Logistic Regression: A Self-learning Text, Third Edition (Statistics in the Health Sciences)

Test The following questions and computer output consider a
data from a cross-sectional study carried out at Grady
Hospital in Atlanta, Georgia involving 289 adult patients
seen in an emergency department whose blood cultures
taken within 24 hours of admission were found to have
Staph aureus infection (Rezende et al., 2002). Information
was obtained on several variables, some of which were
considered risk factors for methicillin-resitance (MRSA).
The outcome variable is MRSA status (1¼yes, 0¼no),
and covariates of interest included the following variables:
PREVHOSP (1¼previous hospitalization, 0¼no previ-
ous hospitalization), AGE (continuous), GENDER (1¼
male, 0¼female), and PAMU (1¼antimicrobial drug
use in the previous 3 months, 0¼no previous antimicro-
bial drug use).

The SAS output provided below was obtained for the fol-

lowing logistic model:

Logit PðXÞ¼aþb 1 PREVHOSPþb 2 AGEþb 3 GENDER

þb 4 PAMU

Deviance and Pearson Goodness-of-Fit Statistics

Criterion Value DF Value/DF Pr>ChiSq

Deviance 159.2017 181 0.8796 0.8769

Pearson 167.0810 181 0.9231 0.7630

Number of unique profiles: 186

Model Fit Statistics

Criterion Intercept Only

Intercept and

Covariates

2 Log L 387.666 279.317

Analysis of Maximum Likelihood Estimates

Parameter DF Estimate Std Error

Wald

Chi-Sq Pr>ChiSq

Intercept 1 5.0583 0.7643 43.8059 <.0001

PREVHOSP 1 1.4855 0.4032 13.5745 0.0002

AGE 1 0.0353 0.00920 14.7004 0.0001

gender 1 0.9329 0.3418 7.4513 0.0063

pamu 1 1.7819 0.3707 23.1113 <.0001

338 9. Assessing Goodness of Fit for Logistic Regression