searchers would be advised to consider other packages to supplement Limdep for simplicity of use (e.g., SST for handling discrete data).
This chapter overviews a wide variety of modeling techniques that can be used to handle the types of data likely to be encountered in modeling driver decision making. An overview of these techniques along with references that can be used for obtaining additional information is provided in Table 7.1.
The techniques in this chapter are very powerful tools for analyzing driver decision making. The intent of this chapter is to give the reader a basic understanding of the various modeling approaches along with some of the likely pitfalls that may be encountered. It is important to select the methodology suited to the decision-making process being modeled, and to carefully search for possible model specification errors. The literature in virtually every field is strewn with papers that have adopted the wrong methodological approach or have made serious model specification errors. Before applying any of the techniques discussed herein, it is recommended that the researcher take the time to read some of the many referenced articles under each methodological heading in Table 7.1. Such reading will help clarify any lingering questions concerning the modeling methods.
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