Methods and Challenges of Analyzing Spatial Data for Social Work Problems: The Case of Examining Child Maltreatment Geographically.

A study was conducted to investigate methods and challenges associated with the analysis of spatial data for social work problems. Data were obtained from examination of 941 census tracts from California for structural factors related to child maltreatment. Findings revealed a negative association...

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Publicado en:Social Work Research Vol. 30; no. 4; pp. 198 - 211
Autores principales: Freisthler, Bridget, Lery, Bridgette, Gruenewald, Paul J.
Formato: Artículo
Publicado: National Association of Social Workers December 2006
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Methods and Challenges of Analyzing Spatial Data for Social Work Problems: The Case of Examining Child Maltreatment Geographically.
      aug:
        au:
          Freisthler, Bridget
          Lery, Bridgette
          Gruenewald, Paul J.
      su:
        Child abuse
        Social services -- Research
        Geographic information systems
        Spatial analysis (Statistics)
      sug:
        subj:
          Child abuse
          Social services -- Research
          Geographic information systems
          Spatial analysis (Statistics)
      ab: A study was conducted to investigate methods and challenges associated with the analysis of spatial data for social work problems. Data were obtained from examination of 941 census tracts from California for structural factors related to child maltreatment. Findings revealed a negative association between immigrant populations/child care burden and rates of child maltreatment when using ordinary least squares (OLS) regression. However, no such relationship was found when generalized linear squares regression models were employed. Findings imply that a reliance on OLS regression methods when creating programs to tackle child maltreatment in spatial areas could result in the development of ineffective strategies that fail to reduce maltreatment. Findings are discussed in detail.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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