BAYESIAN ANALYSIS OF THE ADDITIVE MIXED MODEL FOR RANDOMIZED BLOCK DESIGNS

This paper deals with the Bayesian analysis of the additive mixed model experiments. Consider b randomly chosen subjects who respond once to each of t treatments. The subjects are treated as random effects and the treatment effects are fixed. Suppose that some prior information is available, thus motivating a Bayesian analysis. The Bayesian computation, however, can be difficult in this situation, especially when a large number of treatments is involved. Three computational methods are suggested to perform the analysis. The exact posterior density of any parameter of interest can be simulated based on random realizations taken from a restricted multivariate t distribution. The density can also be simulated using Markov chain Monte Carlo methods. The simulated density is accurate when a large number of random realizations is taken. However, it may take substantial amount of computer time when many treatments are involved. An alternative Laplacian approximation is discussed. The Laplacian method produces smooth and very accurate approximates to posterior densities, and takes only seconds of computer time. An example of a pipeline cracks experiment is used to illustrate the Bayesian approaches and the computational methods.     

A time-varying weights tuning method of the double EWMA controller

In recent years, the exponential-weighted-moving-average (EWMA) statistic based controllers are popular in semiconductor manufacturing. However, the single EWMA controller is not sufficient for compensating for the wear-out process. Thus, a double EWMA controller was proposed to enhance the capability for controlling the drifting process. In the literatures, in the solution of the double EWMA controller, only the “trade-off” solution weights are used to tune the controller. However, it is a fixed weight tuning method, and it is known that a time-varying weight will produce a superior performance over that of a fixed one (J. Quality Technol. 29 (1997) 184). Therefore, this study aims to develop a heuristic time-varying weights tuning method for the double EWMA controller. The numerical results showed that the proposed time-varying tuning method possesses an improvement of least 10% over that of the fixed weight scheme.     

Demographic aspects of lactation and postpartum amenorrhea

Interrelations between lactation and post-partum amenorrhea are studied from the reports of about 5,000 married women included in a 1966 Follow-up Survey of Acceptors of an Intrauterine Device (IUD) in Taiwan. The length of post-partum amenorrhea and of breastfeeding are positively associated. On an average, breastfeeding delayed the resumption of menstruation by about 7 months. The association between lactation and amenorrhea is not accounted for by differences in mother’s age, parity, education and her place of residence. A multiple regression analysis suggests that (1) age affects amenorrhea both directly and through lactation, (2) parity has no independent effect on either lactation or amenorrhea, and (3) education and place of residence affect amenorrhea mainly through the cultural variations in the practice of breastfeeding.     

Gender Differences in the Association Between Stress Trajectories and Depressive Symptoms Among Middle Aged and Older Adults in Taiwan

Purpose: This study investigated the effects of gender differences on the association of chronic stress and depressive symptoms in middle-aged and older adults in Taiwan. Methods: The population base was of adults aged 50 and older in Taiwan. This study included 2,889 participants and examined the gender differences on the impacts of life stress that exhibited depressive symptoms. Results: Females were more susceptible to depressive symptoms when they felt constant stress from finances, increasing stress from jobs, and fluctuating stress from family relationships. Discussion: Gender differences were evident when assuming social roles, as were psychological susceptibilities.     

Reducing Requirement Incorrectness and Coping with Its Negative Impact in Information System Development Projects

The negative impact of incorrect requirements on information system development (ISD) project performance has long been acknowledged. This study addresses the problem of incorrect requirements by proposing a model that combines the error reduction and coping concepts proposed by Field, Ritzman, Safizadeh, and Downing (2006) with the view that ISD is a knowledge‐intensive process. The model hypothesizes that when developers and users possess an understanding of each other's primary domain of knowledge, the prevention of incorrect requirements and the mitigation of the negative consequences of incorrect requirements tend to improve project performance. Data collected from 250 ISD professionals on the basis of their experiences of recently completed ISD projects confirmed all of our hypotheses. The results demonstrate that the eliciting of incorrect requirements can be reduced when users and developers possess cross‐domain understanding and when requirement analysis methodologies and techniques are available. Furthermore, the negative impact of incorrect requirements on project performance can be mitigated when developers have sufficient ISD knowledge and behavioral knowledge.     

On some optimal selection procedures for weibull populations

Consider k (k >(>)2) Weibull populations. We shall derive a method of constructing optimal selection procedures to select a subset of the k populations containing the best population which control the size of the selected subset and which maximises the minimum probability of making a correct selection. Procedures and results are derived for the case when sample sizes are unequal. Some tables and figures are given at the end of this paper.     

On the performance of some subset selection procedures

In this paper, we restrict attention to the problem of subset selection of normal populations. The approaches and results of some previous comparison studies of subset selection procedures are discussed briefly. And then the result of a new Monte Carlo study comparing the performance of two classical procedures and the Bayes procedure is presented.     

Likelihood Ratio Tests for the Non Equivalence of Means

We derive likelihood ratio (LR) tests for the null hypothesis of equivalence that the normal means fall into a practical indifference zone. The LR test can easily be constructed and applied to k ≥ 2 treatments. Simulation results indicate that the LR test might be slightly anticonservative statistically, but when the sample sizes are large, it always produces the nominal level for mean configurations under the null hypothesis. More powerful than the studentized range test, the LR test is a straightforward application that requires only current existing statistical tables, with no complicated computations.     

EOQ model for imperfective items under a one-time-only discount

In practice, when a supplier is confronted with extreme completion in markets, unanticipated surplus in inventory, or change in the production run of a product, he/she may offer a special price discount to motivate buyers to order a special quantity. The purpose of the present paper is to investigate an inventory model for imperfective items under a one-time-only discount, where the defectives can be screened out by a 100% screening process and then can be sold in a single batch by the end of the 100% screening process. The optimal order policies associated with three kinds of effective times of the reduced price are obtained. Finally, a numerical example is provided to illustrate the proposed model.