The questions of fit in the gregor mendel controversy

Ever since R. A. Fisher published his 1936 article , "Has Mendel's Work Been Rediscovered?", historians of both biclogy and statistics have been fascinated by the surprisingly high conformity between Gregor (Johann) Mendel's observed and expected ratios in his famous experiments with peas. Fisher's calculatftl x² statistic of the experiments, taken as a whole, suggested that results on a par or better than those Mendel reported coultl only be expected to occur about three times in every 100,000 attempts. The ensuing controversy as to whether or not the good Father "sophisticated" his data has continued to this very day. In recent years the controversy has focused upon the more technical question of what underlying genetic arrangement Mendel actually studied.

The statistical issues of the controversy are exam:.led in am historical and comparative perspective. The changes the controversy has gone through are evaluated, and the nature of its current, more biological, status is briefly discussed.     

Interval Estimation for the Difference of Two Independent Variances

Analytical methods for interval estimation of differences between variances have not been described. A simple analytical method is given for interval estimation of the difference between variances of two independent samples. It is shown, using simulations, that confidence intervals generated with this method have close to nominal coverage even when sample sizes are small and unequal and observations are highly skewed and leptokurtic, provided the difference in variances is not very large. The method is also adapted for testing the hypothesis of no difference between variances. The test is robust but slightly less powerful than Bonett's test with small samples.     

A Comparison of Large-Sample Confidence Interval Methods for the Difference of Two Binomial Probabilities

A simulation study was done to compare seven confidence interval methods, based on the normal approximation, for the difference of two binomial probabilities. Cases considered included minimum expected cell sizes ranging from 2 to 15 and smallest group sizes (NMIN) ranging from 6 to 100. Our recommendation is to use a continuity correction of 1/(2 NMIN) combined with the use of (N ? 1) rather than N in the estimate of the standard error. For all of the cases considered with minimum expected cell size of at least 3, this method gave coverage probabilities close to or greater than the nominal 90% and 95%. The Yates method is also acceptable, but it is slightly more conservative. At the other extreme, the usual method (with no continuity correction) does not provide adequate coverage even at the larger sample sizes. For the 99% intervals, our recommended method and the Yates correction performed equally well and are reasonable for minimum expected cell sizes of at least 5. None of the methods performed consistently well for a minimum expected cell size of 2.     

“Me,the street,and a backpack”: employment,income, and physical capital in rural recovery

ABSTRACT

Recovery capital is a framework for understanding individuals’ resources for recovery from substance misuse. In a qualitative analysis of rural individuals in recovery (N = 49), the role of physical capital emerged prominently across ten focus groups. Participants highlighted the effects of employment status, income, and other forms of physical capital directly, as well as indirect effects through changes in human capital. Negative cultural capital components, in the form of stigma and employment discrimination, were described as barriers to physical capital acquisition and successful recovery. Based on these findings, we discuss rural recovery challenges and propose a model of recovery capital interactions.     

Quantal Risk Assessment Database: A Database for Exploring Patterns in Quantal Dose‐Response Data in Risk Assessment and its Application to Develop Priors for Bayesian Dose‐Response Analysis

Quantitative risk assessments for physical, chemical, biological, occupational, or environmental agents rely on scientific studies to support their conclusions. These studies often include relatively few observations, and, as a result, models used to characterize the risk may include large amounts of uncertainty. The motivation, development, and assessment of new methods for risk assessment is facilitated by the availability of a set of experimental studies that span a range of dose‐response patterns that are observed in practice. We describe construction of such a historical database focusing on quantal data in chemical risk assessment, and we employ this database to develop priors in Bayesian analyses. The database is assembled from a variety of existing toxicological data sources and contains 733 separate quantal dose‐response data sets. As an illustration of the database's use, prior distributions for individual model parameters in Bayesian dose‐response analysis are constructed. Results indicate that including prior information based on curated historical data in quantitative risk assessments may help stabilize eventual point estimates, producing dose‐response functions that are more stable and precisely estimated. These in turn produce potency estimates that share the same benefit. We are confident that quantitative risk analysts will find many other applications and issues to explore using this database.     

民族地区地方政府债务状况的评价与建议

目前,有关我国地方债务问题的研究备受关注.民族地区地方政府债务形成和发展与全国具有同步性,但债务压力和债务风险比全国大部分地区形势要严重,其主要来源于“吃饭财政”、土地财政、地方政府融资平台以及自然灾害和其他突发经济社会事件的影响.从理论研究层面和数据实证层面都可以看出,民族地区地方政府债务规模较大、增长较快,且县级债务负担更重,信用违约风险概率更高.因此,应高度重视民族地区地方债务问题,以求尽量客观、完整、准确评价债务风险,全面提高债务管理水平.     

Charity Appeals Using Celebrity Endorsers: Celebrity Attributes Most Predictive of Audience Donation Intentions

We compare the relative influence of different celebrity endorser attributes on respondents’ intentions to donate to a fictitious charity. The celebrity endorser attributes we modeled are expertise, admirability, likeability, trustworthiness, and attractiveness. We examine the moderating effects of audience sex, and general attitudes toward charities. Finally, we examined the mediating effects of perceived endorser fit with the endorsed charity. Our results find that endorser expertise and admirability are significant predictors of audience donation intentions. Audience general attitudes toward charities are a significant moderator of the influence of endorser expertise and admirability on donation intentions. We discuss the implications of our findings for researchers and practitioners.