Consequently, the statistical power of our quantitative results is limited by our qualitative approach to data collection and sampling, and we were unable to control for variables that might confound the relationships of interest.
We used a similar approach to data collection and the same sample (27 receiving combined support and 22 counselling support) as in the formative study.
The quality-rating criteria for peer-reviewed empirical articles included items pertaining to the methodological soundness of the study (e.g., clear description of the sample, systematic approach to data collection, valid and reliable measures, appropriate analyses and interpretation).
The continuous nature of the auditory stimulus and our data analysis techniques are not optimal for sparse sampling approaches to data acquisition, so the stimulus had to exceed scanner noise (see also above, due to non-specific auditory activation in sparse presentation).
The approach to sampling, data generation methods and data analysis are described below.
The algorithm combines the conveniences of deconvolution in Laplace domain with a new approach to transform sampled data from time domain to Laplace domain, which removes the necessity to extrapolate the data beyond the sampling interval imposed by Laplace transformation.
With this in mind we allocated some efforts to choose the ideal raw data sampling approaches.
Close-form equations are derived for normal and Laplace distributions, as well as a regression approach to deal with sampled data where no assumptions are made about symmetry.
In this study, we used a molecular phylogenetic approach of DNA sequence data, sampled from both the nuclear (ITS, ncpGS) and the plastid (trnL-trnF, trnK-matK, trnS-trnG, rbcL) genomes, to test the explicit hypothesis of adaptive radiation.
Four tracer approaches namely the frozen velocity approach, the snapshot approach, the data sampling approach and the transient approach, were compared.
