risk of hospitalization that is associated with a given day's air pollution increase is distributed over multiple days in the future and to estimate the cumulative short-term health effect of an air pollution episode over the same multiday period. We propose a Bayesian hierarchical distributed lag model that integrates information from national health and air pollution databases with prior beliefs of the time course of risk of hospitalization after an air pollution episode. This model is applied to air pollution and health data on 6.3 million enrollees of the US Medicare system living in 94 counties covering the years 1999,2002. We obtain estimates of the distributed lag functions relating fine particulate matter pollution to hospitalizations for both ischaemic heart disease and acute exacerbation of chronic obstructive pulmonary disease, and we use our model to explore regional variation in the health risks across the USA. [source]

Citizens' Perceptions of Ideological Bias in Research on Public Policy Controversies

POLITICAL PSYCHOLOGY, Issue 1 2009
Robert J. MacCoun
How do ordinary citizens react to new policy-relevant findings that they learn about from media mentions or word of mouth? We conducted an experiment embedded in a random-digit-dial (RDD) telephone survey of 1,050 California adults. Respondents heard a description of a hypothetical study on one of four politicized topics or a politically neutral topic (nutrition) and were asked to describe their reactions to the study's main finding. As in prior research, citizens were more skeptical when the findings contradicted their prior beliefs about the topic. But, we also found effects of partisanship and ideology even after controlling for specific issue attitudes. Citizens, especially those holding conservative beliefs, tended to attribute studies with liberal findings to the liberalism of the researcher, but citizens were less likely to attribute conservative findings to the conservatism of the researcher. [source]

Should Investors Avoid All Actively Managed Mutual Funds?

THE JOURNAL OF FINANCE, Issue 1 2001
A Study in Bayesian Performance Evaluation
This paper analyzes mutual-fund performance from an investor's perspective. We study the portfolio-choice problem for a mean-variance investor choosing among a risk-free asset, index funds, and actively managed mutual funds. To solve this problem, we employ a Bayesian method of performance evaluation; a key innovation in our approach is the development of a flexible set of prior beliefs about managerial skill. We then apply our methodology to a sample of 1,437 mutual funds. We find that some extremely skeptical prior beliefs nevertheless lead to economically significant allocations to active managers. [source]