Literature DB >> 16713520

Multilevel modeling was a convenient alternative to common regression designs in longitudinal suicide research.

Elfi Antretter1, Dirk Dunkel, Peter Osvath, Viktor Voros, Sandor Fekete, Christian Haring.   

Abstract

BACKGROUND AND
OBJECTIVE: The prospective investigation of repetitive nonfatal suicidal behavior is associated with two methodological problems. Due to the commonly used definitions of nonfatal suicidal behavior, clinical samples usually consist of patients with a considerable between-person variability. Second, repeated nonfatal suicidal episodes of the same subjects are likely to be correlated. We examined three regression techniques to comparatively evaluate their efficiency in addressing the given methodological problems. STUDY DESIGN AND
SETTING: Repeated episodes of nonfatal suicidal behavior were assessed in two independent patient samples during a 2-year follow-up period. The first regression design modeled repetitive nonfatal suicidal behavior as a summary measure. The second regression model treated repeated episodes of the same subject as independent events. The third regression model represented a hierarchical linear model.
RESULTS: The estimated mean effects of the first model were likely to be nonrepresentative for a considerable part of the study subjects. The second regression design overemphasized the impact of the predictor variables. The hierarchical linear model most appropriately accounted for the heterogeneity of the samples and the correlated data structure.
CONCLUSION: The nonhierarchical regression designs did not provide appropriate statistical models for the prospective investigation of repetitive nonfatal suicidal behavior. Multilevel modeling provides a convenient alternative.

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Year:  2006        PMID: 16713520     DOI: 10.1016/j.jclinepi.2005.10.010

Source DB:  PubMed          Journal:  J Clin Epidemiol        ISSN: 0895-4356            Impact factor:   6.437


  2 in total

1.  The factorial structure of the Suicide Intent Scale: a comparative study in clinical samples from 11 European regions.

Authors:  E Antretter; D Dunkel; C Haring; P Corcoran; D De Leo; S Fekete; K Hawton; A J F M Kerkhof; J Lönnqvist; E Salander Renberg; A Schmidtke; K Van Heeringen; D Wasserman
Journal:  Int J Methods Psychiatr Res       Date:  2008       Impact factor: 4.035

2.  Multilevel analysis of air pollution and early childhood neurobehavioral development.

Authors:  Ching-Chun Lin; Shih-Kuan Yang; Kuan-Chia Lin; Wen-Chao Ho; Wu-Shiun Hsieh; Bih-Ching Shu; Pau-Chung Chen
Journal:  Int J Environ Res Public Health       Date:  2014-07-02       Impact factor: 3.390

  2 in total

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