Empirical verification of confidence intervals computed from dental data

Area of Science:

• Dental epidemiology
• Statistical analysis

Background:

• Statistical assumptions are crucial for reliable data interpretation.
• Dental epidemiological data often exhibit skewed distributions.

Purpose of the Study:

• To investigate the impact of data skew on confidence intervals in dental epidemiology.
• To determine the influence of sample size on interval accuracy.

Main Methods:

• Conducted sampling experiments on five positively skewed dental epidemiological datasets.
• Analyzed the asymmetry and underestimation of nominal confidence intervals.

Main Results:

• Increased data skew led to greater underestimation and asymmetry in confidence intervals.
• Larger sample sizes mitigated these inaccuracies.
• Findings align with theoretical expectations regarding sampling distributions.

Conclusions:

• The normality assumption is critical for accurate sampling distributions in dental epidemiology.
• A method was developed to determine adequate sample size for reliable confidence intervals.