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

(vip2019) #1

  1. No. If the study design had been either case-control or
    cross-sectional, risk estimates could not be computed
    because the constant term (a) in the model could not
    be estimated. In other words, even if the computer
    printed out values of1.18 or1.19 for the constant
    terms, these numbers would not be legitimate
    estimates ofa.

  2. For case-control studies, only odds ratios, not risks or
    risk ratios, can be computed directly from the fitted
    model.

  3. ORc(SOC¼1vs.SOC¼0 controlling for SMK and SBP)
    ¼e^b,whereb^¼ 0 : 50 is the estimated coefficient of SOC
    in the fitted model
    ¼exp(0.50)
    ¼0.6065¼1/1.65.
    The estimated odds ratio is less than 1, indicating that,
    for this data set, the risk of CVD death for high social
    class persons is less than the risk for low social class
    persons. In particular, the risk for low social class
    persons is estimated as 1.65 times as large as the risk
    for high social class persons.

  4. Choice (a) isnotappropriate for the effect of SOC
    using model 1. Model 1 contains interaction terms,
    whereas choice (a) is appropriate only if all the
    variables in the model are main effect terms. Choices
    (b) and (c) are two equivalent ways of stating the
    general formula for calculating the odds ratio for any
    kind of logistic model, regardless of the types of
    variables in the model.


Answers to Practice Exercises 39
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