In contrast to imputation, FIML directly estimates all parameters using all available data (Enders, 2001; Enders and Bandalos, 2001) and, in the case of an unconditional mixture model, is based on the assumption that missing data are missing at random (MAR) conditional on the observed repeated measures data.
An important characteristic of IRT models is that they describe reliability, in terms of measurement precision, as a continuous function that is conditional on the values of the measured construct.
A DIF analysis allows to examine the relationship between item responses and another variable, such as gender or age group, conditional on a measure of the latent construct, i.e. vision-related quality-of-life [ 28].
Comparisons of sexual health between intervention and control groups will include the baseline value of each outcome as subject level explanatory variables, so that analysis is of the difference in end point conditional on the within-subject baseline measure.
Indeed, Card et al. (2007) posit that the effect of potential benefits duration on the unemployment exit rate is conditional on the way the researcher measures the end-of-benefit spike phenomenon.
However, the increase in yield with changing planting date and fertilizer application under climate change scenarios is conditional on the use of other measures, such as adjusted irrigation and crop protection, to enable realization of potential yield increases.
Introducing a sunset clause conditional on the proposed EU permanent measures, whereby the DST is due to lapse with the adoption of proposals for a digital significant presence or the CCCTB including the European Parliament position on digital permanent establishment.
Denote, the random conditional entropy of relative to on the measure, that is, (2.1).
Conditional on the obvious limitation that we cannot measure the absolute amount of false science in circulation, these results support the view that distributed governance systems can be designed to uncover false knowledge relatively swiftly and to mitigate the costs that false knowledge for future generations of producers.
Mellenberg (1989) defined measurement invariance (MI) with respect to group as an identical distribution of the observed sum score, conditional on the disorder that the test measures, across groups.
The primary dilemma for examining exposure data with this time-varying structure is how to account for the longitudinal features of the exposure trajectory in a final disease risk model with the binary outcome, conditional on the complete set of exposure measures.
