Simultaneous Comparisons of Multiple Treatments to Two (or More) Control

DUNNETT (1955) developed a procedure simultaneously comparing k treatments to one control with an exact overall type I error of α when all sampling distributions are normal. Sometimes it is desirable to compare k treatments to m≧2 controls, in particular to two controls. For instance, several new therapies (e.g., pain relievers) could be compared to two standard therapies (e.g., Aspirin and Tylenol). Alternatively, a standard therapy could be very expensive, difficult to apply and/or have bad side effects, making it useful to compare each new therapy to both standard therapy and no therapy (Placebo). Dunnett's method is expanded here to give comparisons of mean values for k treatments to mean values for m≧2 controls at an exact overall type I error of α when all sampling distributions are normal. Tabled values needed to make exact simultaneous comparisons at α = .05 are given for m = 2. An application is made to an example from the literature.     

Bayesian Quantile Regression for Longitudinal Studies with Nonignorable Missing Data

Summary .  We study quantile regression (QR) for longitudinal measurements with nonignorable intermittent missing data and dropout. Compared to conventional mean regression, quantile regression can characterize the entire conditional distribution of the outcome variable, and is more robust to outliers and misspecification of the error distribution. We account for the within-subject correlation by introducing a   ℓ₂   penalty in the usual QR check function to shrink the subject-specific intercepts and slopes toward the common population values. The informative missing data are assumed to be related to the longitudinal outcome process through the shared latent random effects. We assess the performance of the proposed method using simulation studies, and illustrate it with data from a pediatric AIDS clinical trial.     

Plausibility of inferred ancestral phenotypes and the evaluation of alternative models of limb evolution in scincid lizards

Phylogenetic approaches to inferring ancestral character states are becoming increasingly sophisticated; however, the potential remains for available methods to yield strongly supported but inaccurate ancestral state estimates. The consistency of ancestral states inferred for two or more characters affords a useful criterion for evaluating ancestral trait reconstructions. Ancestral state estimates for multiple characters that entail plausible phenotypes when considered together may reasonably be assumed to be reliable. However, the accuracy of inferred ancestral states for one or more characters may be questionable where combined reconstructions imply implausible phenotypes for a proportion of internal nodes. This criterion for assessing reconstructed ancestral states is applied here in evaluating inferences of ancestral limb morphology in the scincid lizard clade Lerista. Ancestral numbers of digits for the manus and pes inferred assuming the models that best fit the data entail ancestral digit configurations for many nodes that differ fundamentally from configurations observed among known species. However, when an alternative model is assumed for the pes, inferred ancestral digit configurations are invariably represented among observed phenotypes. This indicates that a suboptimal model for the pes (and not the model providing the best fit to the data) yields accurate ancestral state estimates.     

ABC as a flexible framework to estimate demography over space and time: some cons,many pros

The analysis of genetic variation to estimate demographic and historical parameters and to quantitatively compare alternative scenarios recently gained a powerful and flexible approach: the Approximate Bayesian Computation (ABC). The likelihood functions does not need to be theoretically specified, but posterior distributions can be approximated by simulation even assuming very complex population models including both natural and human‐induced processes. Prior information can be easily incorporated and the quality of the results can be analysed with rather limited additional effort. ABC is not a statistical analysis per se, but rather a statistical framework and any specific application is a sort of hybrid between a simulation and a data‐analysis study. Complete software packages performing the necessary steps under a set of models and for specific genetic markers are already available, but the flexibility of the method is better exploited combining different programs. Many questions relevant in ecology can be addressed using ABC, but adequate amount of time should be dedicated to decide among alternative options and to evaluate the results. In this paper we will describe and critically comment on the different steps of an ABC analysis, analyse some of the published applications of ABC and provide user guidelines.     

Statistical properties of the ordinary least-squares,generalized least-squares,and minimum-evolution methods of phylogenetic inference

Summary Statistical properties of the ordinary least-squares (OLS), generalized least-squares (GLS), and minimum-evolution (ME) methods of phylogenetic inference were studied by considering the case of four DNA sequences. Analytical study has shown that all three methods are statistically consistent in the sense that as the number of nucleotides examined (m) increases they tend to choose the true tree as long as the evolutionary distances used are unbiased. When evolutionary distances (d_ij's) are large and sequences under study are not very long, however, the OLS criterion is often biased and may choose an incorrect tree more often than expected under random choice. It is also shown that the variance-covariance matrix of d_ij's becomes singular as d_ij's approach zero and thus the GLS may not be applicable when d_ij's are small. The ME method suffers from neither of these problems, and the ME criterion is statistically unbiased. Computer simulation has shown that the ME method is more efficient in obtaining the true tree than the OLS and GLS methods and that the OLS is more efficient than the GLS when d_ij's are small, but otherwise the GLS is more efficient.Offprint requests to: M. Nei     

Inference of Multisite Phosphorylation Rate Constants and Their Modulation by Pathogenic Mutations

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