Grounded theory research: Procedures,canons, and evaluative criteria

Using grounded theory as an example, this paper examines three methodological questions that are generally applicable to all qualitative methods. How should the usual scientific canons be reinterpreted for qualitative research? How should researchers report the procedures and canons used in their research? What evaluative criteria should be used in judging the research products? We propose that the criteria should be adapted to fit the procedures of the method. We demonstrate how this can be done for grounded theory and suggest criteria for evaluating studies following this approach. We argue that other qualitative researchers might be similarly specific about their procedures and evaluative criteria.     

Improvement of Highway Safety I: Identification of Causal Factors Through Fault-Tree Modeling1

As the first article of a two-part series, the purpose of this paper is to examine the functional factors that contribute to automobile accident occurrence and to model the causation structure in the form of a fault-tree. The fault-tree model provides an intuitive framework for qualitatively decomposing possible pathways to accident occurrence. Fault-tree analysis also provides a statistical representation of how interacting driver, vehicle, and environmental factors contribute to the likelihood of automobile accident occurrence. The application of this model facilitates pinpointing those factors that most contribute to accident causation and subsequently enables the identification and comparison of potential crash avoidance technologies.     

BAYESIAN HIDDEN MARKOV MODELS FOR LONGITUDINAL COUNTS

This paper describes a Bayesian approach to modelling carcinogenity in animal studies where the data consist of counts of the number of tumours present over time. It compares two autoregressive hidden Markov models. One of them models the transitions between three latent states: an inactive transient state, a multiplying state for increasing counts and a reducing state for decreasing counts. The second model introduces a fourth tied state to describe non‐zero observations that are neither increasing nor decreasing. Both these models can model the length of stay upon entry of a state. A discrete constant hazards waiting time distribution is used to model the time to onset of tumour growth. Our models describe between‐animal‐variability by a single hierarchy of random effects and the within‐animal variation by first‐order serial dependence. They can be extended to higher‐order serial dependence and multi‐level hierarchies. Analysis of data from animal experiments comparing the influence of two genes leads to conclusions that differ from those of Dunson (2000). The observed data likelihood defines an information criterion to assess the predictive properties of the three‐ and four‐state models. The deviance information criterion is appropriately defined for discrete parameters.     

Testing the Martingale Difference Hypothesis

In this paper we consider testing that an economic time series follows a martingale difference process. The martingale difference hypothesis has typically been tested using information contained in the second moments of a process, that is, using test statistics based on the sample autocovariances or periodograms. Tests based on these statistics are inconsistent since they cannot detect nonlinear alternatives. In this paper we consider tests that detect linear and nonlinear alternatives. Given that the asymptotic distributions of the considered tests statistics depend on the data generating process, we propose to implement the tests using a modified wild bootstrap procedure. The paper theoretically justifies the proposed tests and examines their finite sample behavior by means of Monte Carlo experiments.     

Local Gatekeeping Practices and Residential Segregation*

This article links the statistical data on residential segregation with the informal practices of individuals. Local gatekeeping practices contribute to the perpetuation of segregation and further explain the patterns of macro-level analyses. This research focuses on the community of Greenpoint, a predominantly white, working-class neighborhood in Brooklyn. The study describes the strategies used by residents of Greenpoint to accomplish residential segregation and to maintain a predominantly white non-Hispanic neighborhood. The process of informal housing networking is supported by the arrangements of local institutions.