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Neutrosophic Sets and Systems (23316055) 82pp. 639-654
In plant breeding programs, the augmented design is designated to screen numerous new treatments compared with a few check treatments, which in turn are required to estimate both of error variance and local control for new future treatments. It is well known that the classical augmented design is not suitable for data that are imprecise, uncertain, or undetermined, and these accordingly emerge because of many circumstances beyond humans control. As a result, there is a sever necessity to define a proper generalization for the augmented designs to handle uncertain environments. To be more specific, this work aims to propose an easy to apply approach to treat the augmented randomized complete block design under neutrosophic statistics (NS). This well-defined approach is based on building a neutrosophic ANOVA table, including deriving a suitable test statistics, FN, to handle uncertain settings.This leads to the corresponding neutrosophic hypotheses and the necessary related decision rules. Real data and a series of simulation studies numerically assess the performance of the present method. It will be shown that the neutrosophic method outperforms the classical one, and in effect, it is more flexible than in the presence of indeterminacy. © 2025, University of New Mexico. All rights reserved.
Journal of Loss and Trauma (15325024) 30(2)pp. 218-241
The present study aimed to explore the effectiveness of Trauma-Focused Cognitive Behavioral Therapy (TF-CBT) in facilitating post-traumatic growth, increasing self-compassion, and reducing behavior problems among the children experiencing the 2017 Sarpol-e Zahab (Iran) earthquake. Among earthquake-traumatized 9-12-year-old girls, 24 were selected through purposive sampling. The 24 participants were randomly assigned to the experimental and the control group, each with 12 subjects. The experimental group received 12 sessions of TF-CBT, although 3 subjects left the experimental group during the sessions. Consequently, the analysis included 21 participants: 9 in the experimental group and 12 in the control group. The post-traumatic growth inventory for children revised (PTGI-C-R), the self-compassion scale-short form (SCS-SF), and the Rutter children’s behavior questionnaire for parents were completed at baseline, after the intervention, and one-month follow-up. The results indicated that compared to the control group the participants in the experimental group obtained higher scores in post-traumatic growth and lower scores in behavior problems (i.e., aggression and hyperactivity, and anxiety and depression) (p <.01) which were consistent in the follow-up period. It was also find out that, the experimental group reported higher levels of self-compassion in the follow-up (p <.01). The study suggests that TF-CBT may be effective in improving post-traumatic growth, self-compassion, and behavior problems among children affected by earthquake trauma. © 2024 Taylor & Francis Group, LLC.
Complex and Intelligent Systems (21994536) 10(1)pp. 509-523
The augmented randomized complete block design (ARCBD) is widely used in plant breeding programs to screen numerous new treatments. The error variance is estimated based on the replicated control treatments run over a randomized complete block design and is used to test the new treatments that are administrated each once in the extended units of the blocks. However, one or more observations corresponding to the control treatments may be missed in experiments, making difficulties, e.g., biased estimates. An approximate common approach to deal with this problem is the imputation of the estimated value which is with some uncertainties. Moreover, in real-life experiments, there are more sources of uncertainty that cause conflict-indeterminate, vague, imprecise, and erroneous data that increases the complexity of the analysis. In this paper, an exact scheme is utilized to deal with a missing control treatment in ARCBD. To overcome the problem of indeterminacies in data, a novel neutrosophic analysis approach is proposed. Specifically, the problem of a missing value in an ARCBD for an uncertain environment is resolved analytically by considering an augmented incomplete block design in the framework of neutrosophic statistics so-called neutrosophic augmented randomized complete block design (NARCBD). In this approach, by proposing the neutrosophic model, the neutrosophic estimations as well as the mathematical neutrosophic adjusted sums of squares are derived and the analysis of variance table is provided. The new model is applied to the neutrosophic genotype data example of safflower and assessed by a simulation study. Furthermore, a code in the R software was written to analyze the data based on the proposed approach to fill the calculation gap for data analysis in NARCBD with a missing value. In light of the results observed, it can be concluded that the neutrosophic exact proposed method performs better than the classic in the presence of uncertainty. © The Author(s) 2023.
Current Psychology (19364733) 43(1)pp. 885-899
Although Executive Functions has been considered as the main correlation of ADHD few studies have examined the effect of EFs on ADHD symptoms, in the samples with ADHD. This study aimed to examine the structure of EFs on ADHD students in a hypothesized model. After careful screening of ADHD among 1368 university students (with stratified and multistage cluster sampling), out of them, 211 students with ADHD diagnosis were selected purposefully. They received scales on their emotion regulation, motivation, adult ADHD, deficits in EFs, and diagnostic interview. Emotion regulation and intrinsic motivation were considered as input; behavioral-inhibition, time-management, and problem-solving were the mediators and ADHD subscales were as the output variables. Results showed that the model adequately fit the data. The model fit indices were χ2 = 27.081, df = 1, CFI = 0.99, GFI = 0.97, and PGFI = 0.02. The direct effects of intrinsic-motivation and emotion-regulation on all three mediators and indirect effects of them to ADHD subscales were significant. Based on the results, time-management mediated the relationship between motivation and emotion regulation and ADHD. Among EFs, emotion-regulation and intrinsic-motivation had fundamental influence to other aspects of EFs factors such as behavioral-inhibition, time-management, problem-solving, and attention deficit/hyperactivity disorder. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. corrected publication 2023.
Journal of Applied Psychological Research (22518126) 15(4)pp. 261-282
This study aimed to investigate the effectiveness of group cognitive behavioral therapy on the symptoms of Attention Deficit/Hyperactivity Disorder and the Executive Functions in university students with ADHD. The method was semi-experimental, involving a control group, a pre-test, a post-test, and a one-month follow-up. The statistical population encompasses all students at universities in Isfahan in 2021 who exhibit symptoms of ADHD. Randomly assigned to experimental and control groups, ten males and ten females were selected following the screening. The following research tools were employed: the Barkley Adult ADHD Rating Scale (BAARS-IV), Barkley deficit in Executive Functions Scale (BDEFS), Autistic Spectrum Quotient (ASQ), Mood Disorder Questionnaire (MDQ), Minnesota Multiphasic Personality Inventory (MMPI), Cattell Culture Fair Intelligence Test (CCFIT), and Diagnostic Interview for ADHD (DIVA). The data were processed using repeated measures analysis of variance. The results indicated that group cognitive behavioral therapy significantly reduced the symptoms of all ADHD subscales, with the exception of hyperactivity, and all executive functions subscales. The results of the Bonferroni test indicated the effectiveness of the treatment in the post-test phase for all subscales (except hyperactivity) and the follow-up phase except attention deficit and hyperactivity. It could be concluded that the dimensions of ADHD variable except for hyperactivity and executive functions variable in students with ADHD show significant improvement under the influence of cognitive behavioral therapy. This treatment procedure can be employed by therapists to enhance the health and capabilities of students who are affected. © The Author(s).
Neutrosophic Sets and Systems (23316055) 57pp. 128-138
This paper addresses a novel approach for analyzing augmented Latin square design with uncertain observations, the so-called neutrosophic augmented Latin square design (NALSD). The contribution of our work lies in estimating the effects of rows, columns, control and new treatments, as well as formulating their sums of squares. Moreover, by determining the neutrosophic hypotheses and decision rule, the FN-statistic in NANOVA table is given. The performance of the proposed design is evaluated using a numerical example and simulation study. In light of the results observed, it can find that the NALSD performs better than the classic augmented Latin square design (ALSD) in the presence of uncertainty. © (2023). All Rights Reserved.
Stochastic Environmental Research And Risk Assessment (14363259) 37(8)pp. 2993-3007
Most spatial optimal network designs have been developed for Gaussian processes. However, environmental data rarely conform to this assumption and usually reveal non-Gaussian features such as asymmetry, so there is a need for novel methods that can account for skewness. To overcome this limitation, this article develops an optimal network design based on the closed skew Gaussian process and introduces new optimality criteria for different aims using information measures. In the Bayesian framework, the design that maximizes the average overall observational information is optimal. The effect of skewness on the configuration of points in the optimal design is demonstrated through simulation examples. Besides, the proposed approach is implemented to expand the precipitation monitoring network in Khuzestan province, south of Iran. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
In this study, we considered the problem of design for model discrimination in factorial experiments, while there is potential to miss runs. Under such a situation, we questioned the reliability of the superior selected design based on the existing design criteria for model discrimination. In other words, any selected design may miss its efficiency in discriminating between models in the presence of failing runs. To this end, we assumed the missing probability of the runs based on some available information parameters and developed a new design criterion for model discrimination. The proposed Bayesian criterion makes allowance for counting the missing probabilities of runs. The Bayesian framework also takes into account the intercorrelation between the factorial effects. The numerical examples demonstrate the superiority of the obtained criterion to the existing ones in differentiating the rival design for model discrimination. We also considered the problem of design robustness to missing observations and suggested a ratio criterion for selecting the robust design. It was found that a robust design is not necessarily the most efficient in model discrimination and vice versa. Moreover, we also pointed to the estimation efficiency of the designs and gave a compound dual-task design criterion. © 2022 John Wiley & Sons Ltd.
Soft Computing (14327643) 27(12)pp. 7801-7811
The classic split-plot designs are unable to analyze indeterminate and uncertain data resulting from circumstances beyond our control. To this end, proposing a generalized approach to be applied to split-plot designs in uncertain environments is desired. In this study, a new approach is proposed using neutrosophic statistics to analyze split-plot and split-block designs. By such an approach neutrosophic hypothesis is formulated, a decision rule is suggested, and neutrosophic ANOVA Tables, including the FN-test, are derived. Furthermore, a numerical example and a simulation study are established to evaluate the effectiveness of the proposed designs. The results confirm that the neutrosophic logic of the proposed designs is more efficient and flexible than the classic designs in the event of facing uncertain data. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
Communications in Statistics - Theory and Methods (1532415X) 51(7)pp. 1975-1992
The approximation theory is utilized in optimal design finding by approximating the covariance matrix by the Fisher information matrix; however, the approximation accuracy depends on the sample size. Moreover, the proportion of success, (Formula presented.) may also be important in approximation when the underlying model is logistic. So, in the case of facing a restriction in running a large experiment in addition to facing an extreme (Formula presented.) the usual information matrix may not be enough accurate in approximation. In this study, a locally D-optimal design is proposed for a logistic model based on the quasi-information matrix which was obtained by applying more exact Hammersley-Chapman-Robbins (H-C-R) lower bound for variance approximation. The general equivalence theorem was deficient, so it was adapted. Under such an approach, the obtained optimal design is more efficient than the previous ones in terms of variance and mean square error of the parameter estimates. Furthermore, the probability of infinite estimate of the model parameters is reduced in experiments with extreme proportion of successes at the support points. Therefore, the proposed optimal design performs better for special practical situations. © 2021 Taylor & Francis Group, LLC.
Statistics and Probability Letters (01677152) 169
The common classical approach for finding optimal design is minimizing the variance of an unbiased maximum likelihood estimator (MLE) of parameters. However, under regularity condition, the variance of MLE is approximated by the Cramer–Rao lower bound. In this article, optimal designs are obtained under non-regularity condition in non-linear models. In the Bayesian approach, conditional mutual information is used to propose a new optimality criterion; Bayesian optimal design maximizes the mutual information between the observation and the model parameters. A Bayesian compound criterion is also provided to facilitate the performance comparison of the optimal designs. Finally, the equivalence theorem is given for criterion to allow for checking the optimality of the obtained Bayesian design points. © 2020 Elsevier B.V.
REVSTAT-Statistical Journal (21830371) 18(3)pp. 311-323
Shirakura et al. [12] introduced search probability (SP) in order to compare search designs (SD). Afterwards, the SP-based and other related criteria were developed, all for the normal model. In the present study, we considered a general underlying skew-normal (SN) model and obtained new criteria in a simple explicit form using the Bayesian approach. These criteria are design-dependent and hence are able to rank SDs with respect to their search performance. © 2020, National Statistical Institute. All rights reserved.
BMC Psychology (20507283) 8(1)
Background: Stress-related situations play a significant role in children's lives and result in different reaction in children. Among various methods of evaluating the stressful environment of children, 54-item Children's Coping Strategies Checklist-Revision1 (CCSC-R1) has been developed as one of the most powerful tools for assessing different aspects of coping in children. The purpose of the present study is to find the psychometric properties of Persian CCSC-R1 and to identify the coping strategies used by Iranian children. Method: Subjects included 401 female students aged between 9 and 13 who were subjected to the Sarpol-e-Zahab earthquake (in Northeast of Iran). Construct and convergence validities were examined with confirmatory factor analysis and correlated with Children's Coping Behavior Questionnaire (CCBQ). Reliability was obtained by internal consistency. Using repeated analysis of variance, the status of coping strategies in children were achieved. Results: Confirmatory factor analysis showed a good model fit to the four-factor structure, active coping, distracting action/distraction, avoidance, and support seeking strategies. The results also demonstrated that there was a strong relationship between four-factors of CCSC-R1 including their subscales and CCBQ. Internal consistency (Cronbach's Alpha) for the four dimensions were in the range of 0.76 to 0.88. The findings also showed that Iranian children use active coping, especially optimism, more than other strategies in order to deal with their stressful situations. Conclusions: It is concluded that CCSC-R1 is a valid and reliable instrument which could be employed for Iranian children. Furthermore, in the face of traumatic events, Iranian children acted same as people in individualistic cultures. © 2020 The Author(s).
An active interaction in a main effect plan may cause biased estimation of the parameters in an analysis of variance (ANOVA) model. A fractional factorial design (FFD) with higher order resolution can resolve the alias problem, however, with a considerable number of runs. Alternatively, a search design (SD), the so-called main effect plus k plan (MEP.k), with much less number of runs than FFD, is able to search for k possible active interactions and estimate them in addition to estimating the main effects. However, the existing MEP.k's for 3m factorial experiments are either proposed for a large m (e.g. m≥13) or have a large number of runs. In this paper, we proposed an irregular design for 3m factorial experiments, which is able to identify the active two-factor interactions and estimate them along with estimating the general mean and main effects for 3≤m≤14. The obtained design has fewer runs than the previous designs; meanwhile, it is also comparable and competitive in the discrimination and estimation performances with them. By simulation studies, it is shown that the proposed design does well in model identification and variable selection. © 2020 John Wiley & Sons, Ltd.
Journal of Statistical Planning and Inference (03783758) 198pp. 91-104
Main effect plus one plans (MEP.1) search for a non-zero interaction effect and estimate it in addition to estimate all main effects. A new series of MEP.1 with 2f runs has been constructed and given in this research for 2f factorial experiments for all odd prime power f≥9. Designs in this series are more efficient in estimating the factorial effects than the previous existent MEP.1 with the same number of runs based on D-efficiency criterion. In contrast to the former designs with 2f runs, the D-efficiency of new proposed designs is increasing in f. © 2018 Elsevier B.V.
Statistical Methods in Medical Research (14770334) 28(4)pp. 1170-1187
We propose a nonparametric test for interactions when we are concerned with investigation of the simultaneous effects of two or more factors in a median regression model with right censored survival data. Our approach is developed to detect interaction in special situations, when the covariates have a finite number of levels with a limited number of observations in each level, and it allows varying levels of variance and censorship at different levels of the covariates. Through simulation studies, we compare the power of detecting an interaction between the study group variable and a covariate using our proposed procedure with that of the Cox Proportional Hazard (PH) model and censored quantile regression model. We also assess the impact of censoring rate and type on the standard error of the estimators of parameters. Finally, we illustrate application of our proposed method to real life data from Prospective Observational Multicenter Major Trauma Transfusion (PROMMTT) study to test an interaction effect between type of injury and study sites using median time for a trauma patient to receive three units of red blood cells. The results from simulation studies indicate that our procedure performs better than both Cox PH model and censored quantile regression model based on statistical power for detecting the interaction, especially when the number of observations is small. It is also relatively less sensitive to censoring rates or even the presence of conditionally independent censoring that is conditional on the levels of covariates. © The Author(s) 2018.
Journal of Educators Online (1547500X) 16(2)
Test anxiety is a serious problem for many college students. This study examines the development and validation of the Online Test Anxiety Inventory (OTAI) to evaluate test anxiety among online students. In this study, the OTAI is developed and administered to a sample of 157 postgraduate online students: 77 males and 80 females, aged 22 to 51 years. To design the initial version of the 38-item, Sarason’s Test Anxiety Scale, Abolghsemi’s Test Anxiety Inventory (TAI) and Spielberger’s Test Anxiety Scale were studied, and many interviews were conducted with online learning students who had a high level of test anxiety. Confirmatory Factor Analysis was employed to obtain the Goodness of Fit Indices of the model to the data. The final result is a multidimensional, 18-item OTAI comprised of three factors— online, psychological, and physiological—with a high internal consistency (α = 0.91) and acceptable criterion validity. Concurrent validity was measured by the association of the OTAI and the TAI (r = 0.83). © 2019, Grand Canyon University. All rights reserved.
Journal of Statistical Planning and Inference (03783758) 203pp. 151-159
MEP and MEP.k have been designated for 2 f factorial experiments with at least f and 2f runs, respectively, to estimate all main effects, while the sparsity principle implies that only a small number of factors are active. A supersaturated design is superior in this regard because it focuses on active factors and saves runs. In this paper, we consider the problem of searching for and estimating k 1 and k 2 non-zero main and 2-factor interaction effects, respectively, that are not known a priori. A family of designs has been constructed and given for 2 f factorial experiments with f runs for f≥11, k 1 =2 and k 2 =1. These designs are able to estimate all possible models consisting any set of at most 4 main and 2 2-factor interaction effects. It is shown that the obtained designs are near D-optimal. © 2019 Elsevier B.V.
Social Sciences (discontinued) (18185800) 11(6)pp. 890-902
The purpose of this study was comparing effect of Modular Cognitive-Behavioral Therapy (MCBT) and Child-Parent Relationship Training (CPRT). MCBT is the new treatment form of CBT with modular approach and individual of interventions. CPRT is a method for modification mother-child relationship. This study observed and compared the effectiveness of MCBT and CPRT on children with separation anxiety symptoms. This study is a randomized clinical trial. Subjects were 45 pair mother-child 6-7 years old with diagnosis of SAD, being randomly assigned to MCBT, CPRT and control groups (15 children in each group). Subject children in MCBT group participated in variable 4-20 h weekly sessions within modular cognitive-behavioral therapy manual whereas subject children's mother in CPRT group contributed in 10 h weekly sessions within child-parent relationship training. The control group received no treatment. The screen for children separation anxiety disorder from (Child Symptom Inventory (CSI4), parent forms). Tests administered to all subjects in pretesf posttest and the follow-up measurement (2 and 3 months later). Analysis of variance with repeated measurements were applied to analyze data by Statistical Package for Social Sciences (SPSS) Software package (v. 20). MCBT and CPRT; demonstrated significant difference in reducing separation anxiety disorder from children's parent reports. MCBT in comparison with CPRT; effectively improved reducing separation anxiety in children. © Medwell Journals, 2016.
Statistics (02331888) 49(3)pp. 629-637
Since the introduction of the search design by Srivastava [Designs for searching non-negligible effects. In: Srivastava, editor. A survey of statistical design and linear models. Amsterdam: North-Holland, Elsevier; 1975. p. 507–519], construction of such designs has been considered by many researchers. The efficient performances of constructed search designs in terms of parameter estimation and search ability of parameters have also been investigated by several authors. They have proposed suitable optimality measures such as DD- and AD-optimality for estimation in the early stage of search design construction. Moreover, since 1990s, some criteria have been developed to evaluate search performance of a design. Although these criteria are useful none of them is able to evaluate both estimation and search efficiency of a design simultaneously. In this paper, we propose dual-task criteria to deal with searching and estimating performances of search designs. These compound criteria are weighted multiplication of estimation and search suitable criteria. They will be used for design comparison and the results will be presented. © 2015 Taylor & Francis.
Research Journal of Pharmaceutical, Biological and Chemical Sciences (discontinued) (09758585) 6(3)pp. 231-236
The aim of this study was to compare the effectiveness of the affecting weight lifestyle training and the diet therapy on the body mass index (BMI) in obese adolescents of Yasuj city. Forty five female high school students of Yasuj city who had received a diagnosis of overweight and obesity participated in this study. Subjects were randomly selected and divided into three groups, and their body mass indexes were assessed. Two intervention groups were exposed to the affecting weight lifestyle training and the diet therapy, and the third group (control) did not receive any intervention. Following the treatment period, body mass indexes of the three groups were reassessed. The data were analyzed by implementing Univariate analysis of covariance and Bonferroni post hoc tests. The findings showed that although interventional techniques such as the diet therapy and the affecting weight lifestyle training were effective for weight loss, but the affecting weight lifestyle training was more effective for weight loss.
Australian and New Zealand Journal of Statistics (1467842X) 56(4)pp. 395-405
Summary: By means of a search design one is able to search for and estimate a small set of non-zero elements from the set of higher order factorial interactions in addition to estimating the lower order factorial effects. One may be interested in estimating the general mean and main effects, in addition to searching for and estimating a non-negligible effect in the set of 2- and 3-factor interactions, assuming 4- and higher-order interactions are all zero. Such a search design is called a 'main effect plus one plan' and is denoted by MEP.1. Construction of such a plan, for 2m factorial experiments, has been considered and developed by several authors and leads to MEP.1 plans for an odd number m of factors. These designs are generally determined by two arrays, one specifying a main effect plan and the other specifying a follow-up. In this paper we develop the construction of search designs for an even number of factors m, m≠6. The new series of MEP.1 plans is a set of single array designs with a well structured form. Such a structure allows for flexibility in arriving at an appropriate design with optimum properties for search and estimation. © 2014 Australian Statistical Publishing Association Inc. Published by Wiley Publishing Asia Pty Ltd.
Journal of Statistical Computation and Simulation (15635163) 84(2)pp. 428-437
Asymptotic theory of using the Fisher information matrix may provide poor approximation to the exact variance matrix of maximum likelihood estimation in nonlinear models. This may be due to not obtaining an efficient D-optimal design. In this article, we propose a modified D-optimality criterion, using a more accurate information matrix, based on the Bhattacharyya matrix. The proposed information matrix and its properties are given for two parameters simple logistic model. It is shown that the resulted modified locally D-optimal design is more efficient than the previous one; particularly, for small sample size experiments. © 2012 © 2012 Taylor & Francis.
Torkan, H. ,
Blackwell, S.E. ,
Holmes, E.A. ,
Kalantari, M. ,
Neshat doost, H.T. ,
Maroufi, M. ,
Talebi, H. Cognitive Therapy and Research (01475916) 38(2)pp. 132-145
Cognitive bias modification paradigms training positive mental imagery and interpretation (imagery CBM-I) hold promise for treatment innovation in depression. However, depression is a global health problem and interventions need to translate across settings and cultures. The current pilot study investigated the impact of 1 week of daily imagery CBM-I in treatment-seeking individuals with major depression in outpatient psychiatry clinics in Iran. Further, it tested the importance of instructions to imagine the positive training materials. Finally, we examined the effects of this training on imagery vividness. Thirty-nine participants were randomly allocated to imagery CBM-I, a non-imagery control program, or a no treatment control group. Imagery CBM-I led to greater improvements in depressive symptoms, interpretive bias, and imagery vividness than either control condition at post-treatment (n = 13 per group), and improvements were maintained at 2-week follow-up (n = 8 per group). This pilot study provides first preliminary evidence that imagery CBM-I could provide positive clinical outcomes in an Iranian psychiatric setting, and further that the imagery component of the training may play a crucial role. © 2014 The Author(s).
Esmailzadeh, N. ,
Talebi, H. ,
Momihara, K. ,
Jimbo, M. Journal of Statistical Planning and Inference (03783758) 141(4)pp. 1567-1574
An MEP.1 plan for a 2m factorial experiment is able to search and estimate one possible nonzero interaction effect along with estimating the general mean and main effects. Construction of such a plan has been tackled by several authors. Some of these works are developed for all m, in which are focused on m=2h-1 or m=4λ-1 for positive integers h>2 and λ≥2. This leads to a gap for having MEP.1 plans with well-structured runs set and probably with a reasonable number of treatments for m≠2h-1 or 4λ-1. In this paper, we characterize and present a series of highly structured MEP.1 plans for all odd m=4λ±1,lambda;≥2, with N=2m runs. From these designs one can obtain the MEP.1 plans for even m with N=2m+1 treatments. The exemptions are m= 8 and 9 for which we have 1 or 2 extra runs. © 2010 Elsevier B.V.
Bulletin Of The Iranian Mathematical Society (1017060X) 37(4)pp. 269-279
This paper considers the search problem, introduced by Srivastava [10]. This is a model discrimination problem. In the context of search linear models, discrimination ability of search de- signs has been studied by several researchers. Some criteria have been developed to measure this capability, however, they are re- stricted in a sense of being able to work for searching only one possible nonzero effect. In this paper, two criteria are proposed, based on Kullback-Leibler distance. These criteria are able to eval- uate the search ability of designs, without any restriction on the number of nonzero effects. © 2011 Iranian Mathematical Society.
Communications in Statistics - Theory and Methods (1532415X) 40(4)pp. 635-647
Search design is searching and estimating for a few non zero effects in a large set of effects along with estimation of elements in a set of unknown parameters. In presence of noise, the probability of discrimination between the true non zero effect from an alternative one depends on the design and an unknown parameter, say. We develop a new criterion for design comparison which is independent of and for a family density weight function show that it discriminates and ranks the designs precisely. This criterion is invariance to the variable noise which may be present between designs due to noise factors. This allows us to extend the design comparison to classes of equivalent designs. © Taylor & Francis Group, LLC.
European Journal of Social Sciences (discontinued) (14502267) 15(4)pp. 599-610
Management is increasingly transforming to Knowledge management. This means that we manage Knowledge of people not themselves, and leadership means providing good condition for producing valued Knowledge by human and accomplishing this by the way that persuade people to accountability. Contemporary clear sighted says that Knowledge is considered as the main source of competitive advantage, and for the organizations to achieve such advantage. This paper seeks for Amount of Paying Attention to Knowledge Management in Automobile Industry of Iran. The results indicate that there has been attention to creating, maintaining, and disseminating and applying knowledge management in Automobile Industry Findings of data analysis show that in Iran's automobile industry, attention paid to creating, maintaining, sharing, applying and generally knowledge management has been lower than the intended amount.
Asl, N.S. ,
Dost, H.N. ,
Kalantery, M. ,
Talebi, H. ,
Khosravi, A. Koomesh (23453699) 11(4)pp. 294-302
Introduction: Essential hypertension is one of the most important factors on quality of life and third casual of death in the world. The purpose of the present study was to determine the effect of cognitive behavioral therapy and drug therapy on improvement of quality of life in the patients with essential hypertension. Materials and Methods: This clinical trial was performed in Heart center of Medical Uuniversity of Isfahan (Iran) between April 2007 and April 2008. 40 Patients with essential hypertension were selected randomly and assigned into 2 groups: experimental group that received cognitive behavioral therapy and control group with drug therapy. All of the patients completed the quality of life and a demographic questionnaire before start of interventions as pre test. The post test was completed after the end of intervention and follow up completed after 4 month later. Results: Findings showed that cognitive behavioral therapy was more effective than drug therapy on improvement of quality of life in the patients with essential hypertension in post test and follow up. Conclusion: Cognitive behavioral therapy was effective on improvement of quality of life in the patients with essential hypertension. According to findings of this work, we suggest that team work approach consist of psychologists and heart professional can be useful for treatment of quality of life in the patients with essential hypertension.
Journal of Statistical Planning and Inference (03783758) 36(2-3)pp. 367-383
This paper presents a new series of main effect plans for 2m factorial experiments which permit search and estimation of one nonnegligible effect from two and three factor interactions. Plans in the series are Balanced Arrays (BA) of strength two. A robustness property of such plans is proved. Main effect plans which are near BA of strength two and with the search property, are obtained from the robustness property. Some other plans are also given. © 1993.
