A Comparison of Bias Reduction Methods: Clustering versus Propensity Score Subclassification and Weighting

D’Attoma, Ida; Camillo, Furio; Clark, M. H.

doi:10.1080/00220973.2017.1391161

Cited by 3 publications

(1 citation statement)

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“…The distribution of the observations into the subgroup can be implemented by methods as cluster analysis (CA) method or propensity score (PS) methods. However, in this research, we use the method of PS stratification because (1) the CA is more commonly accepted and applied in experimental studies (Peck, 2005;Gibson, 2003;Yoshikawa et al, 2001); (2) the CA is formulated using only baseline characteristics, which are exogenous to the treatment (D'Attoma et al, 2017), while PS is also based on baseline characteristics but related to JED 22,1 treatment (in this study, it is the result of the NRD program) and (3) among PS adjustments, PS stratification is one of the more effective ones (D'Attoma et al, 2017;Schafer and Kang, 2008).…”

Section: Research Modelmentioning

confidence: 99%

Determinants of the result of new rural development program in Vietnam

Hoang

2020

JED

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PurposeThe purpose of this paper is to identify the determinants of the proportion of communes that met all national new rural criteria (hereafter NRD communes).Design/methodology/approachFirst, the method of propensity score (PS) stratification is used to classify 63 provinces into the subgroups. Second, the ordinary least squares (OLS) model is used with the subgroups classified from the PS stratification method as one of explicative variables. The dependent variable in the OLS model is the proportion of NRD communes.FindingsWith the sample of 63 provinces of Vietnam, the author found that per capita income growth rate, high growth of gross regional domestic product (GRDP) and effort of the provincial authority have positive impact on the proportion of NRD communes.Practical implicationsThis research suggests that the provincial authority should actively participate in the NRD program, and the economic development is key factor for success implementation of the NRD program.Originality/valueThis research contributes to understand the factors impacting the result of the NRD program and then help to identify the measures to support this program.

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Section: Research Modelmentioning

confidence: 99%

Determinants of the result of new rural development program in Vietnam

Hoang

2020

JED

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Transporting Causal Effects Across Populations Using Structural Causal Modeling: An Illustration to Work-from-Home Productivity

Park

Tafti

Shmueli

2024

Information Systems Research

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Transportability is a structural causal modeling approach aimed at “transporting” a causal effect from a randomized experimental study in one population to a different population where only observational data are available. It allows for extracting much more value from randomized control trials because under some conditions, it allows the estimation of causal effects in a target population where replicating the experiment is difficult, costly, or impossible. Despite the enormous economic and social benefits of transportability, it has thus far seldom been implemented in practice, likely because of the lack guidelines for applying transportability theory in practice and on handling the statistical challenges that might arise. Using a practical problem as an illustration—estimating the effect of telecommuting on worker productivity—we attempt to offer a detailed procedure for transporting a causal effect across different populations, and we discuss some practical considerations for its implementation, including how to conceptualize causal diagrams, determine the feasibility of transport, select an appropriate diagram, and evaluate its credibility. We also discuss the current limitations, challenges, and opportunities for future research on transportability that would make it more amenable for broad practical use.

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