Sentence examples for log of costs from inspiring English sources

It is common to use linear regression models for the log of costs in healthcare expenditures.

The dependent variable was the log of costs rather than the actual costs because the costs were not distributed normally.

Patient's costs were estimated using a two-part model: (1) a logistic regression for whether patients had any costs; (2) a least squares regression for the log of costs for patient-years with at least some costs.

Results from ordinary least squares, stepwise regressions controlling for age, sex, region, insurance type, and comorbidities (hypertension, hyperlipidemia, cardiovascular disease, ischemic heart disease, and obesity) using log of costs as the dependent variable.

Due to its non-normal distribution, the natural log of cost was used as the dependent variable [ 32, 33].

The predicted log of cost per bed day, ln, can then be calculated from: where and are the estimated parameters, and X i.. n are the independent variables.

This is consistent with published national reports on the average cost-to-charge ratio for the USA such as that published by the United States General Accounting Office (63%) [ 69]. Figure 1 shows the three regression lines of levels one, two and three hospitals, respectively, plotted against the log of GDP per capita (the Y-axis is log of cost per bed-day).

From the tradition of using cost functions to explain observed variations in unit costs, we estimate a long-run cost-function by means of Ordinary Least Squares regression analysis (OLS); the dependent variable is the natural log of cost per bed-day [ 2, 3, 6- 8, 65].

The logs of costs were used as the dependent variable in order to account for the skewed nature of cost data.

[ 21] Alternatively, a natural log transformation of costs is also possible.

When we examined the costs between groups using stepwise logarithmic regression and the log of total costs as the dependent variable, (Table 2) we see that that celiac patients have substantially increased costs compared to that of the control group.