A nonlinear regression approach to estimating signal detection models for rating data

This paper considers a regression approach to estimating signal detection parameters for rating data. The methodology is based on the statistical modeling of ordinal data and requires only standard statistical software such as SAS (SAS/STAT User’s Guide, 1999) for computation. The approach is more efficient than the current practice of extracting the parameter estimates with the use of specialized software and analyzing the estimates with the use of a standard statisticalpackage. It greatly facilitate s exploration of the effects of covariates on model parameters. The method is illustrated using a published data set from a single factor multiple-alternative perceptual task, and data from a more complex factorial design examining recognition memory rating data.     

Causal inferences as perceptual judgments

We analyze how subjects make causal judgments based on contingency information in two paradigms. In the discrete paradigm, subjects are given specific information about the frequency a, with which a purported cause occurs with the effect; the frequency b, with which it occurs without the effect; the frequency c, with which the effect occurs when the cause is absent; and the frequency d, with which both cause and effect are absent. Subjects respond toP ₁ =a/(a+b) andP ₂ =c/(c+d). Some subjects’ ratings are just a function ofP ₁, while others are a function of ΔP =P ₁ -P ₂. Subjects’ postexperiment reports are accurate reflections of which model they use. Combining these two types of subjects results in data well fit by the weighted ΔP model (Allan, 1993). In the continuous paradigm, subjects control the purported causes (by clicking a mouse) and observe whether an effect occurs. Because causes and effects occur continuously in time, it is not possible to explicitly pair causes and effects. Rather, subjects report that they are responding to the rate at which the effects occur when they click versus when they do not click. Their ratings are a function of rates and not probabilities. In general, we argue that subjects’ causal ratings are judgments of the magnitude of perceptually salient variables in the experiment.     

Using java in introductory statistics

In this paper, we discuss the use of Java, a programming language for the Internet, in introductory statistics courses. Monte Carlo estimation and simple linear regression are used as tutorial examples of the versatility of Java. Advantages over traditional instructional methods and other programming languages are examined.     

A note on dual scaling of successive categories data

Three methods for dual scaling of successive categories data are formulated. They are mathematically equivalent, and provide an appropriate technique to determine stimulus values and category boundaries on a joint scale, a problem that Nishisato's method (1980a) failed to handle. This study was supported by the Natural Sciences and Engineering Research Council of Canada (Grant No. A7942) to S. Nishisato. Comments on the earlier draft from anonymous reviewers were most helpful and much appreciated.     

Meta-analysis using linear mixed models

Psychologists often use special computer programs to perform meta-analysis. Until recently, this had been necessary because standard statistical packages did not provide procedures for such analysis. This paper introduces linear mixed models as a framework for meta-analysis in psychological research, using a popular general purpose statisticalpackage, SAS. The approach is illustrated with three examples, usingsas peoc mixed.     

A model of users' satisfaction with Taiwan's Government website

Taiwan's Government web portal has been the sole communication link between citizens and E-Government since being launched in 2002 to provide citizens with government-related information promptly via effective classification. The assessment of the service quality and citizens' satisfaction with E-Government has rarely been explored. The present study explored how the service quality of E-Government subsequently affects the users' psychological and behavioral responses. A structural model was proposed that contained four constructs: service quality, service value, users' satisfaction, and behavioral intention as well as their interrelations. A survey was used to collect users' ratings. Structural equation modeling was applied to verify the factor analysis of the obtained data and fit of a model. Analyses indicated adequate fit of model as follows: E-Government service quality --> service value --> users' satisfaction --> behavioral intention.     

Testing the choice model of social cognitive career theory across Holland themes: A meta-analytic path analysis

Social cognitive career theory (SCCT; Lent, Brown, & Hackett, 1994) seeks to explain the factors that shape educational and vocational interests and choices. We used meta-analytic path analyses to synthesize data (from 1981 to 2008) relevant to SCCT’s interest and choice hypotheses, organizing the literature according to Holland’s (1997) broad occupational themes. Sufficient data were available to test (a) a 6-variable version of the interest/choice model in the Realistic, Investigative, and Enterprising themes, and (b) a 4-variable version of the model in the Artistic, Social, and Conventional themes. Analyses of both model versions were generally consistent with theoretical expectations. However, tests of the 6-variable model indicated better support for representing the pathways from contextual variables to choice goals as being partially mediated by self-efficacy and outcome expectations rather than as producing only direct linkages to goals. We consider implications of the findings for theory, research, and SCCT-based interventions.     

Longitudinal test of the social cognitive model of choice in engineering students at historically Black universities

We tested the social cognitive model of choice (Lent, Brown, & Hackett, 1994) using a longitudinal design. Participants were 116 students taking beginning engineering courses at two historically Black universities. They completed measures of self-efficacy, outcome expectations, interests, goals, and environmental supports and barriers near the end of two consecutive semesters. Path analyses indicated overall support for the choice model and, in particular, suggested that self-efficacy served as a temporal precursor of outcome expectations, interests, goals, and supports. Interests and self-efficacy were found to be reciprocally related but, contrary to expectations, supports and barriers did not account for unique variance in self-efficacy. Implications for future research on the choice model are discussed.     

Longitudinal relations of self-efficacy to outcome expectations, interests, and major choice goals in engineering students

We examined the nature of the temporal relations among the core person variables in the social cognitive model of academic and career choice [Lent, R. W., Brown, S. D., & Hackett, G. (1994). Toward a unifying social cognitive theory of career and academic interest, choice, and performance [Monograph]. Journal of Vocational Behavior, 45, 79-122.]. Participants were 209 students taking beginning level engineering courses at either a predominantly White or a historically Black university. They completed measures of self-efficacy, outcome expectations, interests, and goals near the end of two consecutive semesters. Path analyses indicated support for a model in which self-efficacy served as a temporal precursor of outcome expectations, interests, and goals. There was less support for a model in which the latter variables produced reciprocal paths to self-efficacy. Implications for future longitudinal research on SCCT’s (social cognitive career theory’s) choice hypotheses are discussed.     

The impacts of an air-crash on students’ transportation choice behaviour: An empirical study undertaken in Taiwan

This research’s objectives are to identify major factors influencing offshore student–commuters’ transportation mode-choice and to develop simple Logit choice models prior and post a major air disaster. The total trip time, trip cost, ease of access to a transportation mode, student–commuters’ household income, and the risk perceived by student–commuters using different transportation modes are found to have impacts on their mode-choice behaviour. Several logit model specifications were tested. The research reveals student–commuters’ transportation mode-choice behaviour significantly changed post the May 2002 Penghu air accident. Reduction in airfares (which most airlines used to promote their services after the air-crash) was less attractive to passengers than convincing them that airline services were safe. Therefore, any post-disaster airline marketing campaign aimed at student–commuters should change from reduced fare promotion to service safety promotion.