One of the factors that can be the link between our intentions and actions and their external consequences is human agency, which indicates the conscious design and intentional execution of actions by the individual in order to influence future events.Objective and Method: This research with a developmental approach of psychometric method and method 1, examines the psychometric indices of the Human Factor Characteristics scale using the classical theory of test score measurement and the graduated question-answer theory. The purpose of this study, which included high school students in Tehran, was selected by cluster sampling of 500 people as a sample size and statistical analysis was performed on 481 data. To collect the data, the ion Human Agent Characteristics scale (2011) was used and the research questions were evaluated using IRTPRO and SPSS software.Results:The assumption of local independence based on Pearson x2 index was established by applying Simjima's calibrated question-answer theory and the assumption of being one-dimensional based on the analysis of multidimensional question-answer theory. Diagnosis parameters with question-answer approach and classical approach test score Both item 25 approach had the lowest and item 2 had the highest diagnosis parameter. The answer thresholds for all the questions were so far apart that no option was covered by the other option, and the options were independently selected by individuals at intervals of theta. The total scale was calculated with Cronbach's alpha of 0.945, intentionality of 0.894, foresight of 0.780, self-reactivity of 0.871 and rethinking of 0.762. Also, the role of each item in internal consistency was investigated by the loop method, which all questions had a favorable role in internal consistency of this scale. The value of the validity coefficient obtained from the question-answer theory was obtained by marginal method for intentionality 0.92, forethought 0.85, self-reaction 0.91, rethinking 0.83..

Introduction: Measurement of child anxiety during dental treatment is a challenge during the procedure. Several questionnaires have been developed to assess child anxiety, some of which are pictorial to facilitate their application in children. The aim of the current study was to evaluate validity of new RMS pictorial questionnaire and to compare it with previous scales, including Venham Picture test (VPT) and Facial Image scale (FIS), to assess child dental anxiety during their first visit in a dental office.Materials & Methods: This cross-sectional study was performed on 10 children in Shiraz in 2016, who met the inclusion and exclusion criteria. The children's anxiety was evaluated by RMS-PS, VPT and FIS questionnaires. To assess reliability, questionnaires were given to the children at a two-week interval. Data were analyzed with t-test and regression correlation test (a=0.05).Results: Age and gender had no effect on children's anxiety, but in the presence of preoperative pain, anxiety was significantly higher. RMS had a moderate (r=0.622) and significant (p value<0.001) correlation with VPT questionnaire and a good (r= 0.700) and significant (p value<0.001) correlation with the FIS questionnaire. In addition, the relationship between FIS and VPT questionnaires was moderate (r= 0.623) and significant (p value<0.001).Conclusion: The results showed that RMS questionnaire is not reliable. However, it was valid compared to FIS and VPT questionnaires. Therefore, RMS can be used to indicate child dental anxiety as a proper tool.

Background: Determining real effects on internet dependency is too crucial with unbiased and robust statistical method. MARS is a new non-parametric method in use in the literature for parameter estimations of cause and effect based research. MARS can both obtain legible model curves and make unbiased parametric predictions. Methods: In order to examine the performance of MARS, MARS findings will be compared to Classification and Regression Tree (C&RT) findings, which are considered in the literature to be efficient in revealing correlations between variables. The data set for the study is taken from “The Internet Addiction scale” (IAS), which attempts to reveal addiction levels of individuals. The population of the study consists of 754 secondary school students (301 female, 443 male students with 10 missing data). MARS 2.0 trial version is used for analysis by MARS method and C&RT analysis was done by SPSS. Results: MARS obtained six base functions of the model. As a common result of these six functions, regression equation of the model was found. Over the predicted variable, MARS showed that the predictors of daily Internet-use time on average, the purpose of Internet- use, grade of students and occupations of mothers had a significant effect (P< 0.05). In this comparative study, MARS obtained different findings from C&RT in dependency level prediction.Conclusion: The fact that MARS revealed extent to which the variable, which was considered significant, changes the character of the model was observed in this study.

In this paper, we propose an alternative generalization of a recent test for univariate normality which is based on the empirical moment generating function to the Multivariate case. We show, among other properties, that the proposed weighted L2-class of statistics is affine invariant and consistent. The empirical critical values of the proposed test are evaluated for different sample sizes, variable dimensions and values of the smoothing parameter through large scale simulations. The empirical power comparison of the test with a strong competitor shows that the test has a considerably high power performance, especially at large sample sizes as well as under heavy-tailed alternative distributions. The application of the statistic, together with its competitor, to six real-life datasets also supports the considerable good power performance of the proposed statistic as well as its ease of application.