An analysis of physician visit data from a complex sample survey.
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.
D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D004522:Educational Status; D005006:Ethnicity; D005260:Female; D006801:Humans; D007182:Income; D008297:Male; D008875:Middle Aged; D010361:Patients; D010820:Physicians / Q000706:statistics & numerical data*; D012111:Residence Characteristics; D012737:Sex Factors; D013223:Statistics as Topic; D014481:United States