Past meetings

-11/01/2011:‘Dutch Mplus user’s group: Exploring the boundaries of Mplus’ 

-10/31/2011:‘Pre-conference workshop: How to deal with missing data: your second course'

-03/14/2011:‘Dutch Mplus user’s group: Exploring the boundaries of Mplus’

-10/27/2010: ‘Dutch Mplus user’s group: Exploring the boundaries of Mplus’


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The third Mplus meeting was organized on November 1st. 2011 at Utrecht University. 

The following presentations were given (including the PDF-files of the presentations):
 

Key-note presentation (Prof. Craig Enders) (pdf)

Part I on How to deal with non-ignorable missing data analyses 
 

An example of Alcohol use of groups of youngsters in groups of countries. A comparative study of underage drinking in 25 European countries of an Exploratory Structural Equation Model (dr. Harrie Jonkman) (pdf)

Underage drinking is a major societal problem, especially in Europe. The main objective of this multilevel class analysis is to assess patterns of alcohol use among groups of youngsters in groups of European countries (N=25, n=57.224), to associate this with risk factors in their daily life and to set up targeted prevention on a larger scale in a later phase more successfully.
Alcohol use of groups of youngsters in groups of countries. Multilevel latent class analysis of underage drinking in Europe. 
 

The Effect of Multicollinearity on Two-Level Confirmatory Factor Analysis (Drs. Seda Can) (pdf)  

This simulation study investigates the effect of between level collinearity in Multilevel Structural Eqution Modeling. It also compares two of the estimation methods (ML and Bayesian Estimation) used in Mplus. 

 

How to deal with attrition and drop-out (Drs. Peter Lugtig) (pdf)

 

An example of developmental trajectories of psychotic experiences in adolescents (Drs. Hanneke Wigman) (pdf)

For most individuals, these experiences are transitory; in a minority, however, these experiences may develop into clinical psychotic disorder. Using growth mixture modeling, different developmental trajectories of such experiences are studied in a large adolescent general population sample (N=2230).


Power analyses in complex SEM models (Dr. Mirjam Moerbeek) (pdf)

 

Keynote on MplusAutomation  (Dr. Michael Hallquist) (pdf)

Topic of the presentation is on how to run simulation studies in Mplus and why R might be useful

 

Multivariate Growth Curve Modeling; Challenges and Some Practical Solutions (dr. Loes Keijsers) (pdf)

 

An Example of The use of multiple-group analysis to test the stability of a model over time (Dr. Judith Schoonenboom and drs. Jeroen van Andel)
Based on a questionnaire among students of a Dutch university of professional education (N= 952), a multilevel model was set-up of both personal and institutional factors that influence the rationality and autonomy of these students’ choices in demand-driven education. This presentation demonstrates the use of multiple-group analysis to investigate the stability of the model over a periode of two years, which includes four measurements.

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On Monday, October 31st there was a Pre-conference workshop:How to deal with missing data: your second course   

- Presentation on full information maximum likelihood by prof. Craig (Enders Arizona State University, USA) (pdf)

- Presentation with an introduction to the R-package mice, an open-source tool for flexibly imputing incomplete data by prof. Stef van Buuren (utrecht University, The Netherlands) (pdf)

- Workshop by Gerko Vink (utrecht University, The Netherlands) on the use of Mice in combination with Mplus.


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-On Monday, March 14th  the second meeting of the ‘Dutch Mplus user’s group: Exploring the boundaries of Mplus’ took place at Utrecht University, The Netherlands. 

For a list of participants, click here.

The following presentations were given (including a link the the powerpoint presentations):

 

Key-note presentation (dr. Jan Boom)  

Latent Growth Mixture Modelling:

 

Smart applications of Growth Modeling in Mplus:
1) Evaluation of an intervention program in a longitudinal framework without the need for a control group (ppt).
2) Modeling the overlapping waves model of development as a linear growth model for a categorical outcome(ppt).
3)remaining issues, questions and answers (ppt). 


An example of an Exploratory Structural Equation Model (dr. Mirjam van Zuiden) (ppt)

Exploratory Structural Equation Modeling (ESEM) with target rotation in longitudinal psychobiological research in the military.

 


Multiple group analysis in Mplus and Lavaan: (Yves Rossel) (ppt)

The presentation will focus on how to specify multi group models and how to test for measurement invariance? Furthermore, it will be shown what the defaults of Mplus are, and whether these defaults are useful or not (e.g. parameter constraints, meanstructure). The issue of defaults behind the scene of mutigroup analyses refers to a more general issue of Mplus: there are many constraints used in the background of the software, but how to recognize these defaults and how to override them. An alternative program is Lavaan where measurement invariance can easily be tested


Imputing Data: Why you should and how you could (Gerko Vink) (ppt)

What to do with missing data: FIML, single/multiple imputation. 


Handling missing data in calculating the AIC (Rebecca Kuiper) (ppt)
What does Mplus do wrong?


Drifting apart or bonding together? Changes in parent-adult child relationships as the older generation ages into age old. An example of Latent Transition Analysis in Mplus  (Martijn Hogerbrugge) (ppt)

Although the topic of intergenerational relations and support has been investigated previously,two major challenges remain unsolved. First, intergenerational relations have been investigated predominantly in a rather static way, mainly caused by the studies’ reliance on cross-sectional data. Second, previous studies have often selected only one or two dimensions of intergenerational relations in its research. Fortunately, latent transition analysis (LTA) offers a methodological solution for handling the complexity of intergenerational relations, while allowing the researcher to model transitions into different family types between time points. In this study, we will conduct LTA on panel data from the Longitudinal Study of Generations (LSOG), spanning a total of 17 years.


Seeking convergence (Peter Lugtig) (ppt)

Computing the parameter estimates in a SE-Model in Mplus requires finding the the minimum of a loglikelihood function, that indicates the difference between the observed (S) and model implied (sigma) covariance matrices. MPLUS often has difficulties finding this mimnimum (or seeking convergence). This presentation will start with a short introduction in convergence algorithms. Then, we will discuss some situations in which convergence is difficult, and why this is the case. We will conclude with some suggestions for MPLUS model inputs that often ameliorate convergence problems.  

 

 

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-On October the 27th (9.00 a.m.- 4.30 p.m.) the first meeting of the ‘Dutch Mplus user’s group: Exploring the boundaries of Mplus’ took place at Utrecht University.

 

 

For a list of participants, click here.

 

The following presentations were given (including a link the the powerpoint presentations):

 

 

 

 

  •  Short problem presentations (10 min.)
    • Didi Rhebergen (seeking convergence I)
    • Thomas Scotto (seeking convergence II)
    • Thessa Wong (missing data in recall events) (ppt)

 

  •  (New) features in MPLUS 
    • Peter Lugtig- ESEM: apart from confirmatory analyses, Mplus features the possibility to do Exploratory Structural Equation Modeling. The possibilities and benefits are illustrated with factor analysis models.(ppt) 
    • Maartje van Stralen - How to conduct mediation analyses in Mplus using the MODEL INDIRECT command
    • Rens van de Schoot - How to deal with inequality constraints between regression coefficients in Mplus (MODEL CONSTRAINT) using the parametric bootstrap procedure (MONTECARLO). (ppt)

 

 

  •  Modeling issues in Mplus
    • Daniel Oberski (Detection of misspecifications in Mplus by using modification indices, expected parameter change and the power of the test for stepwise improvement of the model)
    • Yves Rosseel (MLR-MLM estimators) (20 min.)
    • Margot Peeters (giving a metric to a latent variable

 

 

 


 

 

 

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