Modelling risk profiles of depression symptoms using Cloninger'stemperament and character traits: a noniterative approach to assess linear-by-linear association within ordered contingency tables

Zafar, S, Hudson, I, Beh, E and Joyce, P 2015, 'Modelling risk profiles of depression symptoms using Cloninger'stemperament and character traits: a noniterative approach to assess linear-by-linear association within ordered contingency tables', in Proceedings of the 21st International Congress on Modelling and Simulation (MODSIM2015), Gold Coast, Australia, 29 November - 4 December 2015, pp. 1668-1674.


Document type: Conference Paper
Collection: Conference Papers

Title Modelling risk profiles of depression symptoms using Cloninger'stemperament and character traits: a noniterative approach to assess linear-by-linear association within ordered contingency tables
Author(s) Zafar, S
Hudson, I
Beh, E
Joyce, P
Year 2015
Conference name MODSIM2015
Conference location Gold Coast, Australia
Conference dates 29 November - 4 December 2015
Proceedings title Proceedings of the 21st International Congress on Modelling and Simulation (MODSIM2015)
Publisher The Modelling and Simulation Society of Australia and New Zealand
Place of publication Australia
Start page 1668
End page 1674
Total pages 7
Abstract Personality is linked to mental illness. The relationship between the seven temperament and character traits (TCIs), (Novelty seeking (NS), Harm Avoidance (HA), Reward Dependence (RD), Persistence (P), Self-directedness (S), Cooperativeness (C) and Self Transcendence (ST)), of Cloninger (1994) and three symptoms of psychological distress, or SCLs (Depression (D), Anxiety (A) and Psychoticism (Psy)) is investigated across gender and shown to have significantly different symptom profiles post treatment. The data used in this study was earlier analysed by Turner, et al. (2003) and comes from patients measured pre and post-treatment from the NZ Christchurch Psychotherapy of Depression Study (Joyce, et al. 2002). In this study we have used the newly developed direct estimation approach (Beh and Davy, 2004 and Zafar et al., 2015) to estimate the linear-by-linear association in two-way tables, within the framework of ordinal log-linear models (OLLMs), with the aim of analysing associations between the TCIs and SCLs. Two non-iterative estimators were considered for this study the Beh-Davy non-iterative estimator (BDNI) (Beh and Davy, 2004) and the Log non-iterative estimator (LogNI) (Beh and Farver, 2009). The BDNI and LogNI estimation methods provide closed-form estimators which do not require iteration to estimate the linear-by-linear association parameter of OLLMs, unlike their conventional and iterative counter parts, such as the Newton-Raphson and the iterative proportional fitting methods. The estimates obtained from the BDNI and LogNI estimation methods are reported, for pairwise relationships between TCIs and symptoms, along with the standard errors and p-values for males and females for pre and post treatment. Both estimators, BDNI and LogNI, provide estimates which are close to each other. We found significant changing relationships between the seven TCIs and psychological distress symptoms across gender for NS and P post treatment; with both TCIs and SCLs dicho
Subjects Statistics not elsewhere classified
Keyword(s) ordinal log-linear model
non-iterative estimation
linear-by-linear association
temperament and character traits inventory (TCI)
symptom check
ISBN 9780987214355
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