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Wald confidence intervals for RR from matched pairs

RRmpWald.Rd

Estimates confidence intervals for the risk ratio or prevented fraction from matched pairs.

Usage

RRmpWald(
  formula = NULL,
  data = NULL,
  compare = c("vac", "con"),
  affected = 1,
  x,
  alpha = 0.05,
  pf = TRUE,
  tdist = TRUE,
  df = NULL,
  rnd = 3
)

Arguments

formula

Formula of the form y ~ x + cluster(w), where y is the indicator for an individual's positive response, x is a factor with two levels of treatment, and w identifies the pairs.

data

data.frame containing variables in formula

compare

Text vector stating the factor levels: compare[1] is the vaccinate group to which compare[2] (control or reference) is compared.

affected

Indicator for positive response

x

Alternative data input. Instead of formula and data frame, data may be input as frequency vector. See example for how to order this vector.

alpha

Complement of the confidence level

pf

Estimate RR or its complement PF?

tdist

Use t distribution?

df

Degrees of freedom. When NULL, the function will default to `df = N

  • 2`, where N is the total number of pairs.

rnd

Number of digits for rounding. Affects display only, not estimates.

Value

A rrmp object with the following fields:

  • estimate: vector of point and interval estimates - see details

  • estimator: either "PF" or "RR"

  • compare: text vector, same as input

  • alpha: complement of confidence level

  • rnd: how many digits to round the display

  • multvec: data frame showing the multinomial representation of the data

Details

Estimates confidence intervals for the risk ratio or prevented fraction from matched pairs. The response is the tetranomial vector c(11, 12, 21, 22), where the first index is the row and the the second index is the column when displayed as a 2x2 table. Wald type confidence intervals are found by applying the delta method to the multinomial variance. This method fails when there are no responders in one of the treatment groups.

Alternative forms of data entry are illustrated by the output, say Y, where c(Y$xtable) = Y$freqvec = Y$multvec$Freq.

If RR = 0 (PF = 1), the function will return degenerate interval.

Note

Experimental functions for estimating profile likelihood intervals are in the CVBmisc package.

Call to this function may be one of two formats: (1) specify data and formula or (2) as a vector x

RRmpWald(formula, data, compare = c("vac", "con"), affected = 1, alpha = 0.05, pf = TRUE, tdist = TRUE, df = NULL, rnd = 3)

RRmpWald(x, compare = c("vac", "con"), affected = 1, alpha = 0, 05, pf = TRUE, tdist = TRUE, df = NULL, rnd = 3)

Author

PF-package

Examples

RRmpWald(pos ~ tx + cluster(cage), New, compare = c("vac", "con"))
#> 
#> PF 
#> 95% interval estimates
#> 
#>    PF    LL    UL 
#> 0.550 0.183 0.752 
#> 

thistable <- New |>
  tidyr::spread(tx, pos) |>
  tidyr::drop_na() |>
  dplyr::mutate(vac = factor(vac, levels = 1:0),
    con = factor(con, levels = 1:0)) |>
  with(table(vac, con))
thistable
#>    con
#> vac  1  0
#>   1  7  2
#>   0 13  4
as.vector(thistable)
#> [1]  7 13  2  4

RRmpWald(x = as.vector(thistable))
#> 
#> PF 
#> 95% interval estimates
#> 
#>    PF    LL    UL 
#> 0.550 0.183 0.752 
#>