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fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Kelly, Mark James
Languages: English
Types: Doctoral thesis
Subjects: R1
The investigation of associations between places, people and mental health is complicated and there are serious limitations in the current methodology. Using data from the Caerphilly Health and Social Needs Study (CHSNS), as well as the British Household Panel Survey, this thesis investigated some of these methodological issues. Firstly, motivated by the skewed distribution of the Mental Health Inventory (MHI-5), methods for analysing the mental health score were examined. Five methods for deriving a cutpoint on the MHI-5 based on linking with the General Health Questionnaire, were investigated and cutpoints derived for each. These outpoints and methods were compared and contrasted. When investigating associations between place and health, hierarchical modelling is an extremely useful tool. Sparse levels of information are a potential problem when using this method. In the CHSNS, households represent a sparse level of context. A simulation study was conducted to explore the effect of sparse levels on the results of hierarchical analyses. It was found that, in general, the underestimation of fixed effect standard errors is smaller when a sparse level is included than when it is excluded. Another methodological consideration for hierarchical modelling concerns the choice of geographical hierarchy to use. Administrative hierarchies have been criticised for being heterogeneous and arbitrary. An algorithm was developed to partition regions into areas that are homogenous with respect to a given set of variables, and was applied to Caerphilly county borough. The resulting sets of boundaries were compared with the 2001 census administrative boundaries. These new boundaries performed favourably in comparison with the administrative boundaries, indicating that administrative boundaries may not represent the most suitable hierarchy to employ in hierarchical analyses. The thesis has led to a greater understanding of the effects of context on multilevel analysis and contributed to the area-effects on health literature.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • 3 M easu rem en t o f m en tal h ealth sta tu s 3.1 Description of the S F - 3 6 ................................................................................. 3.2 Validity and R eliab ility .................................................................................... 3.2.1 V a l id i t y ................................................................................................... 3.2.2 R e lia b ility ................................................................................................ 3.3 Validity and reliability of the MHI-5 and the S F - 3 6 ............................... 3.3.1 V a l id i t y ...................................................................................................
    • 3.3.2 R e lia b ility ................................................................................................
    • 3.3.3 Suitability for Elderly P opulations.....................................................
    • 3.3.4 Version 1 versus Version 2 ..................................................................
    • 3.3.5 C o n c lu s io n s............................................................................................
    • 3.4.1 Box-cox tran sfo rm atio n .........................................................................
    • 3.4.2 Ordinal R e g re s s io n ...............................................................................
    • 3.4.3 Binomial M odelling ...............................................................................
    • 4 In tro d u ctio n to B ayesian M od ellin g 87 4.1 B a c k g ro u n d ........................................................................................................ 87 4.2 The Bayesian M ethod .................................................................................... 88 4.3 Estim ation of Bayesian Models........................................................................ 92 4.3.1 Monte Carlo Markov C h a in s ............................................................... 92 4.3.2 Metropolis-Hastings and Gibbss a m p lin g ......................................... 92 4.3.3 C onvergence....................... 93 4.4 Illustration of Bayesian M eth o d s.................................................................... 94 4.5 Spatial variation in cases of common m ental disorder in Caerphilly county b o r o u g h ...................................................................................................................101 4.6 C onclusion...............................................................................................................110
    • 5 H ierarchical M o d ellin g 111 5.1 Hierarchical m o d e ls .............................................................................................. I l l 5.2 Application of Hierarchical M o d e llin g ..............................................................116 A ndresen, E ., Bowley, N ., R othenber, B ., et al. (1996) Test-retest performance of a mailed version of the Medical Outcomes Study 36-item Short-Form Health Survey among older adults. Medical Care, 34, 1165-70.
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