7/29/2019 FCM Analysis with interpretation.doc

1/3

Logistic Regression

Dependent Variable Encoding

Original Value Internal Value

No 0

Yes 1

Categorical Variables Codings

Frequency

Parametercoding

(1)

Employment unemployed 37 1.000

employed 4 .000

Gender Male 4 1.000

Female 37 .000

Block 0: Beginning Block

Classification Table(a,b)

Observed Predicted

Practice (Is Px

Compliant)Percentage

CorrectNo Yes

Step 0 Practice (Is PxCompliant)

No0 14 .0

Yes 0 27 100.0

Overall Percentage 65.9

a Constant is included in the model.b The cut value is .500

Block 1: Method = Enter

Model Summary

Step-2 Log

likelihoodCox & SnellR Square

Nagelkerke RSquare

1 40.385 .258 .357

Hosmer and Lemeshow Test

Step Chi-square df Sig.1 5.379 8 .716

Classification Table(a)

7/29/2019 FCM Analysis with interpretation.doc

2/3

Observed Predicted

Practice (Is Px

Compliant)Percentage

CorrectNo Yes

Step 1 Practice (Is Px

Compliant)

No

6 8 42.9Yes 4 23 85.2

Overall Percentage 70.7

a The cut value is .500

Variables in the Equation

B S.E. Wald df Sig. Exp(B)

95.0% C.I.for E

Lower

Step 1(a) AGE -.086 .052 2.760 1 .097 .918 .829

GEN_REC(1)

-.933 1.676 .310 1 .578 .393 .015

EMP_REC(1)

2.588 1.426 3.295 1 .069 13.302 .814

DM_YR .144 .074 3.729 1 .053 1.154 .998

DM_REL -.874 1.088 .645 1 .422 .417 .050

EDUC_ATT

1.019 .694 2.156 1 .142 2.769 .711

KNOWL_SC

-.534 .247 4.671 1 .031 .586 .361

ATT_SC -.015 .031 .239 1 .625 .985 .926

Constant 6.161 4.715 1.708 1 .191 474.013

a Variable(s) entered on step 1: AGE, GEN_REC, EMP_REC, DM_YR, DM_REL, EDUC_ATT, KNOWL_SC,ATT_SC.

Note: Only Knowledge Score is statistically significant in predicting Compliance(the rest are may be due to chance): OR = 0.586, 95% CI: 0.361 0.951, p = 0.031.Interpretation of OR: for every increase in the Knowledge score by 1 point, theresan increase of odds of having compliance by 0.586.

Heres my own re-coding of the variables:

7/29/2019 FCM Analysis with interpretation.doc

3/3

Variables:

Age

Gender [Gen_Rec] (0 = male, 1 = female)

Employment [Emp_Rec] (I used Employment instead of Occupation)

(0 = unemployed, 1 = employed)

DM_yr = Number of years with DM type 2 (I used DM_yr instead ofDiabnumyears)

DM_rel = Does Px have Relatives with DM type 2? (0 = no, 1 = yes)

(I used DM_rel instead of Diabrel)

Educ_att = Educational attainment (0 = none, 1 = elementary, 2 = high

school, 3 = college)

(I used Educ_att instead of Edattain)

Knowl_Sc = total score gotten in the knowledge test (I used Knowl_Sc instead

of Knowledgeover)

Att_Sc = total score gotten in the attitude test (I used Att_Sc instead of

Attitudeover)