ANALYSIS OF INFLUENCE SHARING IN JUDGMENTAL FORECASTING: REGRESSION MODELS AND PERCEPTUAL MEASURE

The committee or group approach is often used where considerable uncertainties have to be handled by skillful judgment. In this paper the authors investigate the subject of influence sharing in judgmental forecasting of commodity prices. They propose a conceptual framework for patterns of influence sharing in groups and for influence roles of individuals. A statistical analysis of the influence of group members on the group forecast leads to inferences about influence pattern and roles in a group.     

Inferring decision strategies from clickstreams in decision support systems: a new process-tracing approach using state machines

Webstores can easily gather large amounts of consumer data, including clicks on single elements of the user interface, navigation patterns, user profile data, and search texts. Such clickstream data are both interesting to merchandisers as well as to researchers in the field of decision-making behavior, because they describe consumer decision-behavior on websites. This paper introduces an approach that infers decision-behavior from clickstream data. The approach observes clicks on elements of a decision-support-system and triggers a set of state-machines for each click. Each state-machine represents a particular decision-strategy which a user can follow. The approach returns a set of decision strategies that best explain the observed click-behavior of a user. Results of two experiments show that the algorithm infers strategies accurately. In the first experiment, the approach correctly infers most of the pre-defined decision-strategies. The second study analyzes the behavior of thirty-eight respondents and finds that the inferred mix of decision-strategies fits well the behavior described in the literature to date. Results show that using decision-support-systems on a web site and observing the user’s click-behavior make it possible to infer a specific decision strategy. The proposed method is general enough to be easily applied to both research and real-world settings, along with other decision-support-systems and strategies.     

Collective Wage Agreements and Firms’ Employment Policies

This paper provides evidence on the way collective wage agreements affect the adjustment of employment, working hours and other production factors when service‐sector firms are faced with demand shocks. The estimation results indicate that collective wage agreements significantly influence firms’ employment policies. It is shown that recruitment is a widespread instrument for service firms to cope with demand fluctuations which are negatively affected by collective wage agreements. The employment of freelance workers is also negatively affected by collective wage agreements, while their effect on using short‐term employment contracts as a reaction to demand shocks is positive.     

On estimands and the analysis of adverse events in the presence of varying follow‐up times within the benefit assessment of therapies

The analysis of adverse events (AEs) is a key component in the assessment of a drug's safety profile. Inappropriate analysis methods may result in misleading conclusions about a therapy's safety and consequently its benefit‐risk ratio. The statistical analysis of AEs is complicated by the fact that the follow‐up times can vary between the patients included in a clinical trial. This paper takes as its focus the analysis of AE data in the presence of varying follow‐up times within the benefit assessment of therapeutic interventions. Instead of approaching this issue directly and solely from an analysis point of view, we first discuss what should be estimated in the context of safety data, leading to the concept of estimands. Although the current discussion on estimands is mainly related to efficacy evaluation, the concept is applicable to safety endpoints as well. Within the framework of estimands, we present statistical methods for analysing AEs with the focus being on the time to the occurrence of the first AE of a specific type. We give recommendations which estimators should be used for the estimands described. Furthermore, we state practical implications of the analysis of AEs in clinical trials and give an overview of examples across different indications. We also provide a review of current practices of health technology assessment (HTA) agencies with respect to the evaluation of safety data. Finally, we describe problems with meta‐analyses of AE data and sketch possible solutions.     

'We Won't Go Back': the ADA on the grass roots level

The Americans with Disabilities Act (ADA) is a civil rights statute protecting people from discrimination based on a disability in both the private and the public sectors. Using interviews with grass roots persons with disabilities across the USA-many of whom are experienced activists-and using other sources this article describes the reaction of the disability community in the United States to the passage of the ADA and its impact. Largely people with disabilities feel empowered by the ADA. However, a strong amount of cynicism is also found at the grass roots level regarding it. A revealing example of the empowerment felt by people with disabilities is the conflict in New York City over a proposal for non-accessible public toilets. Other reactions and developments are discussed including the possibility of the repeal or weakening of the ADA. A fundamental change occurred in the US with the passage of the ADA and the disability community will not allow that change to be undone.     

Three Steps Strategy to Search for Optimum Classification Trees

This article presents a new strategy to construct classification trees. According to the proposed scheme, we focused on keeping the record of sequences of each constructed classification tree; both in terms of splitting predictors and their splitting values in an array. So overall we have as many arrays as we have drawn samples. At this stage, a three steps strategy is introduced, which is used to search for the optimum classification tree. The proposed strategy provides comparable or improved results in terms of generalized error rates than tree and rpart (packages available for classification purposes in the R) using four of the well-known evaluation functions, that is, the Gini, the Entropy, the Twoing, and the Exponent-based function to split nodes for many real-life datasets.     

A combined p-value test for multiple hypothesis testing

Tests that combine p-values, such as Fisher's product test, are popular to test the global null hypothesis H₀ that each of n component null hypotheses, H₁,…,H_n, is true versus the alternative that at least one of H₁,…,H_n is false, since they are more powerful than classical multiple tests such as the Bonferroni test and the Simes tests. Recent modifications of Fisher's product test, popular in the analysis of large scale genetic studies include the truncated product method (TPM) of Zaykin et al. (2002), the rank truncated product (RTP) test of Dudbridge and Koeleman (2003) and more recently, a permutation based test—the adaptive rank truncated product (ARTP) method of Yu et al. (2009). The TPM and RTP methods require users' specification of a truncation point. The ARTP method improves the performance of the RTP method by optimizing selection of the truncation point over a set of pre-specified candidate points. In this paper we extend the ARTP by proposing to use all the possible truncation points {1,…,n} as the candidate truncation points. Furthermore, we derive the theoretical probability distribution of the test statistic under the global null hypothesis H₀. Simulations are conducted to compare the performance of the proposed test with the Bonferroni test, the Simes test, the RTP test, and Fisher's product test. The simulation results show that the proposed test has higher power than the Bonferroni test and the Simes test, as well as the RTP method. It is also significantly more powerful than Fisher's product test when the number of truly false hypotheses is small relative to the total number of hypotheses, and has comparable power to Fisher's product test otherwise.     

Longitudinal Associations of the Attainment of Developmental Tasks With Psychological Symptoms in Adolescence: A Meta‐Analysis

The present meta‐analysis integrates results from 310 longitudinal studies on associations of the attainment of 10 developmental tasks with psychological symptoms (e.g., internalizing or externalizing symptoms, anxiety, and depression). Higher initial success with getting access to a peer group, building friendships, preparing for a future career, body acceptance, as well as developing a personal identity, a value system, and socially responsible behavior predicted lower levels of symptoms at follow‐up and stronger declines of symptoms over time when controlling for initial symptom levels. Furthermore, higher initial symptom levels predicted lower attainment of these tasks at follow‐up as well as lower progress in task attainment. In contrast, more initial romantic/sexual involvement predicted an increase in symptoms over time, while higher initial symptoms were related to an increase in romantic/sexual involvement. Associations with autonomy varied between different forms of autonomy, while acquisition of a gender role was not related with psychological symptoms.     

Ethnic and religious perspectives on disability and the helping professions

This note looks at ethnic and religious perspectives of people who are training for and/or working in the helping professions in regard to their views of disability. The Modified Issues in Disabilities Scale (MIDS) was administered to a sample of people training for and/or working in the helping professions. A statistically significant association was found between ethnic and religious perspectives and scores on the MIDS.