DATA ANALYSIS

You’ve got the data, now what?

RECOMMENDED READING

Learn about basic research methods used by personality psychologists, different types of longitudinal models, and how to conduct integrative data analyses across studies.

SYNTAX LIBRARY

Choose a model to suit your research question(s), and get started with syntax. Resources and code available for Mplus and R / lavaan.

RECOMMENDED READING

Research Methods

Looking for some background on the research methods and analytic tools personality psychologists use? Below is a link that will take you to chapters that cover topics such as: conducting a longitudinal study; using archival data; reliability and validity; moderator, mediator, and suppressor effects; factor analyses; structural equation modeling; idiographic analysis; meta-analysis; and more!

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RECOMMENDED READING

Longitudinal Models

To answer your research questions about personality development, you need to select an appropriate longitudinal model. Below are some recommended readings that provide more details about different longitudinal models, as well as examples of how these models are used in practice in personality development research.

Auto-Regressive Latent Trajectory Model (ALT)
Curve of Factors Model (CUFFS)
Factor of Curves Model (FOCUS)
Individual Change
Latent Change Score Model (LCS)
Latent Curve Model with Structured Residuals (LCM-SR)
Latent Growth Curve Model (LGC)
Measurement Invariance
Random-Intercept Cross-Lagged Panel Model (RI-CLPM)
Traditional Cross-Lagged Panel Model (CLPM)
Trait-State-Error Model (STARTS)

RECOMMENDED READING

Integrative Data Analysis

Using data from multiple longitudinal studies requires some consideration of how to integrate (or coordinate) analyses across studies. Below are some readings that provide an overview of the integrative data analytic approach and some examples of how personality psychologists have done this in practice.

Photo by Marvin Meyer on Unsplash

Photo by Safar Safarov on Unsplash