Cross Lagged Panel Model (CLPM)
The cross-lagged panel model (CLPM) is a structural equation model for two or more variables measured over repeated waves that estimates how each variable predicts the other at the next wave, controlling for prior levels.
교차지연 패널모형(CLPM)은 여러 시점에 반복 측정된 둘 이상의 변수에 대해 이전 수준을 통제한 상태에서 각 변수가 다음 시점의 다른 변수를 예측하는 정도를 추정하는 구조방정식모형이다.
How do I test whether two variables influence each other over time in panel data?
패널 자료에서 두 변수가 시간에 따라 서로 영향을 주는지 어떻게 검정하나요?
The cross-lagged panel model estimates autoregressive paths for stability and cross-lagged paths for how earlier X predicts later Y and earlier Y predicts later X. It fits panel data with two or more waves, although the random-intercept version is preferred when stable between-person differences would bias within-person inferences.
When to use Cross Lagged Panel Model (CLPM)
- Two constructs measured on the same people at two or more waves
- Testing the direction of prediction between variables over time
- Comparing the relative strength of reciprocal lagged effects
When to use something else
- Stable trait-like differences between people may confound lagged effects: use the random-intercept cross-lagged panel model (RI-CLPM)
- Interest is in individual trajectories of a single variable: use latent growth modeling
Assumptions and requirements
- At least two measurement waves of each variable
- Equal or meaningful time intervals between waves
- No unmeasured time-varying confounders
- Multivariate normality or a robust estimator
What the analysis reports
- Autoregressive and cross-lagged path coefficients
- Within-wave correlations
- Fit indices (CFI, TLI, RMSEA, SRMR)
- Tests of equality constraints across waves
- Path diagram
How to report it
[X] at Time 1 significantly predicted [Y] at Time 2 after controlling for prior [Y], β = [value], p = [value], whereas the reverse path was not significant, β = [value], p = [value].
Related methods
- Random Intercept Cross Lagged Panel Model (RI-CLPM)
- Latent Growth Modeling (LGM)
- Structural Equation Modeling (SEM)
Run Cross Lagged Panel Model (CLPM) on Quorant
- Data you need
- a table (CSV or Excel) with item columns (e.g. questionnaire items) and predictor (feature) columns
- Price
- 400 credits for one analysis up to 10,000 rows (complexity level 3); larger or wider data costs more. Optional methodologist review: 1800 credits.
- Checking
- Python results are cross-checked against R reference outputs in every deployment
- Before you pay
- A free pre-analysis diagnosis checks your data and gives an exact quote; nothing is deducted until you approve it.