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Introduction to Categorical Data Analysis

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PROBLEMS 93<br />

in millions of lira, the table indicates the number of subjects sampled and the<br />

number of them possessing at least one travel credit card. (Note: one million lira<br />

at the time of the study is currently worth aout 500 euros.) Software provides the<br />

following results of using logistic regression <strong>to</strong> relate the probability of having<br />

a travel credit card <strong>to</strong> income, treating these as independent binomial samples.<br />

Parameter Estimate Standard error<br />

Intercept −3.5561 0.7169<br />

Income 0.0532 0.0131<br />

a. Report the prediction equation.<br />

b. Interpret the sign of ˆβ.<br />

c. When ˆπ = 0.50, show that the estimated logit value is 0. Based on this, for<br />

these data explain why the estimated probability of a travel credit card is<br />

0.50 at income = 66.86 million lira.<br />

Table 3.6. <strong>Data</strong> for Problem 3.9 on Italian Credit Cards<br />

No. Credit No. Credit No. Credit No. Credit<br />

Inc. Cases Cards Inc. Cases Cards Inc. Cases Cards Inc. Cases Cards<br />

24 1 0 34 7 1 48 1 0 70 5 3<br />

27 1 0 35 1 1 49 1 0 79 1 0<br />

28 5 2 38 3 1 50 10 2 80 1 0<br />

29 3 0 39 2 0 52 1 0 84 1 0<br />

30 9 1 40 5 0 59 1 0 94 1 0<br />

31 5 1 41 2 0 60 5 2 120 6 6<br />

32 8 0 42 2 0 65 6 6 130 1 1<br />

33 1 0 45 1 1 68 3 3<br />

Source: Based on data in <strong>Categorical</strong> <strong>Data</strong> <strong>Analysis</strong>, Quaderni del Corso Estivo di Statistica e Calcolo<br />

delle Probabilità, no. 4, Istitu<strong>to</strong> di Me<strong>to</strong>di Quantitativi, Università Luigi Bocconi, by R. Piccarreta.<br />

3.10 Refer <strong>to</strong> Problem 4.1 on cancer remission. Table 3.7 shows output for fitting a<br />

probit model. Interpret the parameter estimates (a) finding the remission value<br />

at which the estimated probability of remission equals 0.50, (b) finding the<br />

difference between the estimated probabilities of remission at the upper and<br />

lower quartiles of the labeling index, 14 and 28, and (c) using characteristics<br />

of the normal cdf response curve.<br />

3.11 An experiment analyzes imperfection rates for two processes used <strong>to</strong> fabricate<br />

silicon wafers for computer chips. For treatment A applied <strong>to</strong> 10 wafers, the<br />

numbers of imperfections are 8, 7, 6, 6, 3, 4, 7, 2, 3, 4. Treatment B applied <strong>to</strong><br />

10 other wafers has 9, 9, 8, 14, 8, 13, 11, 5, 7, 6 imperfections. Treat the counts

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