CCM Example 2 Output Table (Columns 1-5)
cause |
effect |
library_size |
correlation |
jaccard_index |
indexval |
indexchange |
10 |
0.07415 |
|
indexval |
indexchange |
25 |
0.51966 |
|
indexval |
indexchange |
50 |
0.55927 |
|
indexval |
indexdate |
10 |
-0.52809 |
|
indexval |
indexdate |
25 |
-0.43179 |
|
indexval |
indexdate |
50 |
-0.42503 |
|
marketindex |
indexchange |
10 |
|
0.51125 |
marketindex |
indexchange |
25 |
|
0.6 |
marketindex |
indexchange |
50 |
|
0.6425 |
marketindex |
indexdate |
10 |
|
0.0175 |
marketindex |
indexdate |
25 |
|
0 |
marketindex |
indexdate |
50 |
|
0 |
CCM Example 2 Output Table (Columns 6-9)
lower_bound |
upper_bound |
effect_size |
effect_size_sd |
-0.12229 |
0.26500 |
0.55748 |
0.12117 |
0.42471 |
0.60330 |
|
|
0.46165 |
0.64350 |
|
|
-0.64236 |
-0.39085 |
0.13368 |
0.11398 |
-0.46852 |
-0.39358 |
|
|
-0.53209 |
-0.30460 |
|
|
0.47383 |
0.54867 |
0.13125 |
0.02542 |
0.56526 |
0.63474 |
|
|
0.60961 |
0.67539 |
|
|
0.00400 |
0.03100 |
-0.01750 |
0.00689 |
0.00000 |
0.00000 |
|
|
0.00000 |
0.00000 |
|
|
For numeric variables, the correlation indicates the relationship between the values of the cause variable (as predicted by the effect variable) and the true values of the cause variable. The example shows a steadily increasing absolute value of the correlation between indexval and indexchange, and a high effect size (0.557). There is no clear trend for the correlation between indexval and indexdate.