Lord's Paradox Illustrated in Three-Wave Longitudinal Analyses: Cross Lagged Panel Models Versus Linear Latent Growth Models

Lord’s (1967) paradox showed that two basic ways to analyze change longitudinally can produce contradictory results in 2-occasion nonrandomized studies. This study extends that paradox to difference-score and ANCOVA-type residualized change score analyses across three waves of data for four corrective actions thought to be effective: corrective disciplinary actions by parents (timeout and reasoning) and corrective actions by professionals (psychotherapy and hospitalization). All significant findings indicated that these corrective actions were harmful according to cross-lagged panel models but beneficial according to linear latent growth models. One type of analysis may not generalize to the other type of analysis. These results are consistent with recent recognition that ANCOVA-type analyses are biased by invariant between-person differences, but difference-score analyses can have their own biases. Recognition of these biases is needed to discriminate between stronger and weaker causal evidence in longitudinal analyses.

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Journal
Journal of Behavioral Data Science
Published
2024-12-18
DOI
https://doi.org/10.35566/jbds/lin
Primary Topic
Psychological Well-being and Life Satisfaction
Type
article
Field-Weighted Citation Impact
0.00

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article

Lord's Paradox Illustrated in Three-Wave Longitudinal Analyses: Cross Lagged Panel Models Versus Linear Latent Growth Models

Hua Lin, Robert E. Larzelere
Journal of Behavioral Data Science
Psychological Well-being and Life Satisfaction
article

Lord's Paradox Illustrated in Three-Wave Longitudinal Analyses: Cross Lagged Panel Models Versus Linear Latent Growth Models

Hua Lin, Robert E. Larzelere
article en

Abstract

Lord’s (1967) paradox showed that two basic ways to analyze change longitudinally can produce contradictory results in 2-occasion nonrandomized studies. This study extends that paradox to difference-score and ANCOVA-type residualized change score analyses across three waves of data for four corrective actions thought to be effective: corrective disciplinary actions by parents (timeout and reasoning) and corrective actions by professionals (psychotherapy and hospitalization). All significant findings indicated that these corrective actions were harmful according to cross-lagged panel models but beneficial according to linear latent growth models. One type of analysis may not generalize to the other type of analysis. These results are consistent with recent recognition that ANCOVA-type analyses are biased by invariant between-person differences, but difference-score analyses can have their own biases. Recognition of these biases is needed to discriminate between stronger and weaker causal evidence in longitudinal analyses.

Journal of Behavioral Data ScienceVol. 4(2)
Oklahoma State University Oklahoma City (US)
National Institutes of Health
Reduced inequalities
Openalex Percentile: Top 69%
Psychological Well-being and Life Satisfaction
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Lord's Paradox Illustrated in Three-Wave Longitudinal Analyses: Cross Lagged Panel Models Versus Linear Latent Growth Models — Hua Lin, Robert E. Larzelere · Journal of Behavioral Data Science (2024) | TGRS Research Map | TGRS