The inferences presented in this study are limited, however, by the observational and descriptive nature of this evidence.
Additional Poisson regression models were also tested in under the assumption that the outcome data represent counts, but the results do not change the inferences presented here.
This error rate is two orders of magnitude lower than the estimate of diversity in our samples, and not likely to influence the inferences presented here.
In addition, half of the data sets exhibited some level of publication bias, which could potentially weaken the inferences presented here.
The fact that the Andersen-Gill model applied in analysis controls for both interparticipant and intraparticipant variability in event rates and the associations between early PCP contact and healthcare service utilisation remained significant after adjustment for covariates and the conservative Bonferroni adjustment further strengthens the inferences presented here.
It certainly has not been significant enough to have confounded the phylogenetic inference presented by Laukaitis et al. (2008), and we feel that it should not adversely affect our analysis of recently duplicated products presented here.
An example is the post selection inference presented by Prof. Buja at the MCP 2013 conference, where the inference is valid for any selected regression model because it controls the FWER for all possible ones.
The method of network inference presented in this paper is inspired by the theory of time-lagged correlation inference with regard to the deduction of the interaction network, and on a maximum likelihood approach with regard to the estimation of the kinetic parameters of the network.
The results and inferences presented in this present study further suggest that prevalence and impact of organizational discrepancy should be included in future research on organizational issues.
In fact, the inference model presented in this paper is completely unsupervised.
