Biostatistics For Dummies, 2nd Edition (Monika Wahi, John Pezzullo)

CHAPTER 13 Taking a Closer Look at Fourfold Tables 177

Describing the association between

two binary variables

Suppose you conduct a cross-sectional study by enrolling a random sample of

60 adults from the local population as participants in your study with the hypoth-

esis that being obese is associated with having HTN. For the exposure, suppose

you measure their height and weight, and use these values to calculate their body

mass index (BMI). You then use their BMI to classify them as either obese or non-

obese. For the outcome, you also measure their blood pressure in order to catego-

rize them as having HTN or not having HTN. This is simple random sampling

(SRS), as described in the earlier section “Choosing the Correct Sampling Strat-

egy.” You can summarize your data in a fourfold table (see Figure 13-2).

The table in Figure 13-2 indicates that more than half of the obese participants

have HTN and more than half of the non-obese participants don’t have HTN — so

there appears to be a relationship between being a membership in a particular row

and simultaneously being a member of a particular column. You can show this

apparent association is statistically significant in this sample using either a Yates

chi-square or a Fisher Exact test on this table (as we describe in Chapter 12). If you

do these tests, your p values will be p

0 016

and p

0 013

, respectively, and at

α = 0.05, you will be comfortable rejecting the null.

But when you present the results of this study, just saying that a statistically sig-

nificant association exists between obesity status and HTN status isn’t enough.

You should also indicate how strong this relationship is and in what direction it

goes. A simple solution to this is to present the test statistic and p value to repre-

sent how strong the relationship is, and to present the actual results as row

or column percentages to indicate the direction. For the data in Figure 13-2, you

could say that being obese was associated with having HTN, because 14/21 =

66 percent of obese participants also had HTN, while only 12/39 = 31 percent of

non-obese participants had HTN.

FIGURE 13-2:

A fourfold table

summarizing

obesity and

hypertension

in a sample of

60 participants.