Pairwise comparison matrices and the error-free property of the decision maker

Pairwise comparison is a popular assessment method either for deriving criteria-weights or for evaluating alternatives according to a given criterion. In real-world applications consistency of the comparisons rarely happens: intransitivity can occur. The aim of the paper is to discuss the relationship between the consistency of the decision maker—described with the error-free property—and the consistency of the pairwise comparison matrix (PCM). The concept of error-free matrix is used to demonstrate that consistency of the PCM is not a sufficient condition of the error-free property of the decision maker. Informed and uninformed decision makers are defined. In the first stage of an assessment method a consistent or near-consistent matrix should be achieved: detecting, measuring and improving consistency are part of any procedure with both types of decision makers. In the second stage additional information are needed to reveal the decision maker’s real preferences. Interactive questioning procedures are recommended to reach that goal

Analysis of pairwise comparison matrices: an empirical research

Pairwise comparison (PC) matrices are used in multi-attribute decision problems (MADM) in order to express the preferences of the decision maker. Our research focused on testing various characteristics of PC matrices. In a controlled experiment with university students (N = 227) we have obtained 454 PC matrices. The cases have been divided into 18 subgroups according to the key factors to be analyzed. Our team conducted experiments with matrices of different size given from different types of MADM problems. Additionally, the matrix elements have been obtained by different questioning procedures differing in the order of the questions. Results are organized to answer five research questions. Three of them are directly connected to the inconsistency of a PC matrix. Various types of inconsistency indices have been applied. We have found that the type of the problem and the size of the matrix had impact on the inconsistency of the PC matrix. However, we have not found any impact of the questioning order. Incomplete PC matrices played an important role in our research. The decision makers behavioral consistency was as well analyzed in case of incomplete matrices using indicators measuring the deviation from the final order of alternatives and from the final score vector

Transcranial Direct Current Stimulation Improves Isometric Time to Exhaustion of the Knee Extensors

Transcranial direct current stimulation (tDCS) can increase cortical excitability of a targeted brain area, which may affect endurance exercise performance. However, optimal electrode placement for tDCS remains unclear. We tested the effect of two different tDCS electrode montages for improving exercise performance. Nine subjects underwent a control (CON), placebo (SHAM) and two different tDCS montage sessions in a randomized design. In one tDCS session, the anodal electrode was placed over the left motor cortex and the cathodal on contralateral forehead (HEAD), while for the other montage the anodal electrode was placed over the left motor cortex and cathodal electrode above the shoulder (SHOULDER). tDCS was delivered for 10min at 2.0mA, after which participants performed an isometric time to exhaustion (TTE) test of the right knee extensors. Peripheral and central neuromuscular parameters were assessed at baseline, after tDCS application and after TTE. Heart rate (HR), ratings of perceived exertion (RPE), and leg muscle exercise-induced muscle pain (PAIN) were monitored during the TTE. TTE was longer and RPE lower in the SHOULDER condition (P0.05). In all conditions maximal voluntary contraction (MVC) significantly decreased after the TTE (P<0.05) while motor-evoked potential area (MEP) increased after TTE (P<0.05). These findings demonstrate that SHOULDER montage is more effective than HEAD montage to improve endurance performance, likely through avoiding the negative effects of the cathode on excitability

Use of questionnaire-based data to assess dog personality

AbstractThe study of dog personality is of general academic interest and also has applications for the management of both working dogs and pets. However, acquiring direct behavioral assessments of large numbers of animals is both time consuming and logistically difficult. An alternative approach that is becoming increasingly common is the collection of questionnaire-based information directly from dog owners. In this review, we discuss some commonly used questionnaires for dog personality traits and findings that have been published using these tools. We suggest that the use of such questionnaires may contribute to research that is based on estimation of effects from large sample sizes, for example, genomic analyses of dog personality traits

Evaluation of a Partial Genome Screening of Two Asthma Susceptibility Regions Using Bayesian Network Based Bayesian Multilevel Analysis of Relevance

Genetic studies indicate high number of potential factors related to asthma. Based on earlier linkage analyses we selected the 11q13 and 14q22 asthma susceptibility regions, for which we designed a partial genome screening study using 145 SNPs in 1201 individuals (436 asthmatic children and 765 controls). The results were evaluated with traditional frequentist methods and we applied a new statistical method, called Bayesian network based Bayesian multilevel analysis of relevance (BN-BMLA). This method uses Bayesian network representation to provide detailed characterization of the relevance of factors, such as joint significance, the type of dependency, and multi-target aspects. We estimated posteriors for these relations within the Bayesian statistical framework, in order to estimate the posteriors whether a variable is directly relevant or its association is only mediated. With frequentist methods one SNP (rs3751464 in the FRMD6 gene) provided evidence for an association with asthma (OR = 1.43(1.2–1.8); p = 3×10−4). The possible role of the FRMD6 gene in asthma was also confirmed in an animal model and human asthmatics. In the BN-BMLA analysis altogether 5 SNPs in 4 genes were found relevant in connection with asthma phenotype: PRPF19 on chromosome 11, and FRMD6, PTGER2 and PTGDR on chromosome 14. In a subsequent step a partial dataset containing rhinitis and further clinical parameters was used, which allowed the analysis of relevance of SNPs for asthma and multiple targets. These analyses suggested that SNPs in the AHNAK and MS4A2 genes were indirectly associated with asthma. This paper indicates that BN-BMLA explores the relevant factors more comprehensively than traditional statistical methods and extends the scope of strong relevance based methods to include partial relevance, global characterization of relevance and multi-target relevance