Longitudinal Data Analysis Service | LGM, CLPM, RI-CLPM

We model change over time with repeated measures, latent growth models and cross-lagged panel designs, and test longitudinal measurement invariance first.

Longitudinal data violate the assumptions of ordinary regression, and analysing waves with cross-sectional methods is one of the most common methodological objections raised in review.

We begin by testing whether you are measuring the same construct at each wave; without longitudinal invariance, comparing waves is not interpretable. We then fit the model your question requires — a latent growth model where the question is about trajectory, a cross-lagged panel model where it is about reciprocal prediction, and the random-intercept version where the question is genuinely within-person.

Where both a CLPM and an RI-CLPM are defensible we fit both and discuss the difference, which is a strong position to be in during review.

Models We Fit

Latent growth models (LGM)

Intercept and slope factors, non-linear trajectories and predictors of change.

CLPM and RI-CLPM

Cross-lagged prediction, with stable individual differences separated out where the question is within-person.

Longitudinal invariance

Configural, metric and scalar invariance across waves before any comparison is made.

How the Process Works

Initial assessmentYou share your research question, your dataset and your target journal. Together we decide which analysis is appropriate.
Proposal and planScope, timeline and fee are agreed, and what you will receive is set out in writing.
AnalysisAssumption checks, model specification and estimation, with interim findings shared with you.
Delivery and handoverAPA-format tables, a written interpretation and a handover conversation. We do not request authorship for standard analysis work.