We applied uniform diagnostic procedures to the male veterans from the NVVRS and VES to estimate PTSD prevalences based on varying criteria including one-month and lifetime prevalence estimates, combat and non-combat prevalence estimates, and prevalence estimates using both single and multiple indicator models.
[ 72] The Institute of Medicine has recently been charged with reviewing the previous literature and recommending a reliable measure of PTSD for Gulf War veterans.[ 94] In general, single indicator models of psychological constructs are considered to be both less reliable and less valid measures compared to multiple indicator models.
While all associations but one were statistically significant in single indicator models, when entered into a multiple indicator model only some associations remained significant.
During psychometric development or selection of a Patient Reported Outcome measure it is necessary to determine which, of the five types of measurement models, the measure is based on; 1) a Multiple Effect Indicator model, 2) a Multiple Cause Indicator model, 3) a Single Item Effect Indicator model, 4) a Single Item Cause Indicator model, or 5) a Mixed Multiple Indicator model.
To our knowledge, this is the first study to demonstrate an association between ID and blood Cd in children in the U.S. We used the multiple indicator ferritin model to determine iron status, which takes into account the levels of three iron indicators: SF, FEP, and TSAT.
Therefore, models composed of these two components represent a multiple cause indicator model rather than a multiple effect indicator [ 21], as the items of this model are not interchangeable and thus have a weak correlation.
In the second stage of the analysis, the selected measurement model was combined with a set of observed covariates as well as external validation criteria in order to jointly estimate the external validity of the scale in a full structural model, thus extending the measurement model to a Multiple Causes Multiple Indicators (MIMIC) model.
CFA-OCM appropriately models the categorical nature of the items[ 60] and falls within a larger family of latent variable measurement modeling approaches that includes: CFA for continuous measures, multiple indicator multiple cause (MIMIC) models, and item response theory models.
This study used data collected from two different adolescent samples at two different time periods in two different geographic regions in the USA to provide multiple indicators of model validity.
In SEM, a model of this nature is referred to as the Multiple Indicator Mult iple Causes (MIMIC) model [ 28].
Using the results from these analyses, we tested for the influence of blood lead on multiple outcomes using the Multiple Indicator Mult iple Causes (MIMIC) model under the umbrella of Structural Equations Modeling (SEM).
