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Table 10: 4-way Repeated Measures ANOVA for all data (Significant Interactions Only)
"... In PAGE 7: ... 3 Table 8: Regressions of single formant values and vocal tract length against mean body size ratings. Table 9: Formant Center Frequencies (CF) and Bandwidths (BW) used in Experiment 4 Table10 : 4-way Repeated Measures ANOVA for all data Table 11: Spearman Rank Correlation Coefficients for Piloerection Ratings vs. Lip Protrusion/Rounding Ratings for Each Rater Individually.... In PAGE 55: ... The instructions and rating task were the same in all other respects as that used in the first three experiments (again, the endpoints of the rating scale were not fixed). Experiment 4 Results Table10 shows the main effects and significant interactions for the 4-way repeated measures ANOVA used to analyze these data. As in the first two experiments, there was a clearly significant effect of both vocal tract length and fundamental frequency on body size judgments.... ..."
TABLE 1. BMD AND BONE ARCHITECTURAL PARAMETERS BEFORE AND AFTER 24 MONTHS OF TESTOSTERONE TREATMENT OF 10 HYPOGONADAL MEN
TABLE 2. BMD AND BONE ARCHITECTURAL PARAMETERS IN 10 EUGONADAL MEN FOLLOWED FOR 24 MONTHS
Table 2 Cluster accuracy and stability on the completely synthetic data with four repeated measurements at low noise level
2003
"... In PAGE 6: ... The external knowledge is not used in computing cluster stability. Completely synthetic data at low noise level Table2 a,b shows selected results on cluster accuracy and cluster stability on the completely synthetic datasets with four simulated repeated measurements. Table 2a,b show results from average linkage, complete linkage and centroid linkage hierarchical algorithms, k-means, MCLUST-HC (a hierarchical model-based clustering algorithm from MCLUST) and IMM.... In PAGE 6: ... Completely synthetic data at low noise level Table 2a,b shows selected results on cluster accuracy and cluster stability on the completely synthetic datasets with four simulated repeated measurements. Table2 a,b show results from average linkage, complete linkage and centroid linkage hierarchical algorithms, k-means, MCLUST-HC (a hierarchical model-based clustering algorithm from MCLUST) and IMM. Both single linkage and DIANA produce very low-quality and unstable clusters and their adjusted Rand indices are not shown.... ..."
Table 3 Cluster accuracy and stability on the completely synthetic data with four repeated measurements at high noise level
2003
"... In PAGE 7: ...cluster quality over the approach of averaging over repeated measurements using the same algorithms at high noise level. In terms of cluster stability (see Table3 b), the following three approaches yield average adjusted Rand index above 0.900: the elliptical model of the IMM approach; the comment reviews reports deposited research interactions information refereed research http://genomebiology.... ..."
Table I. Unnormalized benchmark data. All measurements were repeated at least 6 times. The
Table I. Unnormalized benchmark data. All measurements were repeated at least 6 times. The con dence interval is expressed as as the width (+ -) on either side of the mean.
Table 1. Results of the Repeated-Measures ANOVA for Perceived Equivocality Level
in Abstract
"... In PAGE 10: ... Perceived Equivocaiity Data associated with perceived equivocality was analyzed using a repeated-measures ANOVA test with the three independent variables, repre- sentation, task, and order. Table1 reports the results. The mean values and standard deviations are shown in Table 2.... ..."
Table 5 Cluster accuracy on the completely synthetic datasets with different numbers of repeated measurements
2003
"... In PAGE 9: ... Specifically, we generated 1, 4, or 20 repeated measure- ments at both the low and high noise levels. The quality of clustering results on datasets with higher numbers of repeated measurements is usually higher ( Table5 ). For example, using the same algorithms and same similarity measures cluster accuracy is considerably improved with synthetic datasets of four repeated measurements relative to datasets with no repeated measurement.... In PAGE 12: ... The variability-weighted approach works almost as well as the IMM with 20 repeated measurements. From our results on the synthetic data, we showed that there is significant improvement in cluster accuracy from one to four repeated measurements using IMM at both low and high noise levels ( Table5 ). However, there is no substantial improvement in cluster accuracy from 4 to 20 repeated measurements with the IMM approach (Table 5).... In PAGE 15: ... An object in the current cluster is moved to the new cluster if the average similarity with the new cluster is higher than that with the current cluster. Completely synthetic data with different numbers of repeated measurements Table5 shows some selected results produced using average linkage hierarchical algorithm on the completely synthetic data over varying numbers of repeated measurements and different noise levels. In general, increasing the number of repeated measurements increases cluster accuracy (average adjusted Rand index with respect to the six classes).... ..."
Table 4 Summary of a repeated measures analysis of covariance (ANCOVA) on log (x + 1) transformed data for deviation from 1:1 sex ratio (Sex) and wood versus open (Side) with the distance from the stream as covariate. The test was performed on the four most common stoneflies taken in Malaise traps on land
1999
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