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

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Answers to Practice Exercises


Practice
Exercises



  1. The data listing is in events trials (ET) format. There
    are eight lines of data corresponding to the distinct
    covariate patterns defined by the model; each line con-
    tains the number of cases (i.e., events) and the number
    of subjects (i.e., trials) for each covariate pattern.

  2. There are eight covariate patterns:
    Pattern 1:X¼(CAT¼0, AGE¼0, ECG¼0)
    Pattern 2:X¼(CAT¼0, AGE¼1, ECG¼0)
    Pattern 3:X¼(CAT¼0, AGE¼0, ECG¼1)
    Pattern 4:X¼(CAT¼0, AGE¼1, ECG¼1)
    Pattern 5:X¼(CAT¼1, AGE¼0, ECG¼0)
    Pattern 6:X¼(CAT¼1, AGE¼1, ECG¼0)
    Pattern 7:X¼(CAT¼1, AGE¼0, ECG¼1)
    Pattern 8:X¼(CAT¼1, AGE¼1, ECG¼1)

  3. No. The model contains four parameters, whereas
    there are eight covariate patterns.

  4. No. The model does not perfectly predict the case/
    noncase status of each of the 609 subjects in the data.

  5. a. No. The deviance value of 0.9544 is not calculated
    using the deviance formula
    Devðb^Þ¼ 2 lnðL^c=L^maxÞ:
    In particular 2 lnL^c¼ 418 : 181 and 2 lnL^max¼ 0 ,
    so Devð^bÞ¼ 418 : 181.
    b. Model 1 :Logit PðXÞ¼aþbCATþg 1 AGEþg 2 ECG
    Model 2 :Logit PðXÞ¼aþbCATþg 1 AGEþg 2 ECG
    þg 3 AGEECG
    þd 1 CATAGE
    þd 2 CATECG
    þd 3 CATAGEECG
    c. 0 : 9544 ¼ 2 lnL^Model 1 ð 2 lnL^Model 2 Þ,
    where  2 lnL^Model 1 ¼ 418 : 1810 and
     2 lnL^Model 2 ¼ 418 : 1810  0 : 9544 ¼ 417 : 2266 :
    d. H 0 :d 1 ¼d 2 ¼d 3 ¼0, i.e., the deviance is used to
    test for whether the coefficients of all the product
    terms in Model 2 are collectively nonsignificant.
    e. G¼no. of covariate patterns¼ 8 <<n¼609.

  6. a. The HL test has aP-value of 0.9177, which is highly
    nonsignificant. Therefore, the HL test indicates
    that the model does not have lack of fit.
    b. The model contains only eight covariate patterns,
    so it is not possible to obtain more than eight
    distinct predicted risk values from the data. The
    degrees of freedom is 4 because it is calculated as
    the number of groups (i.e., 6) minus 2.
    c. Models 1 and Models 2 as stated in the answer to
    question 5b.


342 9. Assessing Goodness of Fit for Logistic Regression

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