THE EFFECT OF MASCULINE AND FEMININE BRAND NAMES ON THE PERCEIVED TASTE OF A CIGARETTE *

The purpose of the current study was to determine whether brand name can affect the public's evaluation of a product. All subjects smoked identical cigarettes. One group of subjects, however, knew the cigarettes by the name of “Frontiersman,” a masculine name, while the other group knew the cigarettes as “April,” a feminine name. Male and female subjects were asked to rate the cigarette on seven measures. Results show that women gave a more positive evaluation to the cigarette purportedly named “April,” while men gave a more positive evaluation to the identical cigarette when they thought it was named “Frontiersman.” In addition, women reacted more strongly than did men to brand name influence.     

TEACHING EFFECTIVENESS IN THE DECISION SCIENCES: THE USE OF STUDENT EVALUATIONS

This article presents the results of an AIDS-sponsored investigation of teaching effectiveness in the decision sciences. Two national samples were employed in the study: a sample of 247 business school deans and a sample of 3,292 students from 32 different business schools. Included among the findings are that 87 percent of the deans responding indicate they require some sort of faculty teaching effectiveness evaluation, and that great care must be exercised when interpreting student ratings of an individual instructor's teaching effectiveness.     

A COMPARATIVE ANALYSIS OF THE PREDICTIVE ABILITY OF ADAPTIVE FORECASTING,RE-ESTIMATION,AND RE-IDENTIFICATION USING BOX-JENKINS TIME-SERIES ANALYSIS ON QUARTERLY EARNINGS DATA

This paper assesses the predictive ability of the Box-Jenkins methodology when utilized in an on-going setting. Three procedures are utilized to update the original forecasts generated from the Box-Jenkins models: adaptive forecasting, re-estimation, and re-identification. The results indicate that constant monitoring of the structure and parameters of the time-series models are necessary through time. It appears that adaptive forecasting techniques are insufficient to update BJ time-series models when used in conjunction with quarterly earnings data. Re-estimation is recommended as each new observation becomes available. Re-identification procedures are recommended on a less frequent basis.     

SOME TESTS OF BINOMIAL PROBABILITY ASSESSMENTS

A replication of the Alpert-Raiffa probability assessment experiment is used to motivate the development of several tests for evaluating assessors. The tests permit an evaluation of an assessor's accuracy in estimating target quantities and in estimating his own uncertainty as well. Assumption of normal subjective distributions permits the determination of subjective variances. Data from trial assessments are employed to test models which assert that assessed quantities are equal to subjectively assessed error variances. Several tests of the latter type are compared using data from individual, as well as pooled, assessors.     

论小说创作

如果可能,请别写小说.小说创作是一种非社会行为,一旦动笔,小说家会时刻为小说中的人物所困扰;而且,真正写起来,小说指南一类书籍并不管用.假如非写不可,那么,小说家需考虑是以情节为主还是以人物为主.如果以情节为主,小说家即在虚构的事情中间而非在所谓的真实生活中寻找人物的时候,抓住情节不放;如果以人物为主,那么,小说家则需对适于情节的某些特征加以强调,使人物在新环境中显得真实可信,从而赋予他们生命.小说家无论重情节抑或是重人物,都还要考虑以何种形式、何种风格呈现情节和人物的问题;当然,在优秀的小说家笔下,故事和人物本身会以最适合的形式出现.小说家应对形式、人物和语言保持一种敏锐的感觉.此外,小说家可能会对道德教诲产生迷恋.尽管应当通过作品给读者以教益,但是,真诚的艺术家并不能专注于说教.     

Building buy-in: The need for internal relationships and informal coalitions

Significant research has focused on influencing senior leadership, and this study offers new insights into building internal relationships and informal coalitions to provide strategic counsel. These strategies involve internal communications, a neglected area of research and practice. The findings are based on in-depth interviews with 30 executives representing multiple departments in four U.S. companies. A new role justifying public relations’ membership in executive decision teams is internal boundary spanning or gathering intelligence internally across business units, and requires public relations to have a seat at multiple decision tables.     

Mark-specific hazard ratio model with missing multivariate marks

An objective of randomized placebo-controlled preventive HIV vaccine efficacy (VE) trials is to assess the relationship between vaccine effects to prevent HIV acquisition and continuous genetic distances of the exposing HIVs to multiple HIV strains represented in the vaccine. The set of genetic distances, only observed in failures, is collectively termed the ‘mark.’ The objective has motivated a recent study of a multivariate mark-specific hazard ratio model in the competing risks failure time analysis framework. Marks of interest, however, are commonly subject to substantial missingness, largely due to rapid post-acquisition viral evolution. In this article, we investigate the mark-specific hazard ratio model with missing multivariate marks and develop two inferential procedures based on (i) inverse probability weighting (IPW) of the complete cases, and (ii) augmentation of the IPW estimating functions by leveraging auxiliary data predictive of the mark. Asymptotic properties and finite-sample performance of the inferential procedures are presented. This research also provides general inferential methods for semiparametric density ratio/biased sampling models with missing data. We apply the developed procedures to data from the HVTN 502 ‘Step’ HIV VE trial.     

Modeling Correlated Discrete Uncertainties in Event Trees with Copulas

Modeling the dependence between uncertainties in decision and risk analyses is an important part of the problem structuring process. We focus on situations where correlated uncertainties are discrete, and extend the concept of the copula‐based approach for modeling correlated continuous uncertainties to the representation of correlated discrete uncertainties. This approach reduces the required number of probability assessments significantly compared to approaches requiring direct estimates of conditional probabilities. It also allows the use of multiple dependence measures, including product moment correlation, rank order correlation and tail dependence, and parametric families of copulas such as normal copulas, t‐copulas, and Archimedean copulas. This approach can be extended to model the dependence between discrete and continuous uncertainties in the same event tree.     

On testing random effects in the nested-error regression model

We derive an exact F-test for random effects in the nested-error regression model. The derivation utilizes a matrix decomposition that offers a transformation of the response vector into two independent subvectors. When the random effects are absent, the test statistic reduces to a ratio of two independent residual sums of squares that are computed by fitting a regression model using each subvector. A small simulation study compares the power of the F-test with various recent tests and shows that the proposed test has a competitive performance under small as well as large number of clusters.