Evaluation Findings: Rural Reentry Program Works, Data Download, Iowa Department of Corrections, April 2010

Iowa’s Division of Criminal and Juvenile Justice Planning (CJJP) recently completed an evaluation of the 2nd Judicial District’s Rural Prisoner Reentry Initiative (PRI), which provided reentry services to offenders both while in prison and after release.

Institution Reentry Coordinators Proving to be Important Link, Data Download, Iowa Department of Corrections, March 2010

An offender reentry grant program funded through the Governor’s Office of Drug Control Policy supports one reentry coordinator at each of the following institutions: Mount Pleasant Correctional Facility (MPCF), Fort Dodge Correctional Facility and the Clarinda Correctional Facility. The reentry coordinators there engage in a myriad of activities, working with institution educators, counselors and medical personnel, probation/parole officers and counselors, and most importantly the offenders themselves. The program has not been in operation for very long, and only MPCF has operated long enough to be looking at outcomes. The early returns for MPCF show good promise.

Halfway Back Works, Data Download, Iowa Department of Corrections, May 2011

In an effort to reduce the strain on limited prison beds, the Board of Parole – with the support of the Department of Corrections – instituted the Halfway Back revocation option. This option allows for selected parolees to be revoked to work release rather than to prison.

Violator Program: Community Aftercare is Key, Data Download, Iowa Department of Corrections, November 2008

Through an act of the Iowa Legislature, the Violator Program came into existence some 20 years ago, the purpose of which was to provide an alternative to long-term imprisonment for those offenders whose probation/parole had been suspended. This 4-6 month program is currently administered at three locations: Luster Heights, Newton Correctional Release Center,and the Iowa Correctional Institution for Women.

From Empirical Bayes to Full Bayes: Methods for Analysing Traffice Safety Data, October 25, 2004

Traffic safety engineers are among the early adopters of Bayesian statistical tools for analyzing crash data. As in many other areas of application, empirical Bayes methods were their first choice, perhaps because they represent an intuitively appealing, yet relatively easy to implement alternative to purely classical approaches. With the enormous progress in numerical methods made in recent years and with the availability of free, easy to use software that permits implementing a fully Bayesian approach, however, there is now ample justification to progress towards fully Bayesian analyses of crash data. The fully Bayesian approach, in particular as implemented via multi-level hierarchical models, has many advantages over the empirical Bayes approach. In a full Bayesian analysis, prior information and all available data are seamlessly integrated into posterior distributions on which practitioners can base their inferences. All uncertainties are thus accounted for in the analyses and there is no need to pre-process data to obtain Safety Performance Functions and other such prior estimates of the effect of covariates on the outcome of interest. In this slight, fully Bayesian methods may well be less costly to implement and may result in safety estimates with more realistic standard errors. In this manuscript, we present the full Bayesian approach to analyzing traffic safety data and focus on highlighting the differences between the empirical Bayes and the full Bayes approaches. We use an illustrative example to discuss a step-by-step Bayesian analysis of the data and to show some of the types of inferences that are possible within the full Bayesian framework.

From Empirical Bayes to Full Bayes: Methods for Analyzubg Traffic Safey Data, October 25, 2004

Traffic safety engineers are among the early adopters of Bayesian statistical tools for analyzing crash data. As in many other areas of application, empirical Bayes methods were their first choice, perhaps because they represent an intuitively appealing, yet relatively easy to implement alternative to purely classical approaches. With the enormous progress in numerical methods made in recent years and with the availability of free, easy to use software that permits implementing a fully Bayesian approach, however, there is now ample justification to progress towards fully Bayesian analyses of crash data. The fully Bayesian approach, in particular as implemented via multi-level hierarchical models, has many advantages over the empirical Bayes approach. In a full Bayesian analysis, prior information and all available data are seamlessly integrated into posterior distributions on which practitioners can base their inferences. All uncertainties are thus accounted for in the analyses and there is no need to pre-process data to obtain Safety Performance Functions and other such prior estimates of the effect of covariates on the outcome of interest. In this light, fully Bayesian methods may well be less costly to implement and may result in safety estimates with more realistic standard errors. In this manuscript, we present the full Bayesian approach to analyzing traffic safety data and focus on highlighting the differences between the empirical Bayes and the full Bayes approaches. We use an illustrative example to discuss a step-by-step Bayesian analysis of the data and to show some of the types of inferences that are possible within the full Bayesian framework.

Health consultation : Silver City petroleum release and municipal wells, Silver City, Mills County, Iowa (2005)

A resident of Silver City, Iowa requested the Iowa Department of Public Health (IDPH) Hazardous Waste Site Health Assessment Program to evaluate the health impacts of a petroleum release in Silver City, Iowa, and the health impacts from the presence of chemicals detected in wells utilized as the source of municipal water for the citizens of Silver City and in the treated municipal water supply. This health consultation addresses exposure to residents of Silver City to organic chemicals within the groundwater and water supply and potential health effects at the levels of exposure. The information in this health consultation was current at the time of writing. Data that emerges later could alter this document’s conclusions and recommendations.