structure(list(effectiveSize = structure(c(6010.91813446356, 
1428.60500515852), .Names = c("d.control.diet", "sd.d")), summary = structure(list(
    statistics = structure(c(-0.0138621842733287, 0.134696044870237, 
    0.090505271825022, 0.121416291517638, 0.000319984457203024, 
    0.000429271415393222, 0.00118719005156229, 0.00321004646676098
    ), .Dim = c(2L, 4L), .Dimnames = list(c("d.control.diet", 
    "sd.d"), c("Mean", "SD", "Naive SE", "Time-series SE"))), 
    quantiles = structure(c(-0.196956964956764, 0.00514998536486905, 
    -0.0638059724036764, 0.0478537227781431, -0.0143086024444535, 
    0.103100704484174, 0.0380008035675889, 0.184911494352956, 
    0.162834437851103, 0.451120504851119), .Dim = c(2L, 5L), .Dimnames = list(
        c("d.control.diet", "sd.d"), c("2.5%", "25%", "50%", 
        "75%", "97.5%"))), start = 5001, end = 25000, thin = 1, 
    nchain = 4L), .Names = c("statistics", "quantiles", "start", 
"end", "thin", "nchain"), class = "summary.mcmc"), cov = structure(0.00819120422812111, .Dim = c(1L, 
1L)), ranks = structure(c(0.575775, 0.424225, 0.424225, 0.575775
), .Dim = c(2L, 2L), .Dimnames = list(c("control", "diet"), NULL), class = "mtc.rank.probability", direction = 1), 
    dic = structure(list(Dbar = 20.9592507798904, pD = 13.5301447471747, 
        DIC = 34.4893955270651, `data points` = 20L), .Names = c("Dbar", 
    "pD", "DIC", "data points"))), .Names = c("effectiveSize", 
"summary", "cov", "ranks", "dic"))