Causal cycles, causal intervals, and measurement in over-time studies
Year: 2024
Type: article
Abstract: If over-time data are used to model XàY causal relationships, the measurement (or “recording”) interval should match (or at least approximate) the actual causal (or “existence”) interval for X’s effect on Y. I discuss this issue in the context of causal cycles of events and give three examples involving hurricanes, job change and adoption and implementation of new technology. I conclude with some considerations and recommendations for matching measurement to causal intervals in over-time research.
Source: Group & Organization Management
Author: Charles E. Lance
Institution: University of the Western Cape
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,700
OpenAlex ID: W4401513333