Freeman D H, Freeman J L, Koch G G, Brock D B
Am J Public Health. 1976 Oct;66(10):979-83. doi: 10.2105/ajph.66.10.979.
A generalization of ordinary least squares methods is used in the analysis of physician visit data from a complex sample survey. The emphasis, in this paper, is on the valid substantive inferences to be drawn from an analysis of this type of data. The procedure is found to be useful in two ways. First, the resultion on a national basis. It is concluded that age is an imp-s of a comparative sampling study are reported. Second, the procedure is used to remove statistically non-significant variation from the data in order to generate fitted or smoothed estimates on which the substantive analyst may focus his attention. These fitted values are then examined for implications to physician service utilization on a national basis. It is concluded that age is an important variable while the effect of sex and race depends on age. Similarly, residence and income are important but the effect of education depends on the level of income.
普通最小二乘法的一种推广方法被用于分析来自复杂样本调查的医生就诊数据。本文重点在于从这类数据分析中得出有效的实质性推断。该程序在两个方面很有用。首先,报告了基于全国范围的比较抽样研究结果。得出的结论是年龄是一个重要因素。其次,该程序用于去除数据中统计上不显著的变异,以便生成拟合或平滑估计值,让实质性分析人员能够将注意力集中在这些估计值上。然后在全国范围内检查这些拟合值对医生服务利用的影响。得出的结论是年龄是一个重要变量,而性别和种族的影响取决于年龄。同样,居住地区和收入很重要,但教育程度的影响取决于收入水平。