An Efficient Regression Type Estimator in Survey Sampling

For the estimation of population mean in simple random sampling, an efficient regression-type estimator is proposed which is more efficient than the conventional regression estimator and hence than mean per unit estimator, ratio and product estimators and many other estimators proposed by various authors. Some numerical examples are included for illustration.     

Correction of a bootstrap approach to testing for evolution along lines of least resistance

Testing for an association between the leading vectors of multivariate trait (co)variation within populations (the ‘line of least resistance’) and among populations is an important tool for exploring variational bias in evolution. In a recent study of stickleback fish populations, a bootstrap‐based test was introduced that takes into account estimation error in both vectors and hence improves the previously available bootstrap method. Because this test was implemented incorrectly, however, I here describe the correct test protocol and provide a reanalysis of the original data set. The application of this new test protocol should improve future investigations of evolution along lines of least resistance and other vector comparisons.     

Conditional Maximum Likelihood Estimation Following a Group Sequential Test

We consider estimation after a group sequential test. An estimator that is unbiased or has small bias may have substantial conditional bias (Troendle and Yu, 1999, Coburger and Wassmer, 2001). In this paper we derive the conditional maximum likelihood estimators of both the primary parameter and a secondary parameter, and investigate their properties within a conditional inference framework. The method applies to both the usual and adaptive group sequential test designs. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Interaction of silent and replacement changes in eukaryotic coding sequences

Summary We examined the codon usages in wellconserved and less-well-conserved regions of vertebrate protein genes and found them to be similar. Despite this similarity, there is a statistically significant decrease in codon bias in the less-well-conserved regions. Our analysis suggests that although those codon changes initially fixed under amino acid replacements tend to follow the overall codon usage pattern, they also reduce the bias in codon usage. This decrease in codon bias leads one to predict that the rate of change of synonymous codons should be greater in those regions that are less well conserved at the amino acid level than in the better-conserved regions. Our analysis supports this prediction. Furthermore, we demonstrate a significantly elevated rate of change of synonymous codons among the adjacent codons 5 to amino acid replacement positions. This provides further support for the idea that there are contextual constraints on the choice of synonymous codons in eukaryotes.     

Sampling bias in estimating Design II variance components with S1 families

Summary The use of several S₁ individuals to represent an S₀ individual permits the use of a Design II mating scheme for plants with only one pistillate flower per plant. Estimates of additive (V _A ) and dominance (V _D ) variance from this mating scheme will be biased upwards, when a small number (10) of individuals of each S₁ line are used. This bias can be computed, and the additive and dominance estimates can be corrected. Of particular interest is the observation that the additive genetic variance contributes to bias in estimates of V _D . When S₀ plants are non inbred and their selfedprogeny (S₁ lines) are used to represent them in developing families for use in the Design II, where m₁ is the number of individuals used to represent an S₁ line in developing half sib-families and m₂ is the number of individuals used to represent the S₁ line in making up full sib-families. For example, in a 3×3 Design II, with about 10 individuals used to represent each S₁ line in each cross, m₂ = 10 and m₁ = 30. When m₁ = m₂ = 1, and Joint contribution from Department of Agronomy, University of Nebraska 68583, and the S. S. Cameron Laboratory, Werribee, Victoria 3030, Australia. Published as paper No. 7395, Journal Series     

Phylogenetic relationships of the garter snakes based on DNA sequence and allozyme variation

We estimated phylogenetic relationships among 26 species of garter snakes (genus Thamnophis ) using allozyme and mitochondrial cytochrome b gene nucleotide sequence variation. Parsimony analyses of the two data sets give substantially different estimates of phylogeny. Several lines of evidence indicate that much of this conflict is due to error associated with the restricted number of characters in each data set. Such sampling error may be reduced by combining all the characters; we therefore present an estimate of phylogeny based on parsimony analysis of all the data combined. All our analyses support several conclusions in conflict with previous views: a very distant relationship between T.errans and T. elegans , non-monophyly of the elegans group (even excluding T: errans ), and nesting of the form validus (previously considered a member of the genus Nerodia ) within Thamnophis.
The combined analysis gives an almost fully resolved tree. However, bootstrapping indicates only weak support for many clades in this tree. Furthermore, paraphyly of the assemblages of cytochrome b gene lineages within T. elegans and T. radix indicate the potential for discordance between the mitochondrial DNA (mtDNA) and species phylogenies through the sorting of ancestral mtDNA polymorphisms. These problems suggest the need for assaying additional characters, especially ones likely to be independent of those used in the present study.     

Joyful by nature: approaches to investigate the evolution and function of joy in non-human animals

The nature and evolution of positive emotion is a major question remaining unanswered in science and philosophy. The study of feelings and emotions in humans and animals is dominated by discussion of affective states that have negative valence. Given the clinical and social significance of negative affect, such as depression, it is unsurprising that these emotions have received more attention from scientists. Compared to negative emotions, such as fear that leads to fleeing or avoidance, positive emotions are less likely to result in specific, identifiable, behaviours being expressed by an animal. This makes it particularly challenging to quantify and study positive affect. However, bursts of intense positive emotion (joy) are more likely to be accompanied by externally visible markers, like vocalisations or movement patterns, which make it more amenable to scientific study and more resilient to concerns about anthropomorphism. We define joy as intense, brief, and event-driven (i.e. a response to something), which permits investigation into how animals react to a variety of situations that would provoke joy in humans. This means that behavioural correlates of joy are measurable, either through newly discovered ‘laughter’ vocalisations, increases in play behaviour, or reactions to cognitive bias tests that can be used across species. There are a range of potential situations that cause joy in humans that have not been studied in other animals, such as whether animals feel joy on sunny days, when they accomplish a difficult feat, or when they are reunited with a familiar companion after a prolonged absence. Observations of species-specific calls and play behaviour can be combined with biometric markers and reactions to ambiguous stimuli in order to enable comparisons of affect between phylogenetically distant taxonomic groups. Identifying positive affect is also important for animal welfare because knowledge of positive emotional states would allow us to monitor animal well-being better. Additionally, measuring if phylogenetically and ecologically distant animals play more, laugh more, or act more optimistically after certain kinds of experiences will also provide insight into the mechanisms underlying the evolution of joy and other positive emotions, and potentially even into the evolution of consciousness.     

Bias-reduced estimators of conditional odds ratios in matched case-control studies with unmatched confounding

We study bias-reduced estimators of exponentially transformed parameters in general linear models (GLMs) and show how they can be used to obtain bias-reduced conditional (or unconditional) odds ratios in matched case-control studies. Two options are considered and compared: the explicit approach and the implicit approach. The implicit approach is based on the modified score function where bias-reduced estimates are obtained by using iterative procedures to solve the modified score equations. The explicit approach is shown to be a one-step approximation of this iterative procedure. To apply these approaches for the conditional analysis of matched case-control studies, with potentially unmatched confounding and with several exposures, we utilize the relation between the conditional likelihood and the likelihood of the unconditional logit binomial GLM for matched pairs and Cox partial likelihood for matched sets with appropriately setup data. The properties of the estimators are evaluated by using a large Monte Carlo simulation study and an illustration of a real dataset is shown. Researchers reporting the results on the exponentiated scale should use bias-reduced estimators since otherwise the effects can be under or overestimated, where the magnitude of the bias is especially large in studies with smaller sample sizes.