Methods · Panel econometrics · Cross lagged panel

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)

When to use something else

Assumptions and requirements

What the analysis reports

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

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.

Method ID Q52001 · Reviewed 2026-10-25