title: Pivot tables for mortality analysis, or who needs life tables anyway?
abstract: Actuarial life-table analysis has long been used by life insurance medical directors for mortality abstraction from clinical studies. Ironically, today's life actuary instead uses pivot tables to analyze mortality. Pivot tables (a feature/function in MS Excel) collapse various dimensions of data that were previously arranged in an "experience study" format. Summary statistics such as actual deaths, actual and expected mortality (usually measured in dollars), and calculated results such as actual to expected ratios, are then displayed in a 2-dimensional grid. The same analytic process, excluding the dollar focus, can be used for clinical mortality studies. For raw survival data, especially large datasets, this combination of experience study data and pivot tables has clear advantages over life-table analysis in both accuracy and flexibility. Using the SEER breast cancer data, we compare the results of life-table analysis and pivot-table analysis.
authors.affiliation: Transamerica Reinsurance, 401 North Tryon Street, Suite 700, Charlotte, NC 28202, USA. david.wesley.md@transamerica.com
authors.forename: David
authors.initials: D
authors.lastname: Wesley
authors.forename: Hugh F
authors.initials: HF
authors.lastname: Cox
mesh_terms: D000206:Actuarial Analysis / Q000379:methods*; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001943:Breast Neoplasms / Q000145:classification / Q000401:mortality; D005260:Female; D006801:Humans; D007352:Insurance, Life; D015993:Life Tables; D008875:Middle Aged; D009026:Mortality; D018426:SEER Program; D014481:United States / Q000453:epidemiology