From: Michael Dewey <info_at_aghmed.fsnet.co.uk>

Date: Fri 10 Nov 2006 - 14:43:27 GMT

Outcome : Col 1

Comparing : Row 1 vs. Row 2

R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Received on Sat Nov 11 01:53:01 2006

Date: Fri 10 Nov 2006 - 14:43:27 GMT

I can obtain a confidence interval for

the odds ratio from fisher.test of

course

- fisher.test example ===

> outcome <- matrix(c(500, 0, 500, 8), ncol = 2, byrow = TRUE)

> fisher.test(outcome)

Fisher's Exact Test for Count Data

data: outcome

p-value = 0.00761

alternative hypothesis: true odds ratio is not equal to 1
95 percent confidence interval:

1.694792 Inf

sample estimates:

odds ratio

Inf

- end example ===

but in epidemiology authors often

prefer to present risk ratios.

Using the facility on CRAN to search

the site I find packages epitools and Epi
which both offer confidence intervals

for the risk ratio

- Epi example ===

> library(Epi)

> twoby2(outcome[c(2,1),c(2,1)])

2 by 2 table analysis:

Outcome : Col 1

Comparing : Row 1 vs. Row 2

Col 1 Col 2 P(Col 1) 95% conf. interval Row 1 8 500 0.0157 0.0079 0.0312 Row 2 0 500 0.0000 0.0000 NaN 95% conf. interval Relative Risk: Inf NaN Inf Sample Odds Ratio: Inf NaN Inf Conditional MLE Odds Ratio: Inf 1.6948 Inf Probability difference: 0.0157 0.0027 0.0337 Exact P-value: 0.0076 Asymptotic P-value: NaN ------------------------------------------------------

- end example ===

So Epi gives me a lower limit of NaN but the same confidence interval and p-value as fisher.test

- epitools example ===

> library(epitools)

> riskratio(outcome)

$data

Outcome

Predictor Disease1 Disease2 Total

Exposed1 500 0 500 Exposed2 500 8 508 Total 1000 8 1008 $measure risk ratio with 95% C.I. Predictor estimate lower upper Exposed1 1 NA NA Exposed2 Inf NaN Inf $p.value two-sided Predictor midp.exact fisher.exact chi.square Exposed1 NA NA NAExposed2 0.00404821 0.007610478 0.004843385

$correction

**[1] FALSE
**
attr(,"method")

[1] "Unconditional MLE & normal approximation (Wald) CI"
Warning message:

Chi-squared approximation may be incorrect in: chisq.test(xx, correct =
correction)

And epitools also gives a lower limit

of NaN.

- end all examples ===

I would prefer not to have to tell the authors of the
paper I am refereeing that

I think they are wrong unless I can help them with what they
should have done.

Is there another package I should have tried?

Is there some other way of doing this?

Am I doing something fundamentally wrong-headed?

Michael Dewey

http://www.aghmed.fsnet.co.uk

R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Received on Sat Nov 11 01:53:01 2006

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