This data set gives average estimated counts of flies along with standard errors from 7 different observers.
The data frame contains the following columns:
|mean|| ||mean count|
|se2|| ||squared standard error|
Quoting from Cochran (1954), example 3, p.119: “In studies by the U.S. Public Health Service of observers' abilities to count the number of flies which settle momentarily on a grill, each of 7 observers was shown, for a brief period, grills with known numbers of flies impaled on them and asked to estimate the numbers. For a given grill, each observer made 5 independent estimates. The data in table 9 are for a grill which actually contained 161 flies. Estimated variances are based on 4 degrees of freedom each. [...] The only point of interest in estimating the overall mean is to test whether there is any consistent bias among observers in estimating the 161 flies on the grill. Although inspection of table 9 suggests no such bias, the data will serve to illustrate the application of partial weighting.”
W.G. Cochran. The combination of estimates from different experiments. Biometrics, 10(1):101-129, 1954.
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data("Cochran1954") ## Not run: # analysis using improper uniform prior # (may take a few seconds to compute!): bma <- bayesmeta(y=Cochran1954[,"mean"], sigma=sqrt(Cochran1954[,"se2"]), label=Cochran1954[,"observer"]) # show joint posterior density: plot(bma, which=2, main="Cochran example") # show (known) true parameter value: abline(h=161) # show forest plot: forestplot(bma, zero=161) ## End(Not run)
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