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Why would r's prop.test function (documentation here) return different results based on whether I pass it a matrix or vectors?

Here I pass it vectors:

> prop.test(x = c(135, 47), n = c(1781, 1443))

    2-sample test for equality of proportions with
    continuity correction

data:  c(135, 47) out of c(1781, 1443)
X-squared = 27.161, df = 1, p-value = 1.872e-07
alternative hypothesis: two.sided
95 percent confidence interval:
 0.02727260 0.05918556
sample estimates:
    prop 1     prop 2 
0.07580011 0.03257103

Here I create a matrix and pass it in instead:

> table <- matrix(c(135, 47, 1781, 1443), ncol=2)
> prop.test(table)

    2-sample test for equality of proportions with
    continuity correction

data:  table
X-squared = 24.333, df = 1, p-value = 8.105e-07
alternative hypothesis: two.sided
95 percent confidence interval:
 0.02382527 0.05400606
sample estimates:
    prop 1     prop 2 
0.07045929 0.03154362

Why do I get different results? I expect the same results for both scenarios to be returned.

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1 回答 1

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当x和n作为单独的向量输入时，它们分别被视为成功次数和试验总数。但是当您输入一个矩阵时，第一列被视为成功次数，第二列被视为失败次数。从帮助prop.test：

x    a vector of counts of successes, a one-dimensional table with two
     entries, or a two-dimensional table (or matrix) with 2 columns, giving
     the counts of successes and failures, respectively.

因此，要使用矩阵获得相同的结果，您需要将矩阵的第二列转换为失败次数（假设在您的示例x中是成功次数并且n是试验次数）。

x = c(135, 47)
n = c(1781, 1443)

prop.test(x, n)  # x = successes; n = total trials

  2-sample test for equality of proportions with continuity correction

data:  x out of n
X-squared = 27.161, df = 1, p-value = 1.872e-07
alternative hypothesis: two.sided
95 percent confidence interval:
 0.02727260 0.05918556
sample estimates:
    prop 1     prop 2 
0.07580011 0.03257103

prop.test(cbind(x, n - x)) # x = successes; convert n to number of failures

  2-sample test for equality of proportions with continuity correction

data:  cbind(x, n - x)
X-squared = 27.161, df = 1, p-value = 1.872e-07
alternative hypothesis: two.sided
95 percent confidence interval:
 0.02727260 0.05918556
sample estimates:
    prop 1     prop 2 
0.07580011 0.03257103
于 2016-08-08T16:56:24.300 回答