Sampling behavior of cohort rates for recurrent events

Area of Science:

• Biostatistics
• Epidemiology
• Health Services Research

Background:

• Cohort rates are crucial for analyzing recurrent events in health services research.
• Accurate denominator calculation is essential for reliable rate estimation.
• High loss rates and long follow-up periods can complicate denominator calculations.

Purpose of the Study:

• To derive and illustrate large sample properties of cohort rates for recurrent events.
• To highlight the impact of denominator variation on precision estimates.
• To provide guidance for accurate statistical analysis in health services research.

Main Methods:

• Derivation of large sample properties for cohort rates.
• Computation of denominators using follow-up table quantities.
• Illustration using health services utilization data.

Main Results:

• Cohort rates derived from follow-up table quantities provide insights into recurrent event patterns.
• Ignoring denominator variation leads to inaccurate precision estimates, particularly under high loss rates and long follow-up durations.
• The study quantifies the potential for inaccuracy in precision estimation.

Conclusions:

• Properly accounting for denominator variation is critical for precise cohort rate estimation.
• Health services researchers must consider denominator dynamics to avoid biased precision estimates.
• The findings emphasize the importance of robust statistical methods in analyzing longitudinal health data.