Results 151 to 160 of about 24,426,264 (165)

Applied Longitudinal Data Analysis

, 2003
PART I 1. A framework for investigating change over time 2. Exploring Longitudinal Data on Change 3. Introducing the multilevel model for change 4. Doing data analysis with the multilevel mode for change 5. Treating TIME more flexibly 6.
J. Singer, J. Willett
semanticscholar   +1 more source

A primer on two-level dynamic structural equation models for intensive longitudinal data in Mplus.

Psychological methods, 2019
Technological advances have led to an increase in intensive longitudinal data and the statistical literature on modeling such data is rapidly expanding, as are software capabilities.
Daniel M. McNeish, E. Hamaker
semanticscholar   +1 more source

When Should We Use Unit Fixed Effects Regression Models for Causal Inference with Longitudinal Data?

American Journal of Political Science, 2019
Many researchers use unit fixed effects regression models as their default methods for causal inference with longitudinal data. We show that the ability of these models to adjust for unobserved time‐invariant confounders comes at the expense of dynamic ...
K. Imai, In Song Kim
semanticscholar   +1 more source

Testing mediational models with longitudinal data: questions and tips in the use of structural equation modeling.

Journal of Abnormal Psychology, 2003
R. M. Baron and D. A. Kenny (1986; see record 1987-13085-001) provided clarion conceptual and methodological guidelines for testing mediational models with cross-sectional data.
D. Cole, S. Maxwell
semanticscholar   +1 more source

Comparison of Models for the Analysis of Intensive Longitudinal Data

Structural Equation Modeling: A Multidisciplinary Journal, 2019
We discuss the differences between several intensive longitudinal data models. The dynamic structural equation model (DSEM), the residual dynamic structural equation model (RDSEM) and the repeated measures longitudinal model are compared in several ...
T. Asparouhov, B. Muthén
semanticscholar   +1 more source

A tale of two effects: Using longitudinal data to compare within‐ and between‐firm effects

, 2017
Research Summary We investigate the theoretical and empirical implications of longitudinal data in strategy research. Theoretically, longitudinal data allow strategy researchers to distinguish between relationships among constructs within versus between
S. Certo, Michael C. Withers, Matthew Semadeni   +2 more
semanticscholar   +1 more source

Latent variable modeling of differences and changes with longitudinal data.

Annual Review of Psychology, 2009
This review considers a common question in data analysis: What is the most useful way to analyze longitudinal repeated measures data? We discuss some contemporary forms of structural equation models (SEMs) based on the inclusion of latent variables.
J. Mcardle
semanticscholar   +1 more source

On disaggregating between-person and within-person effects with longitudinal data using multilevel models.

Psychological methods, 2015
This article extends current discussion of how to disaggregate between-person and within-person effects with longitudinal data using multilevel models. Our main focus is on the 2 issues of centering and detrending.
Lijuan Wang, S. Maxwell
semanticscholar   +1 more source

Longitudinal Data

Handbook of Statistical Methods for Randomized Controlled Trials, 2021
Soeun Kim, Myunghee Cho Paik
semanticscholar   +2 more sources

Analysis of longitudinal data

British Journal of Psychiatry, 1998
B. Everitt
semanticscholar   +1 more source