R: Power Calculations for Exact and Asymptotic McNemar Test in a...

power_mcnemar_test {MESS} | R Documentation

## Power Calculations for Exact and Asymptotic McNemar Test in a 2 by 2 table

### Description

Compute power of test, or determine parameters to obtain target power for matched case-control studies.

### Usage

    power_mcnemar_test(n = NULL, paid = NULL, psi = NULL,
      sig.level = 0.05, power = NULL, alternative = c("two.sided",
      "one.sided"), method = c("normal", "exact", "cond.exact"))

### Arguments

`n` | Number of observations (number of pairs)
`paid` | The probability that a case patient is not exposed and that the corresponding control patient was exposed (specifying p_12 in the 2 x 2 table). It is assumed that this is the _smaller_ of the two discordant probabilities.
`psi` | The relative probability that a control patient is not exposed and that the corresponding case patient was exposed compared to the probability that a case patient is not exposed and that the corresponding control patient was exposed (i.e., p_21 / p_12 in the 2x2 table). Also called the discordant proportion ratio. psi must be larger than or equal to 1 since paid was the smaller of the two discordant probabilities.
`sig.level` | Significance level (Type I error probability)
`power` | Power of test (1 minus Type II error probability)
`alternative` | One- or two-sided test
`method` | Power calculations based on exact or asymptotic test. The default (normal) corresponds to an approximative test, "exact" is the unconditional exact test, while "cond.exact" is a conditional exact test (given fixed n).

### Value

Object of class `power.htest`, a list of the arguments (including the computed one) augmented with method and note elements.

### Note

`uniroot` is used to solve power equation for unknowns, so you may see errors from it, notably about inability to bracket the root when invalid arguments are given.

### Author(s)

Claus Ekstrom claus@rprimer.dk

### References

Duffy, S (1984). Asymptotic and Exact Power for the McNemar Test and its Analogue with R Controls per Case

Fagerland MW, Lydersen S, Laake P. (2013) The McNemar test for binary matched-pairs data: mid-p and asymptotic are better than exact conditional. BMC Medical Research Methodology.

### See Also

`mcnemar.test`

### Examples

    # Assume that pi_12 is 0.125 and we wish to detect an OR of 2.
    # This implies that pi_12=0.25, and with alpha=0.05, and a power of 90% you get
    power_mcnemar_test(n=NULL, paid=.125, psi=2, power=.9)

    power_mcnemar_test(n=NULL, paid=.1, psi=2, power=.8, method="normal")
    power_mcnemar_test(n=NULL, paid=.1, psi=2, power=.8)

[Package MESS version 0.5.6 Index]