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In the evaluation of most interventions in criminal justice settings, evaluators have no control over assignment to treatment and control/comparison conditions, which means that the treated and comparison groups may have differences that lead to biased conclusions regarding treatment effectiveness. Propensity score analysis can be used to balance the differences in the groups, which can be used in a number of ways to reduce biased conclusions regarding effectiveness. A review of propensity scoring studies was conducted for this chapter, where the limited number of evaluations of criminal justice interventions using these methods was identified. Due to the small number of these studies, research was also reviewed if propensity scoring had been employed to evaluate interventions that are similar to those in criminal justice systems. These studies are used as examples to demonstrate how the methods can be used to evaluate criminal justice interventions, the different ways propensity scores can be used to analyse treatment and comparison group differences, and the strengths and limitations of this approach. It is concluded that, while not appropriate for all interventions/settings, propensity score analysis can be useful in criminal justice arenas, at least to investigate the comparability of treatment and comparison groups, with suspected non-comparability being a common weakness of traditional quasi-experimental studies and frequently cited limitation in terms of drawing efficacy conclusions from such evaluations.

Without controlling for selection bias and the potential endogeneity of the treatment by using proper methods, the estimation of treatment effect could lead to biased or incorrect conclusions. However, these issues are not addressed adequately and properly in higher education research. This study reviews the essence of self-selection bias, treatment assignment endogeneity, and treatment effect estimation. We introduce three treatment effect estimators – propensity score matching analysis, doubly robust estimation (augmented inverse probability weighted approach), and endogenous treatment estimator (control-function approach) – and examine literature that applies these methods to research in higher education. We then use the three methods in a case study that estimates the effects of transfer student pre-enrollment debt on persistence and first year grades. The final discussion provides guidelines and recommendations for causal inference research studies that use such quasi-experimental methods.

Among the research studies related to the relevance between religious belief and mental health, most of them highlight people with religious belief who tend to obtain mental comforting more easily. However, the research studies mentioned above were cross-sectional studies, and they only verified that religious beliefs and mental health are relevant, but they did not prove their cause-and-effect relationship. That is, they do not identify “due to people's religious beliefs, they have healthier mind” or “due to people's healthier minds, they have religious beliefs.” Therefore, the study aims to explore the benefit evaluation of religious belief affecting mental health.

The study uses propensity score matching (PSM) and treatment effect (ATT) to carry out the causal inference between religious beliefs and mental health. First, the propensity score (PS) is calculated from the impact factors that affect people's religious belief before establishing counterfactual analysis based on the PS to analyze the effect of religious beliefs to further understand the difference of mental health index between people with religious belief and without it, and confirm the cause-and-effect relationship between them.

Religious beliefs and participation are ubiquitous within and across populations. The associates between religious participation and health are considerably in great magnitude. Most of the research in the past related to religious beliefs and mental health only verified that religious beliefs and mental health are relevant but not proved its cause-and-effect relationship. This paper aimed to explore the causal relationship between religious belief and mental health. The experimental results showed religious belief has treatment effect toward “daily functioning,” “feeling affect,” “spirituality” and “mental health.” On a whole, religious belief can promote mental health.

In academic and practical circles, there are a lot of research studies exploring the relationship between religious belief and mental health. However, there is no research investigating the cause-and-effect relationship between religious belief and mental health. It also causes some questioning toward the relevant research studies. Therefore, the outcome of this study not only can clarify the legitimacy, importance, and practicality on the researches in the past but also provide the practical support for psychology and counseling.

This paper aims to introduce matching in propensity score analysis (PSA) as an alternative statistical approach for researchers looking to make causal inferences using intact groups.

An illustrative example demonstrated the varying results of analysis of variance, analysis of covariance and PSA on a heuristic data set. The three approaches were compared by results and violations of statistical assumptions.

Through the illustrative example, it is demonstrated how different statistical approaches can produce varied results. Only PSA mitigated pre-existing group differences without violating the assumption of independence.

This paper attempts to answer calls in the literature for more robust statistical methodologies to better inform human resource development practice and theory.

The purpose of this paper is to illustrate how to examine the effectiveness of a pilot summer bridge program for elementary algebra using propensity scores. Typically, selection into treatment programs, such as summer bridge programs, is based on self-selection. Self-selection makes it very difficult to estimate the true treatment effect because the selection process itself often introduces a source of bias.

By using propensity scores, the authors can match students who participated in the summer bridge program with equivalent students who did not participate in the summer bridge program. By matching students in the treatment group to equivalent students who do not participate in the treatment, the authors can obtain an unbiased estimate of the treatment effect. The authors also describe a method to conduct a sensitivity analysis to estimate the amount of hidden bias generated from unobserved factors that would be needed to alter the inferences made from a propensity score matching analysis.

Findings suggest there is no significant difference in the pass rates of the subsequent intermediate algebra course for students who participated in the summer bridge program when compared to matched students who did not participate in the summer bridge program. Thus, students who participate in the summer bridge program fared no better or worse when compared to similar students who do not participate in the program. These findings also appear to be robust to hidden bias.

This study describes a unique way to estimate the causal effect of participating in a treatment program when there is self-selection into the treatment program.

This paper aims to presents one of the first direct micro-econometric impact of competitive industries (based on revealed comparative advantage [RCA] between Pakistan and China) on household welfare in Pakistan using semi-parametric matching technique.

The study has also measured and identified the industrial competitiveness in both agricultural and non-agricultural (manufacturing) industries using RCA approach. RCA at the four-digit ISIC level are matched to household survey data (Pakistan Social and Living Standard Measurement) for 2013-2014 to represent the competitive industries in which the household’s higher earner is employed.

The findings of the study reveal that the China–Pakistan ex-post treatment effect (industrial competitiveness) provides welfare-improving effects. Furthermore, on this behalf, this study further assesses ex-ante treatment effects of recently signed China–Pakistan Economic Corridor (CPEC) on household welfare and suggests that CPEC would boost further trade liberalization and, therefore, would lead to industrial competitiveness and hence economic growth.

Paper contributes to two streams of literature. First, it measures and identifies the industrial competitiveness in both agricultural and non-agricultural industries using RCA approach; and second, it assesses the welfare of those households associated with these industries using semi-parametric propensity score matching technique.

The current study seeks to assess the predictive utility of personality, family violence, associations with criminal friends, peer rejection, parental attachment, and parental supervision as predictors of homicidal behaviour among a sample of 144 male recidivistic offenders.

This research project utilized a quasi‐experimental design with propensity score matching in order to minimize the effect of selection bias. Post‐matching binary logistic regression analysis was subsequently conducted in order to determine what factors predict homicidal behaviour.

Post‐matching regression results indicated that experience of family violence, psychoticism, and parental attachments were significant predictors of being a homicidal murderer.

The findings provide strong empirical support for the important role of early childhood experiences in the prediction of homicidal acts, along with the crucial role of personality (psychoticism). These findings provide additional support for Eysenck's theoretical indications regarding the role of psychoticism in the prediction of violent criminal behaviours.

This study examines the relationship between small-firm managers' propensity to participate in a growth-oriented training program and their subsequent program outcome in terms of strategic reorientation. From a policy perspective, this relates to the important question of what benefit would come from recruiting managers who are normally not easily recruitable for training programs.

A control group design including pre- and post-training surveys is used to assess the effects of a large-scale management training program. Accounting for selection bias, the difference-in-difference method, together with propensity score matching, was applied to assess average program effects. The matching-smoothing method was used to assess heterogeneity in program effects associated with participation propensity.

Overall, program participation associated positively with change in strategic orientations. This effect was especially pronounced for managers with either low or medium to high inclinations for program enrollment, while diminishing in the modest to medium range.

The findings have important practical implications for selection of target groups and recruitment strategies in relation to small-firm management training programs. From the results, recruitment strategies may effectively include managers with either high or low participation propensities, rather than aiming to “fill up” with managers with moderately low participation propensity.

Several extant studies have examined average treatment effects from small-firm training programs. Yet there has been a lack of examination of the extent to which participation propensity modifies the effect of training on outcomes. This study brings new knowledge of the direction and magnitude of such heterogeneous training effects.

In this chapter, we evaluate the employment effects of job-creation schemes (JCS) on the participating individuals in Germany. JCS are a major element of active labour market policy in Germany and are targeted at long-term unemployed and other hard-to-place individuals. Access to very informative administrative data of the Federal Employment Agency justifies the application of a matching estimator and allows us to account for individual (group-specific) and regional effect heterogeneity. We extend previous studies for Germany in four directions. First, we are able to evaluate the effects on regular (unsubsidised) employment. Second, we observe the outcomes of participants and non-participants for nearly three years after the programme starts and can therefore analyse medium-term effects. Third, we test the sensitivity of the results with respect to various decisions that have to be made during implementation of the matching estimator. Finally, we check if a possible occurrence of a specific form of ‘unobserved heterogeneity’ distorts our interpretation. The overall results are rather discouraging, since the employment effects are negative or insignificant for most of the analysed groups. One exception are long-term unemployed individuals who benefit from participation at the end of our observation period. Hence, one policy implication is to address the programmes to this problem group more closely.

In the existing literature on crowdfunding project performance, previous studies have given little attention to the impact of investors’ hedonic value and utilitarian value on project results. In a crowdfunding setting, utilitarian value is somehow hard to satisfy due to information asymmetry and adverse selection problem. Therefore, the projects with more hedonic value can be more attractive for potential investors. Lucky draw is a method to increase consumer hedonic value, and it can influence investors’ behavior as a result. The authors hypothesize that projects with hedonic treatment (lucky draw) may have higher probability to win their campaign than others. The paper aims to discuss these issues.

A unique self-extracted two-year Chinese crowdfunding platform real data set has been applied as the analysis sample. The authors first employ propensity score matching methods to control for the endogeneity of hedonic treatment adoption (lucky draw). The authors then run OLS regression and probit regression in order to test the hypotheses.

The analysis suggests a significant positive relationship not only between project lottery adoption and project results but also between project lottery adoption and project popularity.

The results suggest that an often ignored factor – hedonic treatment (lucky draw) – can play an important role in crowdfunding project performance.