314 PART 6 Analyzing Survival Data

worksheet shown in Figure 22-4, but with a few differences in the raw data cells

and minor differences in the calculations:»

» Instead of a column identifying the time slices, there are two columns

identifying the individual participant (Column A) and their survival or censor-

ing time (Column B). The table is ordered from the shortest time to

the longest.»

» Instead of two columns containing the number who died and were censored

in each interval, you need only one column indicating whether or not the

participant in that row died (Column C). If they died during the observation

period, use code 1, and if not and they were censored, use code 0.»

» These changes mean that Column D labeled Alive at Start now decreases by 1

for each subsequent row.»

» The At Risk column in Figure 21-4 isn’t needed, because it can be calculated

from the Alive at Start column. That’s because if the participant is censored,

the probability of dying is calculated as 0, regardless of the value of the

denominator.»

» To calculate Column E, the Probability of Dying, divide the Died indicator by the

number of participants alive for that time period in Column D, Alive at Start.

Formula: E = C/D.»

» The probability of surviving (Column F) and the cumulative survival (Column G)

are calculated the same way as in the life-table method.

Figure  21-7 shows graphs of the K-M hazard and survival estimates from

Figure 21-6. These charts were created using the R statistical software. Most soft-

ware that performs survival analysis can create graphs similar to this. The K-M

FIGURE 21-6:

Kaplan-Meier

calculations.

© John Wiley & Sons, Inc.