Causal Inference in Cross-Lagged Panel Analysis

Cross-lagged panel analysis (CLPA) is a method of examining one-way or reciprocal causal inference between longitudinally changing variables. It has been used in the social sciences for many years, but not much in nursing research. This article introduces the conceptual and statistical background of CLPA and provides an exemplar of CLPA that examines the reciprocal causal relationship between depression and cognitive function over time in older adults. The 2-year cross-lagged effects of depressive symptoms (Ti) on cognitive function (T2) and cognitive function (Ti) on depressive symptoms (T2) were significant, which demonstrated a reciprocal causal relationship between cognitive function and depressive mood over time. Although CLPA is a methodologically strong approach to examine the reciprocal causal inferences over time, it is necessary to consider potential sources of spuriousness to lead to false causal relationship and a reasonable time frame to detect the change of the variables.