#### Filter Results:

#### Publication Year

2003

2016

#### Publication Type

#### Co-author

#### Publication Venue

#### Key Phrases

#### Method

#### Organism

Learn More

- Daniel J Bauer, Kristopher J Preacher, Karen M Gil
- Psychological methods
- 2006

The authors propose new procedures for evaluating direct, indirect, and total effects in multilevel models when all relevant variables are measured at Level 1 and all effects are random. Formulas are provided for the mean and variance of the indirect and total effects and for the sampling variances of the average indirect and total effects. Simulations show… (More)

- Daniel J Bauer, Patrick J Curran
- Psychological methods
- 2003

Growth mixture models are often used to determine if subgroups exist within the population that follow qualitatively distinct developmental trajectories. However, statistical theory developed for finite normal mixture models suggests that latent trajectory classes can be estimated even in the absence of population heterogeneity if the distribution of the… (More)

- Daniel J Bauer, Patrick J Curran
- Psychological methods
- 2004

Structural equation mixture modeling (SEMM) integrates continuous and discrete latent variable models. Drawing on prior research on the relationships between continuous and discrete latent variable models, the authors identify 3 conditions that may lead to the estimation of spurious latent classes in SEMM: misspecification of the structural model, nonnormal… (More)

- Daniel J Bauer, Patrick J Curran
- Multivariate behavioral research
- 2005

Many important research hypotheses concern conditional relations in which the effect of one predictor varies with the value of another. Such relations are commonly evaluated as multiplicative interactions and can be tested in both fixed- and random-effects regression. Often, these interactive effects must be further probed to fully explicate the nature of… (More)

- John R Hipp, Daniel J Bauer
- Psychological methods
- 2006

Finite mixture models are well known to have poorly behaved likelihood functions featuring singularities and multiple optima. Growth mixture models may suffer from fewer of these problems, potentially benefiting from the structure imposed on the estimated class means and covariances by the specified growth model. As demonstrated here, however, local… (More)

Psychologists are applying growth mixture models at an increasing rate. This article argues that most of these applications are unlikely to reproduce the underlying taxonic structure of the population. At a more fundamental level, in many cases there is probably no taxonic structure to be found. Latent growth classes then categorically approximate the true… (More)

- Daniel J Bauer, Sonya K Sterba, Denise Dion Hallfors
- Multivariate behavioral research
- 2008

Individually randomized treatments are often administered within a group setting. As a consequence, outcomes for treated individuals may be correlated due to provider effects, common experiences within the group, and/or informal processes of socialization. In contrast, it is often reasonable to regard outcomes for control participants as independent, given… (More)

The relations among several alternative parameterizations of the binary factor analysis model and the 2-parameter item response theory model are discussed. It is pointed out that different parameterizations of factor analysis model parameters can be transformed into item response model theory parameters, and general formulas are provided. Illustrative data… (More)

- Patrick J Curran, Daniel J Bauer, Michael T Willoughby
- Psychological methods
- 2004

A key strength of latent curve analysis (LCA) is the ability to model individual variability in rates of change as a function of 1 or more explanatory variables. The measurement of time plays a critical role because the explanatory variables multiplicatively interact with time in the prediction of the repeated measures. However, this interaction is not… (More)

- Daniel J Bauer, Andrea M Hussong
- Psychological methods
- 2009

When conducting an integrative analysis of data obtained from multiple independent studies, a fundamental problem is to establish commensurate measures for the constructs of interest. Fortunately, procedures for evaluating and establishing measurement equivalence across samples are well developed for the linear factor model and commonly used item response… (More)