Impact Assessment in Observational Studies: A Classification and Regression Tree Approach

Shmueli, Galit; Mani, Deepa

doi:10.2139/ssrn.2276770

Cited by 2 publications

(2 citation statements)

References 69 publications

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“…The tree starts with a single node (the root) to which the entire data file belongs, which is then binary divided into other nodes. In each node of the tree, a dividing variable is defined based on which the data set is divided into two groups, as well as the cut-off value of this dividing variable, which determines the value at which the division should take place (Shmueli & Mani, 2013;Berk, 2008). In our study, the root is a group of all individuals in the study, both treated and non-treated.…”

Section: {2} {3}mentioning

confidence: 99%

Impact Evaluation of the Graduate Practice Intervention in Slovakia with the Application of the CART Method

Gabrikova

Švábová

2023

TalTech Journal of European Studies

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In Slovakia, the contribution to graduate practice is one of the active labour market policy interventions, the main goal of which for young school-leavers is to gain first job experiences and contacts with potential employers. Among the young jobseekers, it is one of the most used interventions. This study aims to provide a counterfactual impact evaluation of this contribution on the employability of its participants and also on their monthly wages. The total period under review is 2014–2017, during which the treated individuals participated in the graduate practice during 2014–2015. Then, their course of employment and average monthly wages were monitored over a two-year impact period, covering the period 2015–2017. The study was carried out using a database of 12,953 treated eligible participants of graduate practice and 83,907 non–treated controls. The data used in the study is managed by the Central Office of Labour, Social Affairs and Family of the Slovak Republic (COLSAF SR) and the Social Insurance Agency (SIA). For the evaluation, propensity score matching was used, where the propensity scores were estimated using classification and regression trees. The results of the study show that the participants of the graduate practice were employed on average three months longer during the two-year impact period after the end of the intervention as full-time employees or self-employed, and their average salary was almost 217 euros higher than that of the control group of non-participants.

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Section: {2} {3}mentioning

confidence: 99%

Impact Evaluation of the Graduate Practice Intervention in Slovakia with the Application of the CART Method

Gabrikova

Švábová

2023

TalTech Journal of European Studies

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“…This feature enables decision trees to effectively predict the outcome values of individual observations and to select important predictor variables [51]. This study is based on the tree-based method for assessing the effects of self-selective interventions proposed by Yahav et al [52] to evaluate the differences in average daily steps between users under different intervention conditions, i.e., under varying degrees of perceived social support.…”

Section: B Modeling Processmentioning

confidence: 99%

Research on the Relationship Between Perceived Social Support and Exercise Behavior of User in Social Network

Lei

Zeng

2020

IEEE Access

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A growing number of information technology systems and services have occurred to change users' attitudes or behaviors or both in the rapid development of mobile social media platforms. It is a new topic in the field of health communication whether the digitization and socialization of individual exercise behavior can stimulate health behavior. WeRun is a typical platform for the digitization and socialization of individual exercise. Based on 689 WeRun users' questionnaires, this study first repairs the missing and abnormal data by BP neural network. Then, the decision tree is used to evaluate the relationship between the perceived social support and exercise behavior under different intervention conditions, and detects the heterogeneous intervention effects for different pre-intervention profiles. In addition, this study further discusses the performances of social support features of persuasion technology in the WeRun. The data-driven method used in this study is beneficial to reducing self-selection bias and evaluate the intervention effect. The decision tree does not require decision-makers to have much expertise or to make parameter hypotheses while evaluating the intervention effect, and the results are more direct and intelligible. The results show that the decision tree can detect the heterogeneous intervention effect. In some cases, there is not a perfectly positive correlation between the degree of perceived social support and the number of average daily steps, and the relationship with friends has a great impact on the user's perceived social support. In addition, it also reveals the relationship between social comparison and perceived social support, and their interaction on exercise behavior. Finally, this study provides practical suggestions for the design and operation of e-health social network platform. The platforms are supposed to take corresponding persuasive strategies according to the various characteristics of users, so as to improve the continuous attention and participation of users.

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Impact Assessment in Observational Studies: A Classification and Regression Tree Approach

Cited by 2 publications

References 69 publications

Impact Evaluation of the Graduate Practice Intervention in Slovakia with the Application of the CART Method

Impact Evaluation of the Graduate Practice Intervention in Slovakia with the Application of the CART Method

Research on the Relationship Between Perceived Social Support and Exercise Behavior of User in Social Network

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