Modification of the Minimum Logit Chi-Squared Estimator in Simple Linear Logistic Regression

A new modification of Berkson's minimum logit chi-squared estimator in simple linear logistic regression is suggested in order to achieve reduction of first order bias of the estimator as well as in the model. Furthermore, unlike estimators currently available, our procedure is quite simple to apply in practice and is valid even in the presence of zero frequencies in the table.     

Relative Efficiency of Estimators of the Mean of a Normal Distribution when Coefficient of Variation is Known

A biased but simple and consistent estimator of the parameter ? has been obtained for the normal distribution N(?, a?₂), ?>0 where a is a known constant. It is shown that the estimator is more efficient than the sample mean or any suitably chosen constant multiple of the sample standard deviation. It is also proved to be more efficient than the mimumum variance unbiased estimator among a typical class of unbiased estimators derived by RASUL KHAN (1968).     

On the asymptotics of marginal regression splines with longitudinal data

There have been studies on how the asymptotic efficiency ofa nonparametric function estimator depends on the handling ofthe within-cluster correlation when nonparametric regressionmodels are used on longitudinal or cluster data. In particular,methods based on smoothing splines and local polynomial kernelsexhibit different behaviour. We show that the generalized estimationequations based on weighted least squares regression splinesfor the nonparametric function have an interesting property:the asymptotic bias of the estimator does not depend on theworking correlation matrix, but the asymptotic variance, andtherefore the mean squared error, is minimized when the truecorrelation structure is specified. This property of the asymptoticbias distinguishes regression splines from smoothing splines.     

Evolution of the isochore structure in the scale of chromosome: insight from the mutation bias and fixation bias

Following the development of reliable methods for inferring the direction of mutations of the single nucleotide polymorphism (SNP), and the revealing of the human isochore map, it has become possible to investigate the evolution of the isochore structure in a continuous region. In this study, the recent evolution of the isochore structure on human chromosome 18, as inferred from the SNP, was examined. A remarkable mutation bias was found, which was destroying the present isochore structure. However, a fixation bias contributed by the biased gene conversion (BGC) effect and a rising fixation probability of derived alleles with increasing GC content was extending the present isochore structure. Combining the two opposing processes, the old isochore structure was declining and a more homogenous isochore structure with higher GC content was being formed on the chromosome. During this process, both the CpG and genic sites, which were present in the isochore but were paid little attention to before, played an important role. In addition, the recombination was confirmed to promote the GC alleles fixed in the genome because of the BGC effect. For the first time, it was observed that with the occurrence of little recombination, AT alleles had the identical fixation probability with GC alleles in the recombination cold spots.     

Publication bias in ecology and evolution: an empirical assessment using the 'trim and fill' method

Recent reviews of specific topics, such as the relationship between male attractiveness to females and fluctuating asymmetry or attractiveness and the expression of secondary sexual characters, suggest that publication bias might be a problem in ecology and evolution. In these cases, there is a significant negative correlation between the sample size of published studies and the magnitude or strength of the research findings (formally the ‘effect size’). If all studies that are conducted are equally likely to be published, irrespective of their findings, there should not be a directional relationship between effect size and sample size; only a decrease in the variance in effect size as sample size increases due to a reduction in sampling error. One interpretation of these reports of negative correlations is that studies with small sample sizes and weaker findings (smaller effect sizes) are less likely to be published. If the biological literature is systematically biased this could undermine the attempts of reviewers to summarise actual biology relationships by inflating estimates of average effect sizes. But how common is this problem? And does it really effect the general conclusions of literature reviews? Here, we examine data sets of effect sizes extracted from 40 peer‐reviewed, published meta‐analyses. We estimate how many studies are missing using the newly developed ‘trim and fill’ method. This method uses asymmetry in plots of effect size against sample size (‘funnel plots’) to detect ‘missing’ studies. For random‐effect models of meta‐analysis 38% (15/40) of data sets had a significant number of ‘missing’ studies. After correcting for potential publication bias, 21% (8/38) of weighted mean effects were no longer significantly greater than zero, and 15% (5/34) were no longer statistically robust when we used random‐effects models in a weighted meta‐analysis. The mean correlation between sample size and the magnitude of standardised effect size was also significantly negative (r_s=‐0.20, P < 0‐0001). Individual correlations were significantly negative (P < 0.10) in 35% (14/40) of cases. Publication bias may therefore effect the main conclusions of at least 15–21% of meta‐analyses. We suggest that future literature reviews assess the robustness of their main conclusions by correcting for potential publication bias using the ‘trim and fill’ method.     

Data partitioning and correction for ascertainment bias reduce the uncertainty of placental mammal divergence times inferred from the morphological clock

Bayesian estimates of divergence times based on the molecular clock yield uncertainty of parameter estimates measured by the width of posterior distributions of node ages. For the relaxed molecular clock, previous works have reported that some of the uncertainty inherent to the variation of rates among lineages may be reduced by partitioning data. Here we test this effect for the purely morphological clock, using placental mammals as a case study. We applied the uncorrelated lognormal relaxed clock to morphological data of 40 extant mammalian taxa and 4,533 characters, taken from the largest published matrix of discrete phenotypic characters. The morphologically derived timescale was compared to divergence times inferred from molecular and combined data. We show that partitioning data into anatomical units significantly reduced the uncertainty of divergence time estimates for morphological data. For the first time, we demonstrate that ascertainment bias has an impact on the precision of morphological clock estimates. While analyses including molecular data suggested most divergences between placental orders occurred near the K‐Pg boundary, the partitioned morphological clock recovered older interordinal splits and some younger intraordinal ones, including significantly later dates for the radiation of bats and rodents, which accord to the short‐fuse hypothesis.     

Attentional bias in the radial and vertical dimensions of space

Under visual guidance, healthy subjects usually misbisect radial lines farther than, and vertical lines above the true center. It was suggested that radial and vertical misbisection depended on the presence of an attentional bias toward far/upper space. The aim of the present study was to investigate whether such attentional bias depends on a single mechanism or on separate mechanisms. Ninety participants were asked to bisect lines radially and vertically oriented. The results confirmed the presence of a consistent bisection bias farther than (radial lines), and above (vertical lines) the true center. Furthermore, there was a significant correlation between radial and vertical bisection errors. These findings suggest that a single neural mechanism is involved in producing the attentional bias toward far/upper space.     

On the Reduction of Bias of Ratio Estimator to a Desired Degree

This paper advocates a procedure of obtaining an estimator (as a linear combination of a set of ratio estimators) whose bias can be reduced to a desired degree of sample size without any additional loss in efficiency.     

Progress bias versus status quo bias in the ethics of emerging science and technology

How should we handle ethical issues related to emerging science and technology in a rational way? This is a crucial issue in our time. On the one hand, there is great optimism with respect to technology. On the other, there is pessimism. As both perspectives are based on scarce evidence, they may appear speculative and irrational. Against the pessimistic perspective to emerging technology, it has been forcefully argued that there is a status quo bias (SQB) fuelling irrational attitudes to emergent science and technology and greatly hampering useful development and implementation. Therefore, this article starts by analysing the SQB using human enhancement as a case study. It reveals that SQB may not be as prominent in restricting the implementation of emergent technologies as claimed in the ethics literature, because SQB (a) is fuelled by other and weaker drivers than those addressed in the literature, (b) is at best one amongst many drivers of attitudes towards emergent science and technology, and (c) may not be a particularly prominent driver of irrational decision-making. While recognizing that SQB can be one driver behind pessimism, this article investigates other and counteracting forces that may be as strong as SQB. Progress bias is suggested as a generic term for the various drivers of unwarranted science and technology optimism. Based on this analysis, a test for avoiding or reducing this progress bias is proposed. Accordingly, we should recognize and avoid a broad range of biases in the assessment of emerging and existing science and technology in order to promote an open and transparent deliberation.     

On the Probability of a Negative Estimator of Heteroscedasticity in the Random Coefficient Model

In the estimation of a linear regression model with random coefficients, sometimes negative estimates of variances of random coefficients are obtained–an undesirable feature. In this paper we have obtained the asymptotic bounds of the probability of obtaining negative estimators. A simple illustration is also provided for the purpose.