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Interpreting Confidence Intervals

Child Health Assessment and Monitoring Program (CHAMP)

The prevalence rates reported from N.C. CHAMP estimate the percent of the North Carolina population of children who exhibit certain health behaviors or characteristics. Since the estimates are based on a sample and not the entire population, the percentage of children in the survey with a given health characteristic may differ from the “true” prevalence of that characteristic in the North Carolina population simply by chance. Confidence intervals take this error into account and present a range in which the “true value” is likely to fall. For example, based on the 2007 CHAMP survey between 14.0 percent and 17.5 percent of children in North Carolina have ever had asthma, with a point estimate of 15.7 percent.

2007 North Carolina Statewide CHAMP Survey Results
Has a doctor ever told you that (CHILD) has asthma?***

  Total Respond.^ Yes No
N % C.I.(95%) N % C.I.(95%)
TOTAL 2,573 414 15.7 14.0-17.5 2,159 84.3 82.5-86.0
Male 1,274 237 17.5 15.1-20.2 1,037 82.5 79.8-84.9
Female 1,299 177 13.7 11.5-16.3 1,122 86.3 83.7-88.5
White 1,884 293 14.5 12.6-16.6 1,591 85.5 83.4-87.4
African American 378 88 23.2 18.6-28.5 290 76.8 71.5-81.4
Other Minorities 311 33 8.4 5.5-12.6 278 91.6 87.4-94.5
Yes 231 14 7.1 3.8-12.7 217 92.9 87.3-96.2
No 2.338 399 16.7 14.9-18.7 1,939 83.3 81.3-85.1

The width of the confidence interval is influenced both by the degree of certainty sought (e.g., 95 percent versus 99 percent certainty) and the standard error. A high degree of certainty (e.g., 99 percent) increases the width of the confidence interval. Sample size will also influence the width of the confidence interval, with small samples increasing the width of the confidence interval, as well.

The confidence interval also tells you about the reliability of the point estimate. A reliable estimate is one that would be close to the same value if the survey were repeated and another sample was obtained. A wider confidence interval around the estimate indicates less reliability. On the other hand, narrow confidence intervals tell you that the point estimate is reliable, i.e., repeated CHAMP surveys would give approximately the same results. In 2007, the asthma rate for white children was 14.5 percent, with the range of the confidence interval from 12.6 to 16.6 percent. The upper and lower range of the confidence interval are fairly close, therefore this is a somewhat reliable point estimate.

When comparing two point estimates, can I use confidence intervals to determine if the difference is statistically significant?

No. The overlap of the confidence intervals of two estimates is not a reliable way to determine statistical significance. When the confidence intervals of two estimates of the same indicator from different groups do not overlap, the difference between the estimates is statistically significant. However, when confidence intervals do overlap, the difference may or may not be statistically significant.

A formal test of statistical significance is necessary to determine if the difference between two proportions is statistically significant. Software that can account for the complex sampling design (SUDAAN or the SAS Survey suite) should be used for the significance test.