Effect Sizes in Qualitative Research: A Prolegomenon

The American Psychological Association Task Force recommended that researchers always report and interpret effect sizes for quantitative data. However, no such recommendation was made for qualitative data. Thus, the first objective of the present paper is to provide a rationale for reporting and interpreting effect sizes in qualitative research. Arguments are presented that effect sizes enhance the process of verstehen/hermeneutics advocated by interpretive researchers. The second objective of this paper is to provide a typology of effect sizes in qualitative research. Examples are given illustrating various applications of effect sizes. For instance, when conducting typological analyses, qualitative analysts only identify emergent themes; yet, these themes can be quantitized to ascertain the hierarchical structure of emergent themes. The final objective is to illustrate how inferential statistics can be utilized in qualitative data analyses. This can be accomplished by treating words arising from individuals, or observations emerging from a particular setting, as sample units of data that represent the total number of words/observations existing from that sample member/context. Heuristic examples are provided to demonstrate how inferential statistics can be used to provide more complex levels of verstehen than is presently undertaken in qualitative research.     

各向异性厚板固有频率的精确解

该文抛弃薄板理论的位移和应力假设，利用矩阵分析和三维弹性动力学理论，导出四边简支各向异性厚板的固有频率方程。该方法可推广应用于各向异性层合板动力分析。     

Combining information for prediction in linear regression

This article deals with the prediction problem in linear regression where the measurements are obtained using k different devices or collected from k different independent sources. For the case of k=2, a Graybill-Deal type combined estimtor for the regression parameters is shown to dominate the individual least squares estimators under the covariance criterion. Two predictors ŷ _c and ŷ _p are proposed. ŷ _c is based on a combined estimator of the regression coefficient vector, and ŷ _p is obtained by combining the individual predictors from different models. Prediction mean square errors of both predictors are derived. It is shown that the predictor ŷ _p is better than the individual predictors for k≥2 and the predictor ŷ _c is better than the individual predictors for k=2. Numerical comparison between ŷ _c and ŷ _p shows that the former is superior to the latter for the case k=2.     

Economic analysis of the impact of adopting herd health control programs on smallholder dairy farms in Central Thailand

The economic impact of adopting herd health programs for mastitis and reproduction by small-scale dairy producers of Central Thailand was assessed using a policy analysis matrix (PAM). Following a reduction in the incidence of bovine disease on adopter farms, an increase in private net profits is observed. More importantly the social costs of supporting dairy farmers is reduced; the PAM effective protection coefficient was reduced by 35% for mastitis program adopters and by 44% for reproductive program adopters, indicating improved social efficiency of dairy policy. Other indicators of efficiency and policy implications are discussed.     

EMBEDDED MATRICES FOR FINITE MARKOV CHAINS

For an arbitrary subset A of the finite state space 5 of a Markov chain the so–called embedded matrix P _A is introduced. By use of these matrices formulas expressing all kinds of probabilities can be written down almost automatically, and calculated very easily on a computer. Also derivations can be given very systematically.     

Progressive stress accelerated life tests under finite mixture models

In this paper, progressive stress accelerated life tests are considered when the lifetime of a product under use condition follows a finite mixture of distributions. The experiment is performed when each of the components in the mixture follows a general class of distributions which includes, among others, the Weibull, compound Weibull, power function, Gompertz and compound Gompertz distributions. It is assumed that the scale parameter of each component satisfies the inverse power low, the progressive stress is directly proportional to time and the cumulative exposure model for the effect of changing stress holds. Based on type-I censoring, the maximum likelihood estimates (MLEs) of the parameters under consideration are obtained. A special attention is paid to a mixture of two Rayleigh components. Simulation results are carried out to study the precision of the MLEs and to obtain confidence intervals for the parameters involved.     

Forecasting economic time series with unconditional time-varying variance

The classical forecasting theory of stationary time series exploits the second-order structure (variance, autocovariance, and spectral density) of an observed process in order to construct some prediction intervals. However, some economic time series show a time-varying unconditional second-order structure. This article focuses on a simple and meaningful model allowing this nonstationary behaviour. We show that this model satisfactorily explains the nonstationary behaviour of several economic data sets, among which are the U.S. stock returns and exchange rates. The question of how to forecast these processes is addressed and evaluated on the data sets.     

基于风险矩阵的物流外包风险评估

分析了物流外包中存在的风险，将风险矩阵引入到物流外包的风险评估中，为物流外包提供了一种结构性风险评估方法。并以某生产企业配送外包为例对风险矩阵的应用进行了说明。     

A note on the determination of A-optimal type block designs under fixed and mixed effects models

In this paper, we consider the problem of estimating a selected set of contrasts between v treatments using a block design consisting of b blocks of size k. Traditionally, the construction of A-optimal block designs for such situations has been carried out assuming a fixed effects model. In this paper, we show that A-optimal designs constructed under a fixed effects model are robust in the sense that these designs have maximal minimal efficiency when considered among all available designs and under all possible mixed effects models. AMS 1991 subject classifications: Primary 62K05; Secondary 62K10     

The Application of Sensitivity Analysis on Comprehensive Transportation Evaluation

Comprehensive transportation evaluation objects using multi-objective decision method is a process of choosing the best one from a few objects through calculating, analyzing, and comparing the index system. The result may be different because of the difference of the index weight and index value. Therefore, sensitivity analysis should be one of the necessary parts of the decision-making. It is desired to give the index with higher sensitivity and its varying scope to control the index strictly during the execution process. This paper derives transfer index weight, which changes the rank evaluation order of the projects. Meanwhile, a simple, effective and practical method based on sensitivity district and sensitivity matrix is proposed for the sensitivity analysis of decision-making. As an example, the index sensitivity in decision-making of some provinces comprehensive transportation objects, and their influence on the final decision are discussed.