Since previous research indicates that neurocognitive deficits contribute to theory of mind impairment which, in turn, associates with negative symptoms (in accord with our zero-order correlation results), we conducted follow-up hierarchical regression analyses to examine the cumulative effects of these measures when predicting patients' social functioning and quality of life.
In order to do so, we conducted comparative tests between simulated data and real data with corresponding geometries.
In order to reduce bias, we conducted our searches independently, in duplicate.
In order to demonstrate this, we conducted a simple diffusion-only numerical experiment, described in detail in Additional file 6.
In order to ensure fairness, we conducted a k-fold cross-validation analysis for each of the C-gamma tuples.
In order to detect SDs, we conducted self-plot analysis using genome sequence data (Jul. 2007 assembly of the mouse genome, mm9, NCBI Build37).
In order to overcome this we conducted an additional more complex analysis, including interactions between the specific cardiovascular conditions and the cardiovascular medicine count.
In order to do this, we conducted a series of secondary analyses of data from a randomized controlled trial of personality disorder psychoeducation for substance use disorders.
In order to maximize power, we conducted interaction analyses in the relevant 2 W follow-up samples, which had the smallest amount of missing data, and used the corresponding linear regression model (described above).
In order to accomplish this, we conducted a field survey in southern Spain to examine leaf damage, plant size and trichome density and compare these characters with Mexican populations.
