Refer to Problem 5.1. Table 6.18 shows output for fitting a probit model. Interpret the parameter estimates
Question:
Table 6.18:
Data Problem 5.1:
For a study using logistic regression to determine characteristics associated with remission in cancer patients, Table 5.10 shows the most important explanatory variable, a labeling index (U). This index measures proliferative activity of cells after a patient receives an injection of tritiated thymidine, representing the percentage of cells that are labeled. The response Y measured whether the patient achieved remission (1 = yes). Software reports Table 5.11 for a logistic regression model using LI to predict the probability of remission.
a. Show how software obtained ÏÌ = 0.068 when LI = 8.
b. Show that ÏÌ = 0.5 when LI = 26.0.
c. Show that the rate of change in ÏÌ is 0.009 when LI = 8 and 0.036 when LI = 26.
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