Showing papers by "Michael Hughes published in 1991"

Social Change and Crime Rates: An Evaluation of Alternative Theoretical Approaches

Abstract: Two general theoretical perspectives, criminal opportunity and social disorganization, have been widely used to explain the level of crime in cities and temporal changes in their crime rates. Using a pooled cross-sectional and time-series design of 584 U.S. cities for the years 1960, 1970, and 1980, the present study evaluates the empirical adequacy of these theories. The cross-sectional findings were far more supportive of social disorganization theories than criminal opportunity theories. However, neither perspective was able to consistently explain changes in crime rates over time. Ethnic heterogeneity, household size, and the rate of crowding in households were the strongest predictors of the level and changes in official rates of homicide, robbery, and burglary. The results are discussed in terms of their implications for future research. Explanations for rising crime rates in the U.S. have taken various forms. Traditional theories of criminality (e.g., anomie, differential association, conflict, social bonding) identify the level of social integration, cultural conflict, economic inequality, and breakdown in social control as major correlates of crime. During the last decade, several opportunity-based theories (routine activities, lifestyle/exposure and rational choice models) have emerged as rival explanations for changing crime rates. Essentially, these criminal opportunity theories

Practical Reporting of Bayesian Analyses of Clinical Trials

Abstract: Agreement on appropriate ways of presenting Bayesian analyses of clinical trials is essential if these methods are to obtain more widespread use and not fall into disrepute. Using an example based upon a trial currently in progress, two aspects of reporting are proposed. Using noninformative priors gives standardized likelihoods from which point and interval estimates, and probabilities associated with adverse effects, can be obtained with numerically similar values to classical estimates, confidence intervals, and p-values. Standardized likelihoods are therefore a useful means of introducing Bayesian analyses into trial reports and emphasizing the change in interpretation to quantifying beliefs. The second important use of Bayesian analyses is to illustrate strength of evidence coming from a trial by showing the sensitivity of the conclusions drawn to choice of prior distribution made. This can be achieved by employing other well–defined priors, notably that based on previous trial results and that refle...