For the cross-sectional data from 2009, the estimated mean (\(\bar{x}\)) is \(0.44\) with a standard error (\(SE\)) of \(0.08\). The confidence interval is calculated as follows:
\[
\bar{x} \pm z \frac{s}{\sqrt{n}} = 0.44 \pm 1.96 \cdot \frac{0.08}{\sqrt{5014}} = (0.44, 0.44)
\]
Thus, the confidence interval is:
\[
\text{Confidence Interval: } (0.44, 0.44)
\]
For the cross-sectional data from 2011, the estimated mean (\(\bar{x}\)) is \(0.54\) with a standard error (\(SE\)) of \(0.08\). The confidence interval is calculated as follows:
\[
\bar{x} \pm z \frac{s}{\sqrt{n}} = 0.54 \pm 1.96 \cdot \frac{0.08}{\sqrt{5014}} = (0.54, 0.54)
\]
Thus, the confidence interval is:
\[
\text{Confidence Interval: } (0.54, 0.54)
\]
For the longitudinal data, the estimated mean (\(\bar{x}\)) is \(0.17\) with a standard error (\(SE\)) of \(0.08\). The confidence interval is calculated as follows:
\[
\bar{x} \pm z \frac{s}{\sqrt{n}} = 0.17 \pm 1.96 \cdot \frac{0.08}{\sqrt{5014}} = (0.17, 0.17)
\]
Thus, the confidence interval is:
\[
\text{Confidence Interval: } (0.17, 0.17)
\]
For the baseline data, the estimated mean (\(\bar{x}\)) is \(0.07\) with a standard error (\(SE\)) of \(0.08\). The confidence interval is calculated as follows:
\[
\bar{x} \pm z \frac{s}{\sqrt{n}} = 0.07 \pm 1.96 \cdot \frac{0.08}{\sqrt{5014}} = (0.07, 0.07)
\]
Thus, the confidence interval is:
\[
\text{Confidence Interval: } (0.07, 0.07)
\]
The confidence intervals for the different models are as follows:
- Cross-sectional 2009: \((0.44, 0.44)\)
- Cross-sectional 2011: \((0.54, 0.54)\)
- Longitudinal: \((0.17, 0.17)\)
- Baseline: \((0.07, 0.07)\)
\[
\boxed{
\begin{align_}
\text{Cross-sectional 2009: } & (0.44, 0.44) \\
\text{Cross-sectional 2011: } & (0.54, 0.54) \\
\text{Longitudinal: } & (0.17, 0.17) \\
\text{Baseline: } & (0.07, 0.07)
\end{align_}
}
\]