Postal Savings for National Development—The Experience of Japan and Future Perspective in a Globalized World

Global economic forces have been prompting the institutional changes in the public sector based on the market-oriented principles and such changes greatly have affected the postal savings system in Japan. Postal savings system’s public roles were fundamentally changed because of current administrative reform undertakings. In this article, firstly the role of collecting savings from ordinary citizens for fiscal policies was reviewed and the assessment of this public role is conducted. Secondly, abolishment of Universal Service Obligation due to the privatization of the postal savings system and the possible occurrence of Financial Exclusion are analyzed.

An island biogeographical approach to the analysis of butterfly community patterns in newly designed parks

We analyzed the butterfly communities in the newly designed city parks (area C), “newly opened habitat islands”, of Tsukuba City, central Japan. The area constituted a natural ecological experiment on the mainland for clarifying the pattern and process of faunal immigration. We compared butterfly communities in area C with those in two other areas in the light of the theory of island biogeography and the concept of generalist/specialist. Our results showed the following: (1) Fewer species were found in area C than in other areas, due largely to the absence of many specialist types, restricted and habitat specialists, and/or low density species in the area. Generalist types, widespread and habitat generalists, and/or high density species predominated in area C. (2) The difference in the species numbers among the three sections within area C could be explained by the habitat structure in and around the respective sections. (3) The densities of many species were low in area C, probably due to its man-modified habitat structure. In particular, several species occurred at extremely low densities in area C, but at high densities in other areas. (4) The internal structure of the habitat island butterfly community in area C was almost perfectly consistent with that of “quasi-equilibrium” communities that appear during the colonization of an island. Our results demonstrate that the synergetic application of the generalist/specialist concept and the island biogeography theory is effective for the understanding of the patterns and structures of habitat island communities.     

Resolution of evolutionary conflict: a general theory and its applications

While many cases in which conflict over the evolution of social behavior exists even between closely related individuals (e.g., parent-offspring conflict) have been pointed out, little attention has been paid on the problem of where such conflict should lead. A general theory of conflict resolution, however, has recently been developed. The key idea of the theory is the incorporation of conflict costs in the inclusive fitness evaluation. The theory shows that if both sides engaged in the conflict can potentially control the other at a cost, the coevolutionary game of escalating the fight with increased conflict costs always leads either side to give in to the other, resolving the conflict. Here we examine the logical basis of the theory in terms of a simplest example, donor-recipient conflict over the evolution of altruism, and to show its different types of application we review two more specific examples: reproductive-worker conflict over true (sterile) worker evolution in termites and insider-outsider conflict over group size determination. The latter exemplifies the resolution of conflict over the value of a variable (group size in this case) rather than a behavior, suggesting extended applicability of the basic theory.     

Criterion for the Selection of a Working Correlation Structure in the Generalized Estimating Equation Approach for Longitudinal Balanced Data

The generalized estimating equation is a popular method for analyzing correlated response data. It is important to determine a proper working correlation matrix at the time of applying the generalized estimating equation since an improper selection sometimes results in inefficient parameter estimates. We propose a criterion for the selection of an appropriate working correlation structure. The proposed criterion is based on a statistic to test the hypothesis that the covariance matrix equals a given matrix, and also measures the discrepancy between the covariance matrix estimator and the specified working covariance matrix. We evaluated the performance of the proposed criterion through simulation studies assuming that for each subject, the number of observations remains the same. The results revealed that when the proposed criterion was adopted, the proportion of selecting a true correlation structure was generally higher than that when other competing approaches were adopted. The proposed criterion was applied to longitudinal wheeze data, and it was suggested that the resultant correlation structure was the most accurate.     

Conditional estimation using prior information in 2‐stage group sequential designs assuming asymptotic normality when the trial terminated early

Two‐stage designs are widely used to determine whether a clinical trial should be terminated early. In such trials, a maximum likelihood estimate is often adopted to describe the difference in efficacy between the experimental and reference treatments; however, this method is known to display conditional bias. To reduce such bias, a conditional mean‐adjusted estimator (CMAE) has been proposed, although the remaining bias may be nonnegligible when a trial is stopped for efficacy at the interim analysis. We propose a new estimator for adjusting the conditional bias of the treatment effect by extending the idea of the CMAE. This estimator is calculated by weighting the maximum likelihood estimate obtained at the interim analysis and the effect size prespecified when calculating the sample size. We evaluate the performance of the proposed estimator through analytical and simulation studies in various settings in which a trial is stopped for efficacy or futility at the interim analysis. We find that the conditional bias of the proposed estimator is smaller than that of the CMAE when the information time at the interim analysis is small. In addition, the mean‐squared error of the proposed estimator is also smaller than that of the CMAE. In conclusion, we recommend the use of the proposed estimator for trials that are terminated early for efficacy or futility.     

Biodiversity and community structure of temperate butterfly species within a gradient of human disturbance: An analysis based on the concept of generalist vs. Specialist strategies

We monitored nine butterfly communities with varying degrees of human disturbance by conducting a census twice a month during 1980 by the line transect method in and around Tsukuba City, central Japan. We analyzed the biodiversity and community structures using the generalist/specialist concept. The site (community) order based on decreasing human disturbance was positively correlated with butterfly species diversity (H′), species richness (the total number of species), and the number of specialist species in a community, but not with the number of generalist species. The number of generalist species was rather constant, irrespective of the degree of human disturbance. Thus, both the butterfly species diversity and species richness were more dependent on the specialists than the generalists. Our analyses also showed that the generalist species were distributed widely over the communities, and they maintained high population densities, resulting in high rank status in abundance in a community, with more spatial variation in density per species. Specialist species showed the opposite trends. These results demonstrate that the generalist/specialist concept is a powerful tool applicable to analyse the biodiversity and structure of natural communities.     

Age distribution, sex ratio and mortality of the red foxVulpes vulpes in Tochigi, central Japan: an estimation using a museum collection

One hundred and thirty carcasses of the red fox were collected in Tochigi Prefecture, by the Tochigi Prefectural Museum, from 1981 to 1991. The young/adult ratio of the sample was 1.60, which suggests that the hunting pressure has been relatively low in this area. Six percent of the animals were 5 years or older which compares to those taken in Hokkaido, but is higher than those in Europe and North America. The sex ratio for all specimens had a tendency towards male bias (0.587), but this bias was higher for the adult (0.605) than for the young (0.576). Among young (0 year-old) foxes, more individuals were killed on roads than by trapping or shooting (P<0.02, chisquare test). This mortality pattern was caused by high mortality of young males (P<0.02). The proportions of adults killed by the three mortality factors were similar, though only one of the 14 foxes older than 4 years old was shot, probably due to age-linked activity patterns. Most road-kills of young foxes occurred in May when juveniles began exploiting and in November when sub-adults began dispersal. The ratios of road-kills for the whole sample and for adults alone were 42% and 34%, respectively. These high rates of road-kills suggest that the mortality pattern in Tochigi has been affected by factors characteristic of urban environments.     

Sample size calculations for single-arm survival studies using transformations of the Kaplan–Meier estimator

In single-arm clinical trials with survival outcomes, the Kaplan–Meier estimator and its confidence interval are widely used to assess survival probability and median survival time. Since the asymptotic normality of the Kaplan–Meier estimator is a common result, the sample size calculation methods have not been studied in depth. An existing sample size calculation method is founded on the asymptotic normality of the Kaplan–Meier estimator using the log transformation. However, the small sample properties of the log transformed estimator are quite poor in small sample sizes (which are typical situations in single-arm trials), and the existing method uses an inappropriate standard normal approximation to calculate sample sizes. These issues can seriously influence the accuracy of results. In this paper, we propose alternative methods to determine sample sizes based on a valid standard normal approximation with several transformations that may give an accurate normal approximation even with small sample sizes. In numerical evaluations via simulations, some of the proposed methods provided more accurate results, and the empirical power of the proposed method with the arcsine square-root transformation tended to be closer to a prescribed power than the other transformations. These results were supported when methods were applied to data from three clinical trials.     

Effect of heteroscedasticity between treatment groups on mixed‐effects models for repeated measures

Mixed‐effects models for repeated measures (MMRM) analyses using the Kenward‐Roger method for adjusting standard errors and degrees of freedom in an “unstructured” (UN) covariance structure are increasingly becoming common in primary analyses for group comparisons in longitudinal clinical trials. We evaluate the performance of an MMRM‐UN analysis using the Kenward‐Roger method when the variance of outcome between treatment groups is unequal. In addition, we provide alternative approaches for valid inferences in the MMRM analysis framework. Two simulations are conducted in cases with (1) unequal variance but equal correlation between the treatment groups and (2) unequal variance and unequal correlation between the groups. Our results in the first simulation indicate that MMRM‐UN analysis using the Kenward‐Roger method based on a common covariance matrix for the groups yields notably poor coverage probability (CP) with confidence intervals for the treatment effect when both the variance and the sample size between the groups are disparate. In addition, even when the randomization ratio is 1:1, the CP will fall seriously below the nominal confidence level if a treatment group with a large dropout proportion has a larger variance. Mixed‐effects models for repeated measures analysis with the Mancl and DeRouen covariance estimator shows relatively better performance than the traditional MMRM‐UN analysis method. In the second simulation, the traditional MMRM‐UN analysis leads to bias of the treatment effect and yields notably poor CP. Mixed‐effects models for repeated measures analysis fitting separate UN covariance structures for each group provides an unbiased estimate of the treatment effect and an acceptable CP. We do not recommend MMRM‐UN analysis using the Kenward‐Roger method based on a common covariance matrix for treatment groups, although it is frequently seen in applications, when heteroscedasticity between the groups is apparent in incomplete longitudinal data.