Participants, Participant Demographics and Participant Selection
In this research study, neighborhood plays a significant role in the understanding of why people offend, and more importantly for understanding why ex-convicts re-offend. The study, in pursuance of understanding the role of socioeconomic status of a neighborhood in influencing recidivism would have the target participants as official records of a group of ex-offenders, together with the 2000 census data. The study will employ the use of secondary data.
The question that motivates this study is the degree to which the socioeconomic characteristicof aneighborhood accounts for variations in the recidivism comportment of released convicts that is not accounted for by their individual level characteristics?” The study employs the use of 2000 U.S census data and data from individuals on community supervision in the county of interest. Data on ex-convicts can be obtained through a request of a list of offenders admitted to community supervision between a specified time period from the respective state department of corrections and the state’s repository for all community supervision data.The participant predominant common characteristic would be that he or she must be an ex-offender. The number of participants would ideally be around 5,000 (n=5,000)
Once the sample is identified, a variety of data on the participants would be obtained from various criminal justice agencies. The county department of community justice would provide information on offender characteristics such as sex, age, and race; and offense characteristics such as current offense and number of prior arrests.Data on the use of sanctions would be obtained from the department of correction’s sanctions tracking database, which has invaluable information on whether or not each former inmate committed a sanction-able offense during the study period. Finally, data or arrests made during the supervision period would be obtained from the data warehouse, decision support system justice, which contains integrated, individual level data from law enforcement agencies, the district attorney as well as the courts.
Post-charge residences would be identified in the sample which will reflect the first known housing location after release. The home address data would be matched with the 2000 national census data to determine the census tract in which each ex-convict was located. Census tracts would serve as proxies for neighborhoods.The neighborhood socioeconomic status would be determined by the proportion of persons living off public assistance, proportion of persons living below the poverty level,proportion of people unemployed and median family income.
Statistical Tests to be conducted
The research study core objective is to identify whether there exists any relationship between the independent variable and the dependent variable. It also seeks to establish the extent to which the variables relate and the nature of the relationship. To achieve this goal, two statistical analyses would be used, correlation analysis and regression analysis.
Correlation analysis is one of the statistical tests that the variable will be subjected to. Correlation analysis is an important test because it tests for the existence of a relationship between the variables. It is normally used with two variables to determine a relationship or association. It helps in establishing whether the two variables covary. This test is appropriate for this study because it will help in establishing how strongly the socioeconomic status of a neighborhood and recidivism rates relate and in what direction the variables are associated. However, it does not distinguish between independent and dependent variables.
The other test that the variables would be subjected to is multiple regression analysis. Regression is predominantly used for prediction as it identifies the best set of predictor variables. This test is ideally used when there are several independent variables and one dependent variable. This test is appropriate for this study because itwill help in establishing how much variance in the rates of recidivism among ex-offenders that is explained by the linear combination of the independent variable- socioeconomic status of the neighborhood. How strongly related the variables are, is reflected by the beta coefficient of the independent variable.
Information to be obtained from the Results of these Tests and what will be needed to Draw Conclusions Regarding the Hypotheses
From the correlation test, the statistic of interest will be the coefficient of correlation (r), which will indicate whether a relationship exists between the variables.Any non-zero coefficient denotes that there exists a relationship between the variables. A positive coefficient will denote that there exists a direct relationship between the variables, that is, an increase in one variable result to an increase in the other variable. A negative coefficient implies that the variables have an inverse relationship, while a zero coefficient denotes the non-existence of any relationship between the variables.
A non-zero coefficient of correlation from the correlation analysis will denote that there is a relationship between the variable,a non-zero independent variable coefficient obtained for the regression analysis will also denote that there exists a relationship and show the direction of the relation. In general terms, any non-zero result will mean that the researcher rejects the null hypothesis and accepts the alternative hypothesis.
Expected Biases, Assumptions, and Faults with the Proposed Study and the use of the Identified Statistical Tests
One obstacle to the research study would be the working definition of recidivism. It can be measured through many ways, such as, the number of reconvictions, re-incarceration and re-arrest. However, the most appropriate working definition would be problematic when deciding on which data to use.
The use of correlation analysis as one of the statistical tests also brings with it a number of shortcomings. This statistical instrument only shows the presence or lack of a relationship between two variables, it does not show a cause and effect relationship as it does not establish which variable preceded the other in time, that is, it does not establish causation. Additionally, it has a tendency to carry with it the problem of spurious correlation, where it brings with it a false correlation between two variables. However, these are shortcomings which are addressed by the use of regression analysis.
Practical Significance and Importance of the Results
The main objective of the research study is to establish the influence of a neighborhood’s socioeconomic status on the rates of recidivism among ex-convicts. This objective encompasses establishing whether there exists an association between the two variables, as well as the cause and effect of the variables, and finally the nature and degree of association between the socioeconomic statuses of a neighborhood to the rates of recidivism.The correlation test will assist in computing the coefficient of correlation which will provide data in deducing the presence or absence thereof of anassociation between the two variables and the degree to which they have an association. Regression analysis will provide information on the direction of causation, the extent to which the independent variable explains the independent variable, as well as further re-affirm the findings from the coefficient of correlation on the degree and nature of the relationship.
Conclusions that can be made for the Study using these Statistical Tests
Most recidivism studies have focused on personal characteristics of the offender, overlooking the role that the neighborhood plays in former prisoner’s lives. Previous studies have treated neighborhood as constant and thus irrelevant for understanding recidivism. A neighborhood’s socioeconomic status is fundamental to the apprehending of why people commit an offence, and even more importantly for understanding why ex-convicts recidivate. Previous researches have indicated that there are many factors that influence an ex-convict decision to reoffend. Factors such as individual characteristics, state policies and family relationships have been found to play a significant role in influencing an ex-convict’s decision to recidivate. This research study looks at the influence that neighborhood socioeconomic status has on the decision of an ex-convict to reoffend. The findings of the research study would be invaluable to the government through the relevant policy making agencies as they will direct their focus towards the importance of a neighborhoods’ socioeconomic composition in reducing recidivism rates as well as curbing and predicting criminal activities.
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