Age and Gender Differerences In a Social Process Model of Adolescent Cigarette Use*

This study examines how age and gender influence the ability of social process theory to explain adolescent cigarette use. Differences in the causal effects of social process variables for three age periods for male and female adolescents are examined. Longitudinal data from a sample of midwestern adolescents are analyzed using path analyses procedures. Findings from these analyses indicate that social process theory is better able to account for cigarette use among older females than any other age and gender group. For females, commitment to education and school activities were better predictors of cigarette smoking at a later age than an earlier age, whereas the opposite was found for belief in conventional societal rules. For males, previous smoking was the major variable in all three age groups to directly affect subsequent smoking. These findings are discussed in terms of previous age and gender research.     

On the exact calculation of cumulative F probabilities

Various approximate procedures have been employed in the tabulation of F distributions. These approximations generally perform poorly for small degrees of freedom and/or for extreme tail areas.

Closed form expressions are presented in this paper for the exact calculation of cumulative probabilities of F distributions. For small degrees of freedom, the probabilities may be calculated with the aid of standard mathematical tables and a calculator. An APL computer program, also presented in this paper, may be used in calculating the cumulative probabilities according to the exact expressions.     

On Preference for Flexibility and Complexity Aversion: Experimental Evidence1

Desire for flexibility suggests that the value of a choice-menu should increase with the number of options included. Complexity-aversion on the other hand may imply that the value of a menu decreases with its cardinality. We present the results of an experiment where 5 groups of subjects were asked to evaluate saving plans that let the investor choose between alternative indexing-schemes before the saving period ends. The complexity of the different plans was manipulated in two ways: (1) increasing the number of indexing options; (2) reducing the quality of information upon which the choice between different indices is made. We show that an increase in the number of indexing-options produces a negative complexity effect when the quality of information is high. The same change however results in a positive flexibility effect when the quality of information is low. More generally our results suggest a `negative cross interaction of complexity effects' and that the impact of complexity is marginally decreasing. We discuss possible cognitive explanations to the observed evaluation-patterns. This revised version was published online in June 2006 with corrections to the Cover Date.     

A mixed integer programming and heuristic algorithm for a warehouses location problem

A warehouses location problem is treated using a mixed integer programming and a heuristic algorithm. A simplification of freight rates schedules, based upon shipments consolidation and a linear regression of rates vs distances was made. Warehousing costs were divided according to fixed and variable and related to the throughput of the warehouses. Consideration was given in the analysis to the choice between owning and leasing each warehouse. In the case studied, the analysis demonstrated that a possible saving of approximately 22 per cent in annual distribution costs could be realized under the optimized warehouse location network.