Three-level main-effects designs exploiting prior information about model uncertainty

To explore the projection efficiency of a design, Tsai, et al [2000. Projective three-level main effects designs robust to model uncertainty. Biometrika 87, 467–475] introduced the Q criterion to compare three-level main-effects designs for quantitative factors that allow the consideration of interactions in addition to main effects. In this paper, we extend their method and focus on the case in which experimenters have some prior knowledge, in advance of running the experiment, about the probabilities of effects being non-negligible. A criterion which incorporates experimenters’ prior beliefs about the importance of each effect is introduced to compare orthogonal, or nearly orthogonal, main effects designs with robustness to interactions as a secondary consideration. We show that this criterion, exploiting prior information about model uncertainty, can lead to more appropriate designs reflecting experimenters’ prior beliefs.     

A Diversity Index for Model Space Selection in the Estimation of Benchmark and Infectious Doses via Model Averaging

In chemical and microbial risk assessments, risk assessors fit dose‐response models to high‐dose data and extrapolate downward to risk levels in the range of 1–10%. Although multiple dose‐response models may be able to fit the data adequately in the experimental range, the estimated effective dose (ED) corresponding to an extremely small risk can be substantially different from model to model. In this respect, model averaging (MA) provides more robustness than a single dose‐response model in the point and interval estimation of an ED. In MA, accounting for both data uncertainty and model uncertainty is crucial, but addressing model uncertainty is not achieved simply by increasing the number of models in a model space. A plausible set of models for MA can be characterized by goodness of fit and diversity surrounding the truth. We propose a diversity index (DI) to balance between these two characteristics in model space selection. It addresses a collective property of a model space rather than individual performance of each model. Tuning parameters in the DI control the size of the model space for MA.     

Temporal Disaggregation: Methods,Information Loss,and Diagnostics

This research provides a generalized framework to disaggregate lower-frequency time series and evaluate the disaggregation performance. The proposed framework combines two models in separate stages: a linear regression model to exploit related independent variables in the first stage and a state–space model to disaggregate the residual from the regression in the second stage. For the purpose of providing a set of practical criteria for assessing the disaggregation performance, we measure the information loss that occurs during temporal aggregation while examining what effects take place when aggregating data. To validate the proposed framework, we implement Monte Carlo simulations and provide two empirical studies. Supplementary materials for this article are available online.     

Response Order Effects in Dichotomous Categorical Questions Presented Orally: The Impact of Question and Respondent Attributes

Using data from 548 experiments in telephone surveys conductedby the Gallup Organization, we explored how attributes of questionsand respondents moderate response order effects in dichotomouscategorical questions. These effects were predominantly recencyeffects and occurred most in questions that were more difficultto comprehend (especially among respondents with the least education),with response choices that were more difficult to comprehend(because they were complete sentences instead of words or phrasesand because they were not mutually exclusive), and that wereasked after many prior questions. Recency effects were alsomore common in questions that explicitly or implicitly encouragedrespondents to wait until they had heard all the answer choicesbefore formulating a judgment than in questions that inducedrespondents to begin formulating a judgment before all the answerchoices had been read (especially among the least educated respondents).A study of interviewer behavior revealed patterns of pausingbetween and within sentences that help to explain why some typesof questions are especially prone to recency effects and othersare not.     

The Collegiate Learning Assessment: facts and fantasies

The Collegiate Learning Assessment (CLA) is a computer administered, open-ended (as opposed to multiple-choice) test of analytic reasoning, critical thinking, problem solving, and written communication skills. Because the CLA has been endorsed by several national higher education commissions, it has come under intense scrutiny by faculty members, college administrators, testing experts, legislators, and others. This article describes the CLA's measures and what they do and do not assess, how dependably they measure what they claim to measure, and how CLA scores differ from those on other direct and indirect measures of college student learning. For instance, analyses are conducted at the school rather than the student level and results are adjusted for input to assess whether the progress students are making at their school is better or worse than what would be expected given the progress of "similarly situated" students (in terms of incoming ability) at other colleges.     

The Effects of Personality Type on Choices Made in Strategic Decision Situations*

Jung's personality-theory typology is used as a framework for exploring the effects of cognitive style on the type and radicalness of choices made in strategic decision situations. Extending the work of Haley and Stumpf [23], it is proposed that individuals with different personality-type preferences exhibit cognitive styles that are associated with specific biases in the pattern of choices they make. Through participation in an interactive behavioral simulation, 407 participants confronted over one hundred ill-structured decision situations and proposed whatever actions they perceived appropriate. The results support the hypothesized relationships that individuals with different personality-type preferences (i.e., sensing-thinking, intuition-thinking, sensing-feeling, and intuition-feeling) take patterns of actions that reflect specific biases (i.e., selective perception, positivity, social desirability, and reasoning-by-analogy, respectively). The implications of these findings for evaluating the likely effectiveness of strategic decisions and making senior-level staffing decisions are discussed.     

Happiness is not Enough: Cognitive Judgements as Indicators of National Wellbeing

The European Social Survey, on which this issue of the journal focuses, is a 30-nation multi-funded survey series measuring attitude change. Started in 2001, it is characterised by unusually high standards of sampling and data equivalence. Its data are made available on-line with equal access to all, and have already attracted over 20,000 users. Many papers, articles and books based on the ESS have already appeared. But none has yet employed the data—whether alone or with other sources—to derive indicators of citizens’ cognitive judgements of their society. A recent EC grant is enabling the authors to fill this gap, covering topics such as trust in national institutions, tolerance, social cohesion, social trust and fear of crime. The aim is to be able to monitor changes over time in the distance between what citizens believe their society ought to be in these respects and how they actually perceive it to be.

An Empirical Examination of Characteristics of Mexican Migrants to Metropolitan and Nonmetropolitan Areas of the United States*

Abstract This research examines differences between those Mexican migrants choosing metropolitan destinations and those choosing destinations outside metropolitan areas of the United States. Using general estimating equations, the study presents data indicating that since the 1960s migrants choosing rural destinations are less fluent in English, slightly older, much less educated, far more likely to be unskilled, more likely to be married, and more likely to be undocumented. The picture is more complex when consideration is restricted to those migrants arriving in rural areas since the passage of the North American Free Trade Agreement. These migrants are far more likely to be single, have more education but have less English fluency, have less work experience, and have less family experience with migration to the United States. They are more likely to come from small towns and rural areas of Mexico.