Mean Spearman Correlation Coefficient Research Articles

Temporal stability of shallow soil water content for three adjacent transects on a hillslope

Identifying representative locations that estimate mean soil water content (SWC) for an area of interest is one of the most important applications of the concept of temporal stability but typically requires extensive sampling on multiple occasions. This study aimed to examine the feasibility of identifying temporally stable locations by using other properties (mainly soil) that were themselves relatively temporally stable, thus reducing the cost of sampling. From July 2008 to October 2010, SWCs at four soil depths (0.1, 0.2, 0.4 and 0.6m) were measured using a neutron probe on 20 occasions, along three transects (∼30 locations for each transect) on a hillslope of the Loess Plateau, China. Summary variables were determined at corresponding locations. The results showed good temporal patterns, with mean Spearman correlation coefficients ranging from 0.63 to 0.83 for the three transects at four soil depths. Identified representative locations for the three transects well-represented the mean SWC, with a root mean square error of less than 2% and a mean error of less than 1%. Elevation and clay content of soil were the main factors affecting the spatial and temporal distribution of soil water at the hillslope scale. However, the characteristics of temporal stability differed in part among the three transects, both in temporal persistence and in the number of representative locations. Multiple linear regression equations, determined between the mean relative difference and the measured variables based on the datasets of transects 1 and 2, did not accurately predict temporally stable locations for transect 3. The a priori selection of representative locations based solely on properties of soil and elevation was determined to be infeasible at the present time.

Validation of Tissue Microarray Technology in Ovarian Cancer: Results from the Nurses' Health Study

Tissue microarrays (TMAs) allow high-throughput evaluation of protein expression from archived tissue samples. We identified characteristics specific to ovarian cancer that may influence TMA interpretation. TMAs were constructed using triplicate core samples from 174 epithelial ovarian cancers. Stains for p53, Ki-67, estrogen receptor-alpha, progesterone receptor, Her-2, WT-1, cytokeratin 7, and cytokeratin 20 were evaluated by intraclass correlation coefficients, Spearman correlation coefficients, the effect of sample age, and tumor histology on the ability to score the cores, and inter-rater reliability. The interclass correlation coefficient and the mean Spearman correlation coefficients among 3 cores were > or = 0.91 and 0.87, respectively. Tissue age and tumor histology were not predictive of an inability to evaluate stains, but borderline tumors had a 2 to 4-fold increase in the risk of having uninterpretable cores over invasive tumors. There was moderate to substantial concordance between the two pathologists for estrogen receptor-alpha [Cohen's Kappa (kappa), 0.79] and Ki-67 (kappa, 0.52). The prevalence of positive staining cells by histologic type was comparable with previous studies. TMA is a valid method for evaluating antigen expression in invasive ovarian cancer but should be used with caution for borderline tumors. We suggest several methods of quality control based on intercore comparisons and show that some antigens may be affected by age of the samples.