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NORMATIVE DATA


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.

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