A parameter analysis method for the weight‐set to satisfy preference orders of alternatives in additive multi‐criteria value models

In the context of the additive multi‐criteria value model, this paper investigates how the set of criteria weights (weight‐set hereafter) can be determined according to the preference orders of alternatives given by the decision maker. A construction method is proposed for the weight‐set for different intervals of β, where β is a differential amount of value between the preference information on two alternatives. The results of this paper are important for sensitivity analysis in multi‐criteria decision making (MCDM) problems and multi‐criteria group decision analysis. Copyright © 2000 John Wiley & Sons, Ltd.     

Topographies and functions of emerging problem behavior and appropriate requests in neurotypical preschoolers

The current study builds on a small but growing body of research evaluating the formal and functional characteristics of emerging problem behavior before it becomes harmful and requires costly treatment. The researchers tested 21 preschool children's sensitivity to establishing operations that commonly precede severe problem behavior. Sensitivity tests were embedded in a small group play context to optimize safety, efficiency, and ecological validity. The tests screened several levels of problem-behavior severity as well as the presence of adaptive alternatives (i.e., communication) to problem behavior. Overall, outcomes suggested sources of reinforcement for minor- and moderate-severity problem behavior in 86% of children. Only 17% of children exhibiting problem behavior also engaged in appropriate requests in the same condition(s) as problem behavior. The present data are compared to published functional analyses of severe behavior. The results are discussed as a preliminary step towards a function-based model of risk identification and behavioral prevention of severe problem behavior.     

Clustering, seriation, and subset extraction of confusion data

The study of confusion data is a well established practice in psychology. Although many types of analytical approaches for confusion data are available, among the most common methods are the extraction of 1 or more subsets of stimuli, the partitioning of the complete stimulus set into distinct groups, and the ordering of the stimulus set. Although standard commercial software packages can sometimes facilitate these types of analyses, they are not guaranteed to produce optimal solutions. The authors present a MATLAB *.m file for preprocessing confusion matrices, which includes fitting of the similarity-choice model. Two additional MATLAB programs are available for optimally clustering stimuli on the basis of confusion data. The authors also developed programs for optimally ordering stimuli and extracting subsets of stimuli using information from confusion matrices. Together, these programs provide several pragmatic alternatives for the applied researcher when analyzing confusion data. Although the programs are described within the context of confusion data, they are also amenable to other types of proximity data.     

Strict and random alternation in concurrent variable-interval schedules

Six pigeons responded on pairs of concurrent variable-interval schedules with, in different parts, four different arrangements of alternation between schedules. Following a single switching-key response, alternation was either strict or random, and the alternative presented after a switch (the postswitch alternative) was either signaled by the location of the switching key or unsignaled. Generalized-matching analyses showed little difference in behavior among the different alternation arrangements, except the usual finding of lower sensitivity of response allocation than time allocation was eliminated by arranging random alternation. Patterns of interchangeover times were similar for all arrangements except signaled random alternation. Differences in behavior preceding the different postswitch alternatives were found in the signaled random alternation procedure. Preference was biased towards the color of the signaled postswitch alternative and showed increased sensitivity when the postswitch alternative was to be the one with the higher reinforcer rate. Interchangeover times were substantially shorter when the postswitch alternative was signaled to be different from the current alternative than when it was signaled to be the same. However, when separate reinforcer ratios were calculated for the different postswitch alternatives, those effects were eliminated or greatly reduced. We suggest that, although behavior is indeed influenced by the postswitch alternative, the mechanism is indirect. That is, the distributions of reinforcers between alternatives obtained before each postswitch alternative differ when those alternatives are signaled, and those distributions are discriminated, but the same relations between choice and relative reinforcement hold irrespective of which postswitch alternative is signaled.     

An evaluation of multi‐criteria methods in integrated assessment of climate policy

Those who conduct integrated assessments (IAs) are aware of the need to explicitly consider multiple criteria and uncertainties when evaluating policies for preventing global warming. MCDM methods are potentially useful for understanding tradeoffs and evaluating risks associated with climate policy alternatives. A difficulty facing potential MCDM users is the wide range of different techniques that have been proposed, each with distinct advantages. Methods differ in terms of validity, ease of use, and appropriateness to the problem. Alternative methods also can yield strikingly different rankings of alternatives. A workshop was held in which climate change experts and policy makers evaluated the usefulness of MCDM for IA. Participants applied several methods in the context of a hypothetical greenhouse gas policy decision. Methods compared include value and utility functions, goal programming, ELECTRE, fuzzy sets, stochastic dominance, min max regret, and several weight selection methods. Ranges, rather than point estimates, were provided for some questions to incorporate imprecision regarding weights. Additionally, several visualization methods for both deterministic and uncertain cases were used and evaluated. Analysis of method results and participant feedback through questionnaires and discussion provide the basis for conclusions regarding the use of MCDM methods for climate change policy and IA analyses. Hypotheses are examined concerning predictive and convergent validity of methods, existence of splitting bias among experts, perceived ability of methods to aid decision‐making, and whether expressing imprecision can change ranking results. Because participants gained from viewing a problem from several perspectives and results from different methods often significantly differed, it appears worthwhile to apply several MCDM methods to increase user confidence and insight. The participants themselves recommended such multimethod approaches for policymaking. Yet they preferred the freedom of unaided decision‐making most of all, challenging the MCDM community to create transparent methods that permit maximum user control. Copyright © 2002 John Wiley & Sons, Ltd.     

Travel time and concurrent-schedule choice: retrospective versus prospective control

Six pigeons were trained on concurrent variable-interval schedules in which two different travel times between alternatives, 4.5 and 0.5 s, were randomly arranged. In Part 1, the next travel time was signaled while the subjects were responding on each alternative. Generalized matching analyses of performance in the presence of the two travel-time signals showed significantly higher response and time sensitivity when the longer travel time was signaled compared to when the shorter time was signaled. When the data were analyzed as a function of the previous travel time, there were no differences in sensitivity. Dwell times on the alternatives were consistently longer in the presence of the stimulus that signaled the longer travel time than they were in the presence of the stimulus that signaled the shorter travel time. These results are in accord with a recent quantitative account of the effects of travel time. In Part 2, no signals indicating the next travel time were given. When these data were analyzed as a function of the previous travel time, time-allocation sensitivity after the 4.5-s travel time was significantly greater than that after the 0.5-s travel time, but no such difference was found for response allocation. Dwell times were also longer when the previous travel time had been longer.     

Subjective norms and the prediction of romantic relationship state and fate

This study examined whether subjective norms are associated with commitment to a romantic relationship and with remaining in that relationship over time. Subjective norms are defined in the context of relationships as the perceived normative beliefs of a social network member regarding a given relationship weighted by the motivation to comply with that network member. In a longitudinal study of college students involved in dating relationships, subjective norms were found to be a significant predictor of romantic relationship commitment level, alone and in multiple regression analyses including satisfaction level, quality of alternatives, and investment size. Longitudinal analyses indicated that commitment mediated the effect of subjective norms on remaining in the relationship approximately 8 months later. Finally, level of dependence on a romantic relationship moderated the predictive value of subjective norms, with lower relationship dependence yielding greatest predictive value for subjective norms.     

Stochastic interactive processes and the effect of context on perception

The effects of context on perceptual identification responses given without time pressure are well-described by classical models in which contextual and stimulus information exert independent effects. A recent article by Massaro (1989) raises the possibility that interactive models, such as the TRACE model of speech perception, are inherently incompatible with these classical context effects. The present article shows that this incompatibility hypothesis can be rejected. Mathematical analysis and computer simulation methods are used to show that interactive models can exhibit the classical effects of context, if there is variability in the input to the network or if there is intrinsic variability in the network itself. A variety of interactive models which incorporate variability can all produce the classical context effects, at least under some conditions; the conditions are rather general in the case of one of the variants. The findings suggest that interactive models should not be viewed as alternatives to classical accounts, but as hypotheses about the dynamics of information processing that lead to the global asymptotic behavior that the classical models describe.     

Modeling competence development in the presence of selection bias

A major challenge for representative longitudinal studies is panel attrition, because some respondents refuse to continue participating across all measurement waves. Depending on the nature of this selection process, statistical inferences based on the observed sample can be biased. Therefore, statistical analyses need to consider a missing-data mechanism. Because each missing-data model hinges on frequently untestable assumptions, sensitivity analyses are indispensable to gauging the robustness of statistical inferences. This article highlights contemporary approaches for applied researchers to acknowledge missing data in longitudinal, multilevel modeling and shows how sensitivity analyses can guide their interpretation. Using a representative sample of N = 13,417 German students, the development of mathematical competence across three years was examined by contrasting seven missing-data models, including listwise deletion, full-information maximum likelihood estimation, inverse probability weighting, multiple imputation, selection models, and pattern mixture models. These analyses identified strong selection effects related to various individual and context factors. Comparative analyses revealed that inverse probability weighting performed rather poorly in growth curve modeling. Moreover, school-specific effects should be acknowledged in missing-data models for educational data. Finally, we demonstrated how sensitivity analyses can be used to gauge the robustness of the identified effects.     

Trying Hard or Hardly Trying: An Analysis of Context Effects in Choice

Several studies have shown that consumer choice is often influenced by the context or the set of alternatives under consideration. Context effects have largely been explained in terms of constructive preferences that are consistent with 2 theoretical accounts—effort minimization and perceptual contrast—that emphasize different underlying motivations. We propose that the effect of time pressure on context effects can be used as a moderating variable to determine which of the 2 motives is supported. Specifically, if context effects bias preferences due to effort minimization, time pressure should increase the magnitude of such effects. In contrast, if context effects arise due to an excessive focus on the relational characteristics of the alternatives provided, time pressure should reduce the magnitude of such effects. We examine this proposition in relation to the compromise effect and a choice between an extreme and an all‐average option. We find that the compromise effect and the preference for an all‐average alternative are both reduced under time pressure. A study using Mouselab provides additional support for the underlying decision mechanisms. We discuss the theoretical implications of this research and explore its consequences for marketers.     

Alternatives to a table of criterion values in signal detection theory

Gardner, Dalsing, Reyes, and Brake (1984) supplied a table of criterion values (β) related to hit and false-alarm rates in signal detection theory. Other methods of calculatingβ are suggested as more accurate alternatives to using that table. A short computer program is provided to calculate β and the sensitivity indexd’.     

A Comparison of Population-Averaged and Cluster-Specific Approaches in the Context of Unequal Probabilities of Selection

Sampling designs of large-scale survey studies are typically complex, involving multiple design features such as clustering and unequal probabilities of selection. Single-level (i.e., population-averaged) methods that use adjusted variance estimators and multilevel (i.e., cluster-specific) methods provide two alternatives for modeling clustered data. Although the literature comparing these methods is vast, comparisons have been limited to the context in which all sampling units are selected with equal probabilities (thus circumventing the need for sampling weights). The goal of this study was to determine under what conditions single-level and multilevel estimators outperform one another in the context of a two-stage sampling design with unequal probabilities of selection. Monte Carlo simulation methods were used to evaluate the impact of several factors, including population model, informativeness of the design, distribution of the outcome variable, intraclass correlation coefficient, cluster size, and estimation method. Results indicated that the unweighted estimators performed similarly across conditions, whereas the weighted single-level estimators tended to outperform the weighted multilevel estimators, particularly under nonideal sample conditions. Multilevel weight approximation methods did not perform well when the design was informative. An empirical example is provided to demonstrate how researchers might investigate the implications of the simulation results in practice.     

The Mating Sociometer and Attractive Others: A Double-Edged Sword in Romantic Relationships

Eighty-one participants were recruited to test the sensitivity of the mating sociometer to mate-value feedback in the context of ongoing intimate relationships. Experiences of social rejection/acceptance by attractive opposite-sex confederates were manipulated. The effects of this manipulation on self-esteem, relationship satisfaction and commitment, perceptions of dating alternatives, and friendship-dedication were assessed. Social rejection/acceptance by members of the opposite sex altered relationship satisfaction and commitment; this causal link was amplified by changes in state self-esteem; and these effects were specific to intimate relationships and did not generalize to friendship-dedication. This research supports a domain-specific conceptualization of sociometer theory, extending the theory in important directions.     

Divorce Therapy in Context

Abstract

Partners trying to decide whether to continue or end their marriage rely on the expertise of therapists to help them evaluate their alternatives. Research on what predicts divorce and what consequences divorce has for parents and children is reviewed so therapists are informed in the guidance they give clients. Attention is given to the environmental context of marriage as well as its interior quality. Implications for therapists doing divorce therapy in the context of a “pro-marriage” climate are also discussed.     

The word superiority effect: A comparison between restricted and unrestricted alternative set

Three experiments were conducted to investigate the word superiority effect (WSE) (Reicher, 1969). The first two experiments used mixed presentations of words and nonwords, and positional uncertainty of the critical letter. Experiment 1 used an unrestricted set of alternatives, while Experiment 2 used only two alternatives (R and L). Experiment 3 compared letter detection in nonwords with a restricted and unrestricted alternative set. WSE was found for both Experiments 1 and 2, at about the same level. Experiment 3 showed superior performance when alternatives were known in advance. It was concluded that context has an effect on letter recognition even with prior knowledge of alternatives if the critical position is not known in advance. Some incompatibilities between the present results and those of other investigators in the field are discussed.     

From the interpersonal to the international: understanding commitment to the "war on terror"

Applying constructs from the investment model used traditionally to understand interpersonal commitment, the present investigation seeks to elucidate social cognitive antecedents of commitment to the war on terror waged by the United States. In Study 1, satisfaction with, investments in, and alternatives to the war on terror predict levels of commitment to the war beyond several important control variables. In Study 2, levels of satisfaction with, investments in, and alternatives to the war are experimentally manipulated. The highest levels of commitment to the war are observed among participants exposed to a high satisfaction, high investment, and low alternatives scenario, and the lowest levels are among those exposed to a low satisfaction, low investment, and high alternatives scenario. These results support broadening the targets of commitment normally considered within the context of the investment model and suggest applying relational models to understanding broader societal concerns.     

Rethinking the focusing effect in decision-making

According to Legrenzi et al. [Cognition 49 (1993) 37], in making a choice people consider only the alternatives explicitly represented in their mental model of the decision situation. Their idea has found empirical support in the "focusing effect": Individuals focus on the alternatives explicitly stated in the problem context, and do not take into account other possibilities. In their original study, Legrenzi and colleagues considered only one factor to account for the explicit representation of an alternative--i.e., its explicit verbal formulation in the decision problem. Recent theories of relevance and information gain can help articulate their original idea, suggesting that individuals explicitly represent relevant alternatives, whether or not they are explicitly formulated in the decision problem. In three experiments we first replicated Legrenzi et al.'s original experiment, and then showed that the explicit verbal mention of an alternative is neither sufficient nor necessary to focus on it. The results suggest that individuals are able to consider relevant alternatives, even when they are not made explicit in the verbal formulation of a decision problem.     

Relative reinforcer rates and magnitudes do not control concurrent choice independently

One assumption of the matching approach to choice is that different independent variables control choice independently of each other. We tested this assumption for reinforcer rate and magnitude in an extensive parametric experiment. Five pigeons responded for food reinforcement on switching-key concurrent variable-interval variable-interval schedules. Across conditions, the ratios of reinforcer rates and of reinforcer magnitudes on the two alternatives were both manipulated. Control by each independent variable, as measured by generalized-matching sensitivity, changed significantly with the ratio of the other independent variable. Analyses taking the model-comparison approach, which weighs improvement in goodness-of-fit against increasing number of free parameters, were inconclusive. These analyses compared a model assuming constant sensitivity to magnitude across all reinforcer-rate ratios with two alternative models. One of those alternatives allowed sensitivity to magnitude to vary freely across reinforcer-rate ratios, and was less efficient than the common-sensitivity model for all pigeons, according to the Schwarz-Bayes information criterion. The second alternative model constrained sensitivity to magnitude to be equal for pairs of reinforcer-rate ratios that deviated from unity by proportionately equal amounts but in opposite directions. This model was more efficient than the common-magnitude-sensitivity model for 2 of the pigeons, but not for the other 3. An analysis of variance, carried out independently of the generalized-matching analysis, also showed a significant interaction between the effects of reinforcer rate and reinforcer magnitude on choice. On balance, these results suggest that the assumption of independence inherent in the matching approach cannot be maintained. Relative reinforcer rates and magnitudes do not control choice independently.