The decision to check in multialternative choices and limited sensitivity to default

Given the rapid proliferation of smartphone applications and data aggregation websites, in many situations people can use decision aids to guide their choices. For example, they may consider whether to use a navigation device to check the fastest route or whether to use a price comparison website to find the cheapest deal. In what circumstances will subjects use a costly comparison decision aid (which I refer to as “checking”) to choose for them? In six studies, I investigate the impact of the number of available alternatives and checking's attractiveness on the decision to check. While at first increasing the attractiveness of checking led to higher checking rates, a further increase in the number of available alternatives (and thus checking's attractiveness) did not increase the checking rate. Surprisingly, even when checking had a 40% higher expected value compared with not checking, the observed checking rate was below 45%, contrary to risk and ambiguity aversion predictions. Furthermore, labeling the checking alternative as the default had no impact on its choice rate. I find large individual differences in decisions to check. Surprisingly, subjects' initial decisions had high predictive power over their subsequent checking rates, even after 100 trials with full feedback. I propose two simple learning models that capture well the aggregated results.     

A general model for the analysis of multilevel data

A general model is developed for the analysis of multivariate multilevel data structures. Special cases of the model include repeated measures designs, multiple matrix samples, multilevel latent variable models, multiple time series, and variance and covariance component models.We would like to acknowledge the helpful comments of Ruth Silver. We also wish to thank the referees for helping to clarify the paper. This work was partly carried out with research funds provided by the Economic and Social Research Council (U.K.).     

Three-term contingency patterns in mother-child verbal interactions during first-language acquisition

Selections from a large longitudinal data set of verbal interactions between a mother and her child are presented. Two sets of three-term contingency sequences that seemed to reflect maternal rewards and corrections were noted. Both the antecedents as well as the immediate consequences of maternal interventions are presented to explore training and learning processes. The observed frequencies of three-step sequences are compared to those expected based upon Markov-chain logic to substantiate the patterning of the interactions. Behavioral conceptualizations of the learning process are supported by these analyses, although their sufficiency is questioned. It is suggested that maternal rewards and corrections should be integrated with perceptual, cognitive, and social learning conceptualizations in a skill-learning approach to explain the complexity of language transmission and acquisition processes.     

Peer review: Selecting the best science

The major challenge facing today’s biomedical researchers is the increasing competition for available funds. The competitive review process, through which the National Institutes of Health (NIH) awards grants, is built upon review by a committee of expert scientists. The NIH is firmly committed to ensuring that its peer review system is fair and objective. Wendy Baldwin, Ph.D., is Deputy Director for Extramural Research, National Institutes of Health. This paper is based on a presentation at a workshop, “Advances in Peer Review Research”, American Association for the Advancement of Science Meeting, Baltimore, MD, February 9, 1996.     

A marginalization model for the multidimensional unfolding analysis of ranking data

A marginalization model for the multidimensional unfolding analysis of ranking data is presented. A subject samples one of a number of random points that are multivariate normally distributed. The subject perceives the distances from the point to all the stimulus points fixed in the same multidimensional space. The distances are error perturbed in this perception process. He/she produces a ranking dependent on these error-perturbed distances. The marginal probability of a ranking is obtained according to this ranking model and by integrating out the subject (ideal point) parameters, assuming the above distribution. One advantage of the model is that the individual differences are captured using the posterior probabilities of subject points. Three sets of ranking data are analyzed by the model.     

Psychological determinants of decision attitude

Decision attitude — an analog of risk attitude — is the propensity to make (or avoid making) a decision: in decision aversion, a person finds it more desirable to receive through fiat the better of two options than to have a choice between them; in decision seeking, the choice is more desirable, even though it can lead to nothing better than the best option. Both decision aversion and decision seeking were found in hypothetical scenarios. Experimental manipulations and subjects' justifications point to anticipated regret, fear of blame for poor outcomes, and desire for equitable distributions as sources of decision aversion. One source of decision seeking (for self) and decision aversion (when deciding for others) appears to be the desire for the self-determination of the affected parties. We consider the implications of our results for personal choice and public policy decisions.     

A compensatory approach to optimal selection with mastery scores

A Bayesian approach for simultaneous optimization of test-based decisions is presented using the example of a selection decision for a treatment followed by a mastery decision. A distinction is made between weak and strong rules where, as opposed to strong rules, weak rules use prior test scores as collateral data. Conditions for monotonicity of optimal weak and strong rules are presented. It is shown that under mild conditions on the test score distributions and utility functions, weak rules are always compensatory by nature. The authors are indebted to Wilbert Kallenberg for his valuable comments and to Jan Gulmans for providing the data for the empirical example. The names of the authors are alphabetical; they are equally responsible for the contents of this paper.     

On various causes of improper solutions in maximum likelihood factor analysis

In the applications of maximum likelihood factor analysis the occurrence of boundary minima instead of proper minima is no exception at all. In the past the causes of such improper solutions could not be detected. This was impossible because the matrices containing the parameters of the factor analysis model were kept positive definite. By dropping these constraints, it becomes possible to distinguish between the different causes of improper solutions. In this paper some of the most important causes are discussed and illustrated by means of artificial and empirical data.The author is indebted to H. J. Prins for stimulating and encouraging discussions.     

MULTIVARIATE ASSESSMENT OF CONFLICT IN DISTRESSED AND NONDISTRESSED MOTHER-ADOLESCENT DYADS

A battery of measures was used to assess conflict between mothers and young adolescents (females and males, 11 to 15 years of age). Two groups of families, one composed of a distressed clinical sample (N = 38), the other a nondistressed normative sample (N = 40), participated. The assessment battery included retrospective judgments, frequency estimates, self-monitored home recording, and tape-recorded discussion of a home problem. Content of assessment measures tapped aspects of parental control, decisionmaking, self-reported interaction behavior, arguments, interaction behavior rated by independent “blind” observers, frequency and anger-intensity of specific problematic issues, and perceptions of positive and negative behaviors of the other family member. Based on univariate analyses, 21 of the 26 defined variables discriminated significantly in the predicted direction. Maternal and adolescent reports of behavior and independent ratings of tape-recorded interaction emerged as strong and consistent discriminators. Stepwise multivariate discriminant analysis provided successful classification of 100% of the families based on the inclusion of nine variables. In a cross-validation sample, 84% of the families were correctly classified. Implications for systematic outcome research as well as clinical application are discussed.