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The sample composition of the 15,501 individuals is shown in Table 1. Predisposing variables were age, gender, race, ethnicity, education, marital status, region of residence, and MSA (Metropolitan Statistical Area) status. For need variables, individuals'' general health status was used. Family poverty level and insurance status were included as enabling factors. Having insurance was defined as having coverage for physician and hospital services. Insurance status was grouped into: no insurance for 12 months, insured for 1-11 months, insured for 12 months by different types of plans, and insured for 12 months by the same plan. The probabilities of having no usual source of care, having a regular doctor, and having a regular site in the first stage were estimated by a multinomial logit model. In the selection stage, a reduced-form estimation was employed. The probabilities of having no usual source of care, a regular doctor, and a regular site were predicted for each individual. These probabilities were then transformed into the endogeneity correction terms. Whether an individual had children and the total number of conditions the children had were included as two additional exogenous variables appearing only in the selection stage. To test the presence of selection biases, an adjusted Wald test was performed for each service on the endogeneity correction terms, the [lambda]''s. The unbiased effects of having a regular doctor and a site were then calculated based on the parameter estimates. The differences in the effects of having a regular doctor and having a regular site on the five preventive services were obtained. Tests were conducted to determine whether the differences were statistically significant. The biased effects obtained through single-equation estimations were also examined.RESULTSTable 2 presents the cross-tabulation of the type of usual source of care and preventive service use. Among the 15,501 individuals, about 23 percent did not have a usual source of care, whereas approximately 44 percent had a regular doctor and one third had a regular site. Persons without a usual source of care had a lower proportion than individuals who had a usual source of care in receiving prevention within the past two years, a result that was significant at a 99 percent confidence level for all five preventive services. When the comparison was made between having a regular doctor and having a regular site, it was found that a regular doctor outperformed a regular site in providing blood pressure checks, cholesterol level checkups, and flu shots. However, a regular site outperformed a regular doctor in providing pap smears. These findings were significant at a 99 percent confidence level. No statistically significant difference was found between having a regular site and having a regular doctor in receiv ing mammograms. Adjusted Wald tests (F tests) were used to evaluate the joint performance of the additional two exogenous variables identifying the equation. In predicting the probabilities of having a regular doctor and having a regular site, the F test scores were 11.92 and 12.55, respectively. They were significant at a 99 percent confidence level. Table 3 shows the selected parameter estimates from the second-stage estimation. As discussed, the adjusted Wald tests of whether the coefficients of the [lambda]''s were zero were the tests for the endogeneity of having a regular doctor or site. The last column of Table 3 reports the result of the joint tests. The endogeneity of having a regular doctor or site was present for flu shots, blood pressure checkups, and cholesterol level checkups. No selection biases were found in the equations of pap smears or mammograms within the past two years.As described before, the effects of having a regular doctor ([I.sub.d]) and having a regular site ([I.sub.s]) conditional on the choice of a usual source of care are [gamma]1 + ([[alpha].sub.d][[lambda].sub.d] - [[alpha].sub.0][[lambda].sub.0]) barrow and [gamma]2 + ([[alpha].sub.s][[lambda].sub.s] - [[alpha].sub.0][[lambda].sub.0]), respectively. These two effects are show in Table 4. Marginal effects of having a regular doctor and a regular site on the probabilities of receiving preventive services were reported. The [lambda]''s were calculated for each individual based on the predicted probabilities from the first-stage estimation. Because the [lambda]''s vary by individuals, the averages of the [lambda]''s were used in calculating the marginal effects.
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