2016
DOI: 10.1177/0022427816657578
|View full text |Cite
|
Sign up to set email alerts
|

The Role of Religious Support in Reentry

Abstract: Objective: Research on the relationship between religion and criminal recidivism has produced encouraging but ultimately inconclusive findings. This study offers a new direction for studying the role of religious support in reentry, providing a longitudinal analysis of the effect of change in religious support on both crime and noncrime outcomes postrelease. Methods: Employing mixed-effects longitudinal analyses, this study uses data from the Serious and Violent Offender Reentry Initiative to examine the impac… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

6
36
0
2

Year Published

2017
2017
2024
2024

Publication Types

Select...
8
1

Relationship

4
5

Authors

Journals

citations
Cited by 45 publications
(44 citation statements)
references
References 71 publications
(92 reference statements)
6
36
0
2
Order By: Relevance
“…Nevertheless, to reconfirm these findings, we estimated a series of t tests that compared our target respondents with those who dropped out across the measures used in this analysis. No t value reached statistical significance, supporting the assumption that the data are missing at random as well as prior findings from SVORI primary investigators (Lattimore and Steffey, 2010;Lattimore and Visher, 2009) and researchers (Stansfield et al, 2017;Wallace et al, 2016). Furthermore, to ensure that results were not being affected by patterns of missingness, we performed an identical series of analyses to those described in the next section using full-information maximum likelihood (FIML) imputation, the preferred method of imputing missing values in cross-lagged dynamic panel data models (Moral-Benito, Williams, Allison, and Moral-Benito, 2017).…”
Section: Missing Datasupporting
confidence: 65%
“…Nevertheless, to reconfirm these findings, we estimated a series of t tests that compared our target respondents with those who dropped out across the measures used in this analysis. No t value reached statistical significance, supporting the assumption that the data are missing at random as well as prior findings from SVORI primary investigators (Lattimore and Steffey, 2010;Lattimore and Visher, 2009) and researchers (Stansfield et al, 2017;Wallace et al, 2016). Furthermore, to ensure that results were not being affected by patterns of missingness, we performed an identical series of analyses to those described in the next section using full-information maximum likelihood (FIML) imputation, the preferred method of imputing missing values in cross-lagged dynamic panel data models (Moral-Benito, Williams, Allison, and Moral-Benito, 2017).…”
Section: Missing Datasupporting
confidence: 65%
“…The titles of published studies describe analyses as examining “ violent offenders released to the community” (Braga, Piehl, and Hureau, ), “the labeling of convicted felons ” (Chiricos et al., ), “attitudes toward ex‐offenders ” (Hirschfield and Piquero, ), “re‐entry for sex offenders ” (Levenson, D'Amora, and Hern, ), “the effect of criminal background checks on hiring ex‐offenders ” (Stoll and Bushway, ), and “the effect of stigma on criminal offenders ’ functioning” (Moore, Stuewig, and Tangney, ) . Authors ask “how many [registered] sex offenders really live among us?” (Ackerman, Levenson, and Harris, : 464), hypothesize that a variable's effect “on reentry success will be partially explained by changes in an offender's family and peer support networks” (Stansfield et al., : 9), or conclude that findings highlight “both the promise and the limitations of employment programs for criminal offenders ” (Uggen, : 544).…”
Section: Discussionmentioning
confidence: 99%
“…In nearly all panel studies, respondent attrition can be an issue that can bias analyses using follow‐up samples, and it is especially challenging to follow the formerly incarcerated released to their communities (Western, Braga, Hureau, & Sirois, ). Findings from several works, however, indicate that these data are missing at random, including studies conducted by the original SVORI investigators (Lattimore & Steffey, ), as well as by other researchers (Boman & Mowen, ; Stansfield, Mowen, O'Connor, & Boman, ; Wallace et al., ). Our key health variables were measured at baseline and have almost no missing data, and the ultimate reincarceration variable measured at 15 months contains no missing data.…”
Section: Data and Measuresmentioning
confidence: 99%
“…Additional supporting information can be found in the listing for this article in the Wiley Online Library at http://onlinelibrary.wiley.com/doi/10.1111/crim.2019.57.issue-3/issuetoc. that these data are missing at random, including studies conducted by the original SVORI investigators (Lattimore & Steffey, 2010), as well as by other researchers Stansfield, Mowen, O'Connor, & Boman, 2016;Wallace et al, 2016). Our key health variables were measured at baseline and have almost no missing data, and the ultimate reincarceration variable measured at 15 months contains no missing data.…”
Section: Missing Datamentioning
confidence: 99%