Browsing by Subject "Analysis of Variance"

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    Open Access
    Apparent Absorption Efficiencies of Nectar Sugars in the Cape Sugarbird, with a Comparison of Methods
    (1998) Jackson, Susan; Nicolson, Susan W; van Wyk, Ben‐Erik
    Nectarivore sugar preferences and nectar composition in the Cape Floristic Kingdom (southern Africa) differ from trends reported for analogous systems in America and Europe in that sugarbirds and sunbirds show no aversion to sucrose, which is the dominant nectar sugar in many of their food plants. To elucidate the physiological bases (if any) of nectarivore sugar preferences, we determined apparent sugar absorption efficiencies in a passerine endemic to this region, the Cape sugarbird Promerops cafer. Apparent absorption efficiencies for the three major nectar sugars, sucrose, glucose, and fructose, were extremely high (> 99%), as in other specialized avian nectarivores. Xylose, a pentose sugar recently reported in the nectar of some Proteaceae, was absorbed and/or metabolized inefficiently, with a mean of 47.1% of ingested sugar recovered in cloacal fluid. We did not measure the proportions of xylose that were absorbed and/or metabolized. We also compared three methods of estimating absorption efficiency: (1) measurements of total sugar in cloacal fluid with refractometry, without correction for differences between volumes of ingesta and excreta; (2) the same measurements combined with correction for volume differences; and (3) HPLC analyses quantifying individual sugars in cloacal fluid, with correction for volume differences. Refractometry has been frequently used in previous studies. For all sugars except xylose, method 1 yielded results similar to those obtained with method 2, but the convergence was artifactual, and we do not recommend use of this method. Apparent absorption efficiencies calculated with method 2 underestimated true absorption efficiency, because refractometry measures nonsugar solutes, but this error is biologically significant only when efficiencies are low.
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    Open Access
    A random effects variance shift model for detecting and accommodating outliers in meta-analysis
    (BioMed Central Ltd, 2011) Gumedze, Freedom; Jackson, Dan
    BACKGROUND:Meta-analysis typically involves combining the estimates from independent studies in order to estimate a parameter of interest across a population of studies. However, outliers often occur even under the random effects model. The presence of such outliers could substantially alter the conclusions in a meta-analysis. This paper proposes a methodology for identifying and, if desired, downweighting studies that do not appear representative of the population they are thought to represent under the random effects model. METHODS: An outlier is taken as an observation (study result) with an inflated random effect variance. We used the likelihood ratio test statistic as an objective measure for determining whether observations have inflated variance and are therefore considered outliers. A parametric bootstrap procedure was used to obtain the sampling distribution of the likelihood ratio test statistics and to account for multiple testing. Our methods were applied to three illustrative and contrasting meta-analytic data sets. RESULTS: For the three meta-analytic data sets our methods gave robust inferences when the identified outliers were downweighted. CONCLUSIONS: The proposed methodology provides a means to identify and, if desired, downweight outliers in meta-analysis. It does not eliminate them from the analysis however and we consider the proposed approach preferable to simply removing any or all apparently outlying results. We do not however propose that our methods in any way replace or diminish the standard random effects methodology that has proved so useful, rather they are helpful when used in conjunction with the random effects model.