ROC curves showing MoCA©
superiority to MMSE in distinguishing Normal Controls from
MCI.
«The areas under ROC curves were compared with the method
of Delong,Delong and Clarke-Pearson (1988) for correlated
curves. The difference was statistically significant
x2(1,N=182)=11,66, p<0.001.»
|
Area Under the Curve |
|
Test Result Variable(s) : MoCA |
|
Lower BoundUpper BoundLower
Bound |
|
Area |
Std. Error (a)
|
Asymptotic Sig. (b)
|
Asymptotic 95%
Interval |
|
Upper Bound |
Lower Bound |
|
.921 |
.020 |
.000 |
.882 |
.960 |
|
The test
result variable(s): MOCA new has at least one tie between the
positive actual state group and the negative actual state group.
Statistics may be biased.
|
|
(a) Under the
nonparametric assumption. (b) Null hypothesis: true area =
0.5 |
|
Area Under the Curve |
|
Test Result Variable(s) : MMSE |
|
Lower BoundUpper BoundLower
Bound |
|
Area
|
Std. Error (a)
|
Asymptotic Sig. (b)
|
Asymptotic 95%
Interval |
|
Upper Bound |
Lower Bound |
|
.814 |
.032 |
.000 |
.751 |
.876 |
|
The test
result variable(s): MMSE_num has at least one tie between the
positive actual state group and the negative actual state group.
Statistics may be biased. |
|
(a) Under the
nonparametric assumption. (b) Null hypothesis: true area =
0.5 |
Nasreddine ZS, Phillips NA, Bédirian
V, Charbonneau S, Whitehead V, Collin I, Cummings JL,
Chertkow H.
The Montreal Cognitive Assessment (MoCA©):
A Brief Screening Tool For Mild Cognitive Impairment. J Am
Geriatr Soc 53:695–699, 2005. |