BACKGROUND: Mediation modeling can explain the nature of the relation among three or more variables. In addition, it can be used to show how a variable mediates the relation between levels of intervention and outcome. The Sobel test, developed in 1990, provides a statistical method for determining the influence of a mediator on an intervention or outcome. Although interactive Web-based and stand-alone methods exist for computing the Sobel test, SPSS and SAS programs that automatically run the required regression analyses and computations increase the accessibility of mediation modeling to nursing researchers. OBJECTIVES: To illustrate the utility of the Sobel test and to make this programming available to the Nursing Research audience in both SAS and SPSS. METHODS: The history, logic, and technical aspects of mediation testing are introduced. The syntax files sobel.sps and sobel.sas, created to automate the computation of the regression analysis and test statistic, are available from the corresponding author. RESULTS: The reported programming allows the user to complete mediation testing with the user's own data in a single-step fashion. A technical manual included with the programming provides instruction on program use and interpretation of the output. CONCLUSION: Mediation modeling is a useful tool for describing the relation between three or more variables. Programming and manuals for using this model are made available.
BACKGROUND: Mediation modeling can explain the nature of the relation among three or more variables. In addition, it can be used to show how a variable mediates the relation between levels of intervention and outcome. The Sobel test, developed in 1990, provides a statistical method for determining the influence of a mediator on an intervention or outcome. Although interactive Web-based and stand-alone methods exist for computing the Sobel test, SPSS and SAS programs that automatically run the required regression analyses and computations increase the accessibility of mediation modeling to nursing researchers. OBJECTIVES: To illustrate the utility of the Sobel test and to make this programming available to the Nursing Research audience in both SAS and SPSS. METHODS: The history, logic, and technical aspects of mediation testing are introduced. The syntax files sobel.sps and sobel.sas, created to automate the computation of the regression analysis and test statistic, are available from the corresponding author. RESULTS: The reported programming allows the user to complete mediation testing with the user's own data in a single-step fashion. A technical manual included with the programming provides instruction on program use and interpretation of the output. CONCLUSION: Mediation modeling is a useful tool for describing the relation between three or more variables. Programming and manuals for using this model are made available.
Authors: Amy J Hoffman; Alexander von Eye; Audrey G Gift; Barbara A Given; Charles W Given; Marilyn Rothert Journal: Cancer Nurs Date: 2011 May-Jun Impact factor: 2.592
Authors: Sana El Mhamdi; Andrine Lemieux; Hela Abroug; Arwa Ben Salah; Ines Bouanene; Kamel Ben Salem; Mustafa al'Absi Journal: J Public Health (Oxf) Date: 2019-09-30 Impact factor: 2.341
Authors: S A Mitchell; N Kline Leidy; K H Mooney; W N Dudley; S L Beck; P C LaStayo; E W Cowen; P Palit; L E Comis; M C Krumlauf; D N Avila; N Atlam; D H Fowler; S Z Pavletic Journal: Bone Marrow Transplant Date: 2009-09-28 Impact factor: 5.483
Authors: Raquel Myers; Chih-Ping Chou; Steve Sussman; Lourdes Baezconde-Garbanati; Harry Pachon; Thomas W Valente Journal: J Health Soc Behav Date: 2009-06
Authors: Maria J Silveira; Charles W Given; Kemp B Cease; Alla Sikorskii; Barbara Given; Laurel L Northouse; John D Piette Journal: BMC Palliat Care Date: 2011-11-25 Impact factor: 3.234
Authors: Chunyan Yang; Ce Wang; Zhiwei Rong; Zhenyi Xu; Kui Deng; Weiwei Zhao; Lei Cao; Yaxin Lu; Humara Adnan; Kang Li; Yan Hou Journal: Cancer Manag Res Date: 2020-02-04 Impact factor: 3.989
Authors: Lorraine B Robbins; Karin A Pfeiffer; Amber Vermeesch; Kenneth Resnicow; Zhiying You; Lawrence An; Stacey M Wesolek Journal: BMC Public Health Date: 2013-05-15 Impact factor: 3.295