Test of two proportions from the same survey

I was wondering which test I should use for comparing two proportions from the same survey.

Example: A survey of 1000 people ask two question. "Do you smoke everyday?" and "Do you drink alcohol everyday?" 25% report they smoke cigarettes. 20% report they drink alcohol. Are the two proportions different?

If anyone could provide me with the correct test and a reference I would much appreciate it.

If you can produce a 2x2 table then you should use McNemar's test. If not then you would have to make the assumption that alcohol and cigarette consumption are independent to do any other analysis.

Further explanation

In response to comment from @SalMangiafico

https://en.wikipedia.org/wiki/McNemar's_test describes McNemar's test as determining whether row- and column- marginal frequencies are equal in a 2x2 table. So in this case you tabulate according to smoking and drinking.

╔══════════════╦═══════╦══════════════╦═══════╗
║              ║ Smoke ║ Do not smoke ║ Total ║
╠══════════════╬═══════╬══════════════╬═══════╣
║ Drink        ║ a     ║ b            ║   200 ║
║ Do not drink ║ c     ║ d            ║   800 ║
╠══════════════╬═══════╬══════════════╬═══════╣
║ Total        ║ 250   ║ 750          ║  1000 ║
╚══════════════╩═══════╩══════════════╩═══════╝


From the information you have provided it is not possible to populate this table, but it may be available to you. But let's suppose that 100 drink but do not smoke and 150 smoke but do not drink:

╔══════════════╦═══════╦══════════════╦═══════╗
║              ║ Smoke ║ Do not smoke ║ Total ║
╠══════════════╬═══════╬══════════════╬═══════╣
║ Drink        ║ 100   ║ 100          ║   200 ║
║ Do not drink ║ 150   ║ 650          ║   800 ║
╠══════════════╬═══════╬══════════════╬═══════╣
║ Total        ║ 250   ║ 750          ║  1000 ║
╚══════════════╩═══════╩══════════════╩═══════╝


We can use mcnemar.test in R:

> mcnemar.test(matrix(c(100, 150, 100, 650), ncol = 2))

McNemar's Chi-squared test

data:  matrix(c(100, 150, 100, 650), ncol = 2)
McNemar's chi-squared = 9.604, df = 1, p-value = 0.001942


In this case it finds there is a statistically significant difference between the proportions smoking and the proportions drinking.

In fact, across all valid values of a (from 0 to 200) you find that there is a statistically significant difference.

If you do not have access to the 2x2 table, then a publication from 1993 suggests an approximate solution C. J. Wild and G. A. F. Seber. Comparing Two Proportions from the Same Survey. The American Statistician Vol. 47, No. 3 (Aug., 1993), pp. 178-181

$$\left|z\right| \ge \frac{\hat{p}_1 - \hat{p}_2}{\sqrt{\max(\hat{p}_1+\hat{p}_2, \hat{q}_1+\hat{q}_2)/n}}$$

$$\left|z\right| \ge \frac{0.25 - 0.2}{\sqrt{\max(0.25+0.2, 0.75+0.8)/1000}} = \frac{0.05}{\sqrt{1.55/1000}} = 1.27$$