chi2_risk(M)

Computes a Risk test using data in matrix M and a significance level of 0.95 (95%). Matrix M must store a contingency table 2x2.

chi2_risk(M, alpha)

As above but the significance level is alpha.


See also chi2_mcnemar chi2_kappa chi2_mantel chi2_mcnemarbowker 


Example


The contingency table below shows some facts about drinking, and heart attacks:


Alcoholic
Heart attack
Total
Yes
No
Yes
70
52
122
No
29
48
77
Total
99
100
199

Entering the basic data in a matrix we obtain:

M = ( 70, 52; 29, 48)

/ 70 52 \

\ 29 48 /


We now use function chi2_totable to transform the matrix into a proper contingency table

M=chi2_totable(M)

/ "" "" "" "" \

| ""  70  52  122 |

| ""  29  58   77 |

\ ""  99  100 199 /


Using the function chi2_risk we obtain,

chi2_risk(M)


Risk test.

Significance level : 0.95 (95.0%)

Results:

Odds Ratio value: 2.228116710875332

Interval  : (1.2423360294768229, 3.996104080932578 )

Risk ratio (first column): 1.5234595816845675

Interval  : (1.1001650009990764, 2.10961909797062 )

Risk ratio (second column): 0.6837431693989071

Interval  : (0.5223155228288222, 0.8950618950930114 )

Number of valid cases: 199