MCDM methods in strategic planning of forestry on state‐owned lands in Finland: applications and experiences

The forests in Finland have been under intensive planning for decades. Currently, mathematical programming is widely used in planning of wood production. Today's multi‐functional forestry, however, calls for more flexible decision support methods. MCDM tools have been used in responding to fresh planning challenges. For example, the Finnish Forest and Park Service, entrusted with the care of the vast majority of state‐owned natural resources in Finland, endeavours to produce large‐scale natural resource plans satisfying the needs of both economic, social, and ecological sustainability. Participatory approach is applied in the process. Several forestry applications of MCDM methods, particularly those making use of the AHP or the HIPRE program, have been presented. Also, the outranking methods ELECTRE and PROMETHEE have been tested. Due to the nature of forestry applications, statistical techniques for analysing uncertainties in pairwise comparisons and for utilizing interval judgement data have been developed to improve the usability of the AHP. Recently, a hybrid method called A'WOT, making use of the AHP and SWOT, was also introduced into strategic forest planning. This paper summarizes the experiences gained in applying a MAVT and two outranking methods in connection with a participatory natural resource planning process in Finland. In addition, some results of the method development work related to application needs are briefly presented. The details of the planning cases reviewed here have previously been presented in forestry journals. The purpose of this paper is not only to show how MCDM methods have been applied in forestry, but also to discuss the usability and usefulness of MCDM methods from the viewpoint of supporting forestry decision making—and how they might further be improved. Also, some perspectives for the future development work of MCDM applications in the field of natural resource management are focused on. As a conclusion, the use of more than just one MCDM method in a single planning process is seen usually recommendable. In addition, developing hybrid MCDM methods is regarded as a potential direction for future research. Also, closer co‐operation between method developers and appliers is called for to produce more useful applications. Copyright © 2002 John Wiley & Sons, Ltd.     

Statistics and ethics in medical research

Ethical conduct is an essential component in research, especially in medical research. Statistical methods for design and analysis are powerful research tools if used properly. Abuse of these principles and methods are just as unethical as other laboratory or clinical misconduct. Inadequate research design can produce worthless results and thus wastes effort and valuable resources. For clinical research, patient resources are wasted. Inappropriate analysis of data can also produce misleading results and conclusions. For clinical research, inferior therapy might be given to patients as a consequence. These ethical concerns can have implications for and affect the individuals responsible for the statistical design and analysis. Examples are provided which illustrate some possible abuses and inappropriate pressures.     

Effects of serial dependency on the agreement between visual and statistical inference

Comparisons between visual and time-series inferences from behavioral data show that serial dependency in scores is likely to disrupt agreement between the two methods of analysis. If researchers follow an earlier recommendation that time-series analysis be used to supplement or confirm visual analysis, this study's findings suggest that the two methods will disagree most often when the data contain high levels of autocorrelation and when reliable behavorial changes are indicated by time-series analysis.     

The ethics of doing policy relevant science: The precautionary principle and the significance of non-significant results

The precautionary principle is a widely accepted policy norm for decision making under uncertainty in environmental management, However, some of the traditional ways of ensuring trustworthy results used in environmental science and of communicating them work contrary to the general goal of providing the political system and the public with as good an input as possible in the decision making process. For example, it is widely accepted that scientists should only communicate results fulfilling the traditional scientific standard for hypothesis testing. The need for introducing complementary norms in environmental science is illustrated by a recent discussion among scientists on how the precautionary principle should be used in the context of marine biological studies. This discussion highlights the importance of the use of statistical power in communicating scientific results to decision makers and to the general public as well as to the scientific peers. We argue that it would be unethical to report only certainties—because of the need of early warnings—and it would in the same way be unethical to hide the uncertainties. Environmental science can make a better contribution to environmental decision making, if the available knowledge is communicated in a manner which allows for insight on how strong the evidence is.     

DISCIPLINED DECISION MAKING IN AN INTERDISCIPLINARY ENVIRONMENT: SOME IMPLICATIONS FOR CLINICAL APPLICATIONS OF STATISTICAL PROCESS CONTROL

This paper explores some of the implications the statistical process control (SPC) methodology described by Pfadt and Wheeler (1995) may have for analyzing more complex performances and contingencies in human services or health care environments at an organizational level. Service delivery usually occurs in an organizational system that is characterized by functional structures, high levels of professionalism, subunit optimization, and organizational suboptimization. By providing a standard set of criteria and decision rules, SPC may provide a common interface for data-based decision making, may bring decision making under the control of the contingencies that are established by these rules rather than the immediate contingencies of data fluctuation, and may attenuate escalation of failing treatments. SPC is culturally consistent with behavior analysis, sharing an emphasis on data-based decisions, measurement over time, and graphic analysis of data, as well as a systemic view of organizations.     

一种新的统计方法和研究思路——结构方程建模述评

结构方程建模(SEM)是一种新的统计方法和研究思路,近年来在心理学和社会科学领域的应用日益增多。本文在非数学化的基础上,结合心理学研究实例介绍了SEM的渊源、发展、基本概念、分析过程以及相应的计算机统计软件LI-SREL。本文认为SEM有四大优点:①引进潜变量使研究更为深入,②遵循一般线性模式进行验证型分析,使研究更有意义,③妥善处理多变量间的复杂关系,④模型具有参数不变性。SEM应该引起国内心理学界的重视。     

The Effect of Researchers' Focus on Interpretation of Diversity Data

Abstract

The tendency for intercultural researchers to focus primarily on cultural differences instead of both differences and similarities may reflect the emphasis of current statistical methodology toward cultural distance instead of cultural overlap. The authors proposed the cultural similarity index as a way of assessing the extent of communalities between 2 groups. The authors (a) analyzed research (T. Cox, S. Lobel, & P. L. McLeod, 1991; Y. F. Niemann & J. Dovidio, 1998) that placed a primary emphasis on differences, (b) presented alternative insights gained from a focus on similarities, and (c) explored the implications of a research focus on both cultural differences and similarities.     

Chunking or not chunking? How do we find words in artificial language learning?

What is the nature of the representations acquired in implicit statistical learning? Recent results in the field of language learning have shown that adults and infants are able to find the words of an artificial language when exposed to a continuous auditory sequence consisting in a random ordering of these words. Such performance can only be based on processing the transitional probabilities between sequence elements. Two different kinds of mechanisms may account for these data: Participants may either parse the sequence into smaller chunks corresponding to the words of the artificial language, or they may become progressively sensitive to the actual values of the transitional probabilities between syllables. The two accounts are difficult to differentiate because they make similar predictions in comparable experimental settings. In this study, we present two experiments that aimed at contrasting these two theories. In these experiments, participants had to learn 2 sets of pseudo-linguistic regularities: Language 1 (L1) and Language 2 (L2) presented in the context of a serial reaction time task. L1 and L2 were either unrelated (none of the syllabic transitions of L1 were present in L2), or partly related (some of the intra-words transitions of L1 were used as inter-words transitions of L2). The two accounts make opposite predictions in these two settings. Our results indicate that the nature of the representations depends on the learning condition. When cues were presented to facilitate parsing of the sequence, participants learned the words of the artificial language. However, when no cues were provided, performance was strongly influenced by the employed transitional probabilities.     

心理研究中统计方法应用的元分析——以《心理学报》《心理科学》(1998-2008)统计方法应用为例

统计方法在心理研究中得到了广泛的应用。统计方法的应用,除了具备一定的统计方法知识外,还应当了解统计方法应用的必要前提条件。通过调查、分析国内最具代表性的两种杂志《心理学报》、《心理科学》(1998 2008)应用了统计方法的论文(或报告),主要了解哪些统计方法得到最多的应用以及发现应用中存在的一些问题,并对此作了评述。目的是使心理学研究者在心理研究中能更好地应用统计方法分析问题,解决问题。