Suchergebnisse

Czechoslovak PO poll results for the period Jan 1968-Mar 1969 are summarized. The original polls were conducted by the Czechoslovak Instit of PO & released to the press. Topics covered include econ trends, perspectives on nat'l history, evaluation of nat'l leaders, att's toward foreign countries & world events, the movement of Soviet troops into Czechoslovakia, student protests, censorship, rehabilitation of prisoners, reforms & the role of the Communist Party. Reforming tendencies got massive support & the policies of the 1950's typically were endorsed by 2-3% on most questions. AA.

Voter expectations concerning the electoral prospects of parties & candidates (viability & electability) play an important role in modern theories of voting behavior, especially if more than two choices are involved. Research on public opinion polls as source of these expectations has been hampered by circumstantial & methodological difficulties. The research reported here satisfied the necessary condition & presents (on the basis of a survey among 1,393 respondents & with the use of multiple logistic regression analysis) strong evidence that the polls were the dominant source of expectations for voters in the 1994 Dutch parliamentary election. 4 Tables, 1 Appendix, 29 References. Adapted from the source document.

We retrospectively explore the effectiveness of various probabilistic opinion pools against a set of insider threat detection modeling data from a recently completed, multiyear, sponsored research effort. We explored four opinion pools: the linear opinion pool (likely the most popular), the beta-transformed linear opinion pool, the geometric opinion pool, and a multiplicative method based on odds called Bordley's formula. The data for our study came from our recent work in the inference of insider threats for our research sponsor. In this work, we created a multimodeling inference enterprise modeling (MIEM) process to either predict threats within a population or, given the threats, predict how well the enterprise system can detect those threats. As part of larger research challenges designed by the research sponsor, we applied the MIEM process quarterly to respond to a sequence of varying challenge problems (CPs). Via MIEM, we developed multiple, independent computation forecast models. These models generated certainty intervals to answer CP questions. These intervals were fused into a single interval for each question via an expert panel prior to submission. The sponsors scored the responses against ground truth. In this paper, we (a) ask which pooling functions work best on these data and consider why, and (b) compare this performance to the actual submissions to determine if one of the pooling functions performed better than our judgment-based fusion.

Linear and log-linear pools are widely used methods for aggregating expert belief. This paper frames the expert aggregation problem as a decision problem with scoring rules. We propose a scoring function that uses the Kullback-Leibler (KL) divergence measure between the aggregate distribution and each of the expert distributions. The asymmetric nature of the KL measure allows for a convenient scoring system for which the linear and log-linear pools provide the optimal assignment. We also propose a "goodness-of-fit" measure that determines how well each opinion pool characterizes its expert distributions, and also determines the performance of each pool under this scoring function. We work through several examples to illustrate the approach.