Analysis of genetic changes in radiated and non-radiated bulk oat (Avena sativa L.) populations

Summary In both radiated and non-radiated oat populations inbreeding coefficients increased more slowly than was expected on the assumption of full selfing and equal selective values for homozygotes and heterozygotes. Assuming 1% outcrossing for oats and a selective value of 1.0 for the mean, the heterozygotes for two loci governing crown rust reaction have an advantage of 50% over the homozygotes. This study supports previous observations that the heterozygote often has a decided advantage in predominantly self-pollinated crops.     

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.     

Actuarial senescence in laboratory and field populations of Lepidoptera

1. Recent observations of actuarial senescence – an increase in mortality rate with age – have challenged the assertion that the brevity of adult insect life spans precludes ageing. 2. Here the rate of senescence in 22 species of Lepidoptera was quantified by fitting demographic models to adult survivorship data drawn from a range of field and laboratory studies. 3. Senescence was evident in all 22 species investigated, with a model of age‐related mortality consistently fitting the survivorship curves significantly better than an alternative model which assumes constant mortality. 4. The rates of senescence varied significantly among species. The rates of senescence also differed significantly between sexes for all species tested, but not in a consistent way.     

Describing Ordinal Odds Ratios for Stratified r × c Tables

For an r × ctable with ordinal responses, odds ratios are commonly used to describe the relationship between the row and column variables. This article shows two types of ordinal odds ratios where local‐global odds ratios are used to compare several groups on a c‐category ordinal response and a global odds ratio is used to measure the global association between a pair of ordinal responses. When there is a stratification factor, we consider Mantel‐Haenszel (MH) type estimators of these odds ratios to summarize the association from several strata. Like the ordinary MH estimator of the common odds ratio for several 2 × 2 contingency tables, the estimators are used when the association is not expected to vary drastically among the strata. Also, the estimators are consistent under the ordinary asymptotic framework in which the number of strata is fixed and also under sparse asymptotics in which the number of strata grows with the sample size. Compared to the maximum likelihood estimators, simulations find that the MH type estimators perform better especially when each stratum has few observations. This article provides variances and covariances formulae for the local‐global odds ratios estimators and applies the bootstrap method to obtain a standard error for the global odds ratio estimator. At the end, we discuss possible ways of testing the homogeneity assumption.     

Bias of maximum likelihood estimator of intraclass correlation

Summary A bias correction was derived for the maximum likelihood estimator (MLE) of the intraclass correlation. The bias consisted of two parts: a correction from MLE to the analysis of variance estimator (ANOVA) and the bias of ANOVA. The total possible bias was always negative and depended upon both the degree of correlation and the design size and balance. The first part of the bias was an exact algebraic expression from MLE to ANOVA, and the corrected estimator by this part was ANOVA. It was also shown that the first correction term was equivalent to Fisher's reciprocal bias correction on hisZ scores. The total possible bias of MLE was large for small and moderate samples. Relative biases were larger for small parametric values and vice versa. To ensure a relative bias less than 10% assuming an intraclass correlation of 0.025, which is not unusual in most of the animal genetic studies, the total number of observations (N) should be not less than 500. From a design point of view, minimum bias occurred atn = 2, the minimum family size possible, underN fixed.