[On the problems of fitting linear regression models for hierarchically structured data in medical research].
There are a large number of the hierarchically structured data in the field of medical sciences, which have been analyzed usually by conventional linear regression models. The objective of this paper is to explore the problems and the relationship of parameter estimates of the three common linear regression models in fitting the hierarchically structured date, and the correction of the precision of parameter estimates. It is shown that the estimate of parameter and it's precision of linear regression models is related to the variation of independent variable between and within level 2 units, and the difference of residual estimates is associated with the difference of parameter estimates. The three common linear regression models are all inappropriate for the hierarchically structured data, but the standard error of the level 1 combined model can be corrected by variance inflation factor in conditions.
Department of Health Statistics, School of Public Health, WCUMS, Chengdu 610041.
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D000704:Analysis of Variance; D015510:Clinical Medicine; D016000:Cluster Analysis; D006801:Humans; D016014:Linear Models; D012044:Regression Analysis; D012107:Research Design; D013223:Statistics as Topic