Alternative adjustment for seasonality and long-term time-trend in time-series analysis for long-term environmental exposures and disease counts.

ABSTRACT:

Background

Time-series analysis with case-only data is a prominent method for the effect of environmental determinants on disease events in environmental epidemiology. In this analysis, adjustment for seasonality and long-term time-trend is crucial to obtain valid findings. When applying this analysis for long-term exposure (e.g., months, years) of which effects are usually studied via survival analysis with individual-level longitudinal data, unlike its application for short-term exposure (e.g., days, weeks), a standard adjustment method for seasonality and long-term time-trend can extremely inflate standard error of coefficient estimates of the effects. Given that individual-level longitudinal data are difficult to construct and often available to limited populations, if this inf

SUBMITTER: Kim H 

PROVIDER: S-EPMC7780665 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature