MTO Research Sandwich
Tuesday, February 16
PZ 43 at 12:45h
12:45h dr. Duygu Güngör Culha
(Dept. Methodology & Statistics, Tilburg
University and Faculty of Art and Sciences, Department of Psychology Izmir University).
‘Detecting Measurement Equivalence with Latent
Markov Models’
Measurement equivalence in longitudinal studies guarantees that the
same measurement instrument used in different time points measures exactly
the same construct. Some example studies with different latent variable models
include item response theory and latent growth models. However, testing
measurement equivalence with latent Markov models seems to be neglected;
many applications of latent Markov models assume measurement equivalence
or give little attention to this topic. When testing for inequivalent items with
nested models approach there are different alternative strategies. One question
to be answered is which data analytic technic should be used for the detection
of equivalence. In this talk, I will focus on free baseline and constrained
baseline strategies. When the baseline model is free model, we estimate a
model where all item response probabilities for all time points are free to vary.
The next step is to specify a series of models with one item restricted. On the
other hand, baseline model can be constrained model that all items are assumed
equivalent. Then, one can free items one-by-one to flag nonequivalent items.
In this simulation study, we explore overall performance of latent Markov
models in testing measurement equivalence using free baseline and constrained
baseline models. Our simulation conditions are related to sample size,
measurement strength, amount of inequivalence, number of inequivalent items,
and statistics used for model selection.