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191.
With today's emphasis on crossfunctional teams, natural work groups, and continuous improvement task forces, companies must learn to formally plan and review the activities of these emerging horizontal organizations. The traditional command-and-control structures had their teams, but they were vertical. Employees belonged to the sales team or the internal audit team, and the boss was responsible for managing the team. Now, with the growing evolution of networking across departmental boundaries, team meeting skills are vital to the success of the teams and their organizations. This article outlines the self-discipline required for teams when they've been granted decision-making authority. 相似文献
192.
Patrick Y.K. Chau 《决策科学》1997,28(2):309-334
Structural equation modeling is a technique that has been widely used for instrument validation and model testing in research in marketing and organizational behavior. The technique has also been introduced to MIS researchers and used in several studies recently reported in the literature. This article offers an example of how the technique can be used for instrument validation and model testing. The illustration is made through a reexamination of a model for evaluating information center (IC) success. With the growth of end-user computing, the success of an IC is more important than ever. Obtaining a valid model for measuring IC success is thus crucial to organizations with ICs. The results of this study highlight the importance of a strong theoretical base in developing such a valid model, and management should be cautious when using these models to assess the performance of their ICs. 相似文献
193.
The dramatic growth of interorganizational systems (IOS) has changed the way organizations conduct their business, and has resulted in significant tangible and intangible benefits being realized by participating firms. However, the implementation of these IOS requires the cooperation and commitment of all the participating members. These members may have complex economic and business relationships among themselves that can result in a number of social, political, and economic factors influencing the adoption and implementation of IOS. This study examines the role of interorganizational and organizational factors on the decision mode for adoption of IOS, in the specific context of electronic data interchange (EDI). Four interorganizational factors, based on the socio-political framework derived from research in marketing, and five organizational factors based on research in IS were used in the study. The data for the study were collected through a large scale field survey. Two respondents, the sales/purchase manager and the IS manager, from 201 firms responded to the survey. The results of discriminant analysis of the data reveal that two interorganizational variables, competitive pressure and exercised power, and two organizational variables, internal need and top management support, are important variables to differentiate firms with proactive decision mode from firms with reactive decision mode. The study also evaluates the differences between proactive and reactive firms on three implementation outcomes. Proactive firms are found to have greater extent of adaptation, more external connectivity with trading partners, and better integration of EDI information in their internal IS applications. 相似文献
194.
195.
Motivated by our meta‐analytic dataset involving survival rates after treatment for critical leg ischemia, we develop and apply a new multivariate model for the meta‐analysis of study level survival data at multiple times. Our data set involves 50 studies that provide mortality rates at up to seven time points, which we model simultaneously, and we compare the results to those obtained from standard methodologies. Our method uses exact binomial within‐study distributions and enforces the constraints that both the study specific and the overall mortality rates must not decrease over time. We directly model the probabilities of mortality at each time point, which are the quantities of primary clinical interest. We also present I2 statistics that quantify the impact of the between‐study heterogeneity, which is very considerable in our data set. © 2014 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd. 相似文献
196.
Jessica K. Paulus Issa J. Dahabreh Ethan M. Balk Esther E. Avendano Joseph Lau Stanley Ip 《Research Synthesis Methods》2014,5(2):152-161
When examining the evidence on therapeutic interventions to answer a comparative effectiveness research question, one should consider all studies that are informative on the interventions' causal effects. “Single group studies” evaluate outcomes longitudinally in cohorts of subjects who are managed with a single treatment strategy. Because these studies are “missing” a direct, concurrent comparison group, they are typically deemed non‐informative on comparative effectiveness. However, in principle, single group studies can provide information on causal treatment effects by extrapolating expected outcomes in the “missing” untreated arm. Single group studies rely on before–after, implicit, or historical comparisons as a proxy for an ideal comparison group. The validity of these comparisons must be carefully examined on a case‐by‐case basis. While in many cases, researchers will disagree on whether such extrapolations are reasonable; circumstances exist where such studies are generally acceptable as a source of evidence. This article provides an overview of issues related to the interpretation of single group studies with a focus on the assumptions required to support their consideration in comparative effectiveness reviews. We discuss the various settings in which single group studies are employed, common research designs that systematic reviewers need to interpret, and challenges associated with using these designs to inform comparative effectiveness questions. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
197.
Regression models play a dominant role in analyzing several data sets arising from areas like agricultural experiment, space experiment, biological experiment, financial modeling, etc. One of the major strings in developing the regression models is the assumption of the distribution of the error terms. It is customary to consider that the error terms follow the Gaussian distribution. However, there are some drawbacks of Gaussian errors such as the distribution being mesokurtic having kurtosis three. In many practical situations the variables under study may not be having mesokurtic but they are platykurtic. Hence, to analyze these sorts of platykurtic variables, a two-variable regression model with new symmetric distributed errors is developed and analyzed. The maximum likelihood (ML) estimators of the model parameters are derived. The properties of the ML estimators with respect to the new symmetrically distributed errors are also discussed. A simulation study is carried out to compare the proposed model with that of Gaussian errors and found that the proposed model performs better when the variables are platykurtic. Some applications of the developed model are also pointed out. 相似文献
198.
In many clinical trials and epidemiological studies, comparing the mean count response of an exposed group to a control group is often of interest. This type of data is often over-dispersed with respect to Poisson variation, and previous studies usually compared groups using confidence intervals (CIs) of the difference between the two means. However, in some situations, especially when the means are small, interval estimation of the mean ratio (MR) is preferable. Moreover, Cox and Lewis [4] pointed out many other situations where the MR is more relevant than the difference of means. In this paper, we consider CI construction for the ratio of means between two treatments for over-dispersed Poisson data. We develop several CIs for the situation by hybridizing two separate CIs for two individual means. Extensive simulations show that all hybrid-based CIs perform reasonably well in terms of coverage. However, the CIs based on the delta method using the logarithmic transformation perform better than other intervals in the sense that they have slightly shorter interval lengths and show better balance of tail errors. These proposed CIs are illustrated with three real data examples. 相似文献
199.
Compositional tables represent a continuous counterpart to well-known contingency tables. Their cells contain quantitatively expressed relative contributions of a whole, carrying exclusively relative information and are popularly represented in proportions or percentages. The resulting factors, corresponding to rows and columns of the table, can be inspected similarly as with contingency tables, e.g. for their mutual independent behaviour. The nature of compositional tables requires a specific geometrical treatment, represented by the Aitchison geometry on the simplex. The properties of the Aitchison geometry allow a decomposition of the original table into its independent and interactive parts. Moreover, the specific case of 2×2 compositional tables allows the construction of easily interpretable orthonormal coordinates (resulting from the isometric logratio transformation) for the original table and its decompositions. Consequently, for a sample of compositional tables both explorative statistical analysis like graphical inspection of the independent and interactive parts or any statistical inference (odds-ratio-like testing of independence) can be performed. Theoretical advancements of the presented approach are demonstrated using two economic applications. 相似文献
200.
In multistate survival analysis, the sojourn of a patient through various clinical states is shown to correspond to the diffusion of 1 C of electrical charge through an electrical network. The essential comparison has differentials of probability for the patient to correspond to differentials of charge, and it equates clinical states to electrical nodes. Indeed, if the death state of the patient corresponds to the sink node of the circuit, then the transient current that would be seen on an oscilloscope as the sink output is a plot of the probability density for the survival time of the patient. This electrical circuit analogy is further explored by considering the simplest possible survival model with two clinical states, alive and dead (sink), that incorporates censoring and truncation. The sink output seen on an oscilloscope is a plot of the Kaplan–Meier mass function. Thus, the Kaplan–Meier estimator finds motivation from the dynamics of current flow, as a fundamental physical law, rather than as a nonparametric maximum likelihood estimate (MLE). Generalization to competing risks settings with multiple death states (sinks) leads to cause‐specific Kaplan–Meier submass functions as outputs at sink nodes. With covariates present, the electrical analogy provides for an intuitive understanding of partial likelihood and various baseline hazard estimates often used with the proportional hazards model. 相似文献