The extension to multivariate processes involves the derivation of the autocorrelation matrix from the marginal transforms, which determines the generating vector autoregressive process.
In the present study, we verified the usefulness of PFAA profiling for lung cancer detection using new independent samples that had never been used for previous analysis and a derivation of multivariate discriminating function(s) that could distinguish lung cancer patients from control subjects.
Based on results of the multivariate logistic models from the derivation data, two strategies for constructing the prediction model were applied.
The weighting of EDLIPS points was adjusted based on the multivariate logistic regression analysis in the derivation cohort of 2,000 randomly selected patients and was validated in the remaining (2,361) patients (Table 2).
In the 'Multivariate binomial process modeling and MLE derivation' section, the model of the process behavior is described and the MLEs of a step-change and a linear-trend disturbance are derived.
Based on the derivation group data, using multivariate analysis, a simple clinical risk scoring system was created using the clinical characteristics of maternal age, BMI, and race (Table 2).
Multivariate logistic regression models were then derived using the derivation set to develop a clinical prediction score for SBI.
Indeed, by using multivariate regression analysis and two different derivations with a national dataset, Attridge et al. found significant associations between early use of indomethacin and spontaneous intestinal perforation [ 22].
In a multivariate analysis of the single center LIPS derivation cohort, patients receiving anti-platelet therapy at the time of admission had significantly lower rates of developing ALI [ 44] (Table 2).
The crude assumption that the multivariate distribution is Gaussian is crucial in the derivation, whereas the unrealistic assumption that v j j ′ = 0 for j ≠ j ′ is made for simplicity.
