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. 2018 Jun;26(2):111-114.
doi: 10.5455/aim.2018.26.111-114.

Comparison of Efficiency GEE and QIF Methods for Predicting Factors Affecting on Bipolar I Disorder Under Complete-case in a Longitudinal Studies

Zahra Geraili-Afra  1 , Alireza Abadi  2 , Jamshid Yazdani-Charati  3 , Somayeh Ahmadi Gooraji  2 , Mehran Zarghami  4 , Samaneh Saadat  5
Affiliations

Comparison of Efficiency GEE and QIF Methods for Predicting Factors Affecting on Bipolar I Disorder Under Complete-case in a Longitudinal Studies

Zahra Geraili-Afra et al. Acta Inform Med. 2018 Jun.

Abstract

Background: Mood variation in manic and depression phases during time is common in type I of Bipolar disorder. Analyzing recurrence require to the related statistical methods. In this paper, we compare the two methods of estimating the GEE and the QIF in recurrence data.

Methods: In this study, data of 255 patients with Bipolar I disorder hospitalized during years of 2007-2011. Recurrence in Bipolar I disorder was as outcome. Patients' characteristics were gender, age of onset, recurrence history in first degree family, and economic status. Under simulation, percentage of missing were generated to vary and handled by complete-case(cc) strategy. Data were analyzed using GEE and QIF methods. Performance of the methods was assessed using Relative Efficiency.

Results: QIF method had more efficiency than GEE method in the data with missing /without missing. Odds of recurrence in a first-degree family history was 30% more than those without a family history (p=0.009). Also, odds of recurrence in high/moderate level of economic status was 23% more than low level status (p=0.014).

Conclusion: QIF method was more appropriated for modeling recurrence during time with the structure of more correlation and low dropout rate in data. Family history and economic status were more affected recurrence in type I of Bipolar disorder.

Keywords: Bipolar I disorder; Generalized Estimation Equations; Quadratic Inference Function; Recurrence; missing; simulation.

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