Reliability coefficient

The reliahility coefficient (R) is the ratio of between-subject variation to total variation. This is another measure of individuality. It is calculated as the between-individual variance divided by the total variation. 

The reliability coefficient will always be between 0 and 1. If it approaches 1, this means that there is very little variation 

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Then one has to utilize special algorithms (software) to calculate reliable coefficients. The appropriate nonlinear parameter (coefficient) estimation should be preferred. Sometimes again it is possible to linearize a nonlinear model. For the above function, e.g., using a logarithmic transformation will give ... 

In Attitude Scaling, the coefficient a created by L.XCronbach is commonly used to test the reliability (Wen Ye 2011). The reliability is acceptable with its internal consistency reliability coefficient a is above 0.50. The internal consistency coefficient between each factor and indicator is calculated (Table 2) and the results show that most elements internal consistency coefficient exceed 0.6, indicating the reliability is acceptable. The a coefficient of both accident loss and the specific location exceed 0.8. The coefficients of the place of accidents and the gas levels are 0.5 which need optimizing on the expression of statements though it can be accepted. 

A complete treatment of these complex topics is beyond the present scope. However, it can be said that standards are such (Potvin et al., 1985) that most published works regarding measurement instruments do address quality of measurements to some extent. Validity (i.e., how well does the measurement reflect the intended quantity) and reliability are most often addressed. However, one could easily be left with the impression that these are binary conditions (i.e., measurement is or is not reliable or valid), when in fact a continuum is required to represent these constructs. Of all attributes that relate to measurement quality, reliability is most commonly expressed in quantitative terms. This is perhaps because statistical methods have been defined and promulgated for the computation of so-called reliabiUty coefficients (Winer, 1971). Reliability coefficients range from 0.0 to 1.0, and the implication is that 1.0 indicates a perfectly reliable or repeatable measurement process. Current methods are adequate, at best, for making... 

ABSTRACT Paper presents problems connected with reliability analysis of the electronic protection systems, with the special regard to the intruder alarm systems. It is presented division of the intruder alarm systems these systems with regard of their structure, and then the analysis for the system with mixed, three branches reliability structure with eventuality of the simultaneously damage of the parallel branches. Utilization of the analysis of reliability structures makes possible the enlargement of the values of the reliability coefficients of the designed systems by accomplishment of the analyses and simulations which allow to select the optimal system structure with regard to the user requirements as well as the characteristics of the protected object (e.g. location of the protected objects in terrain, distances between buildings, etc.). 

Reliability means that scores from an instrument are stable and consistent. Scores should be nearly the same when the researchers administer the instrument multiple times on different occasions. Reliability estimates provide researchers with an idea of how much variation to expect, measured in terms of the reliability coefficient that ranges from 0.00 to 1.00, with no negative values (Fraenkel Wallen, 2006). The three best-known ways to obtain a reliability coefficient are the test-retest method, the equivalent-form method, and the internal-consistency method ... 

The test-retest method involves administering the same test twice to the same group after a certain time interval has elapsed. The reliability coefficient is then calculated to indicate the relationship between the two sets of scores obtained. 

Standardized Cronbach Coefficient Alpha is 0.88. Tucker and Lewis s Reliability Coefficient is 0.93. Kaiser-Meyer-Olkin measure of sampling adequacy is 0.91. According to the variables. Factor 1 is named as Leadership , Factor 2 Assessments and Factor 3 Utilization of measures . For workers, variance explained by each factor are as follows Factor 1 24 %, Factor 2 23 % and Factor 3 23 %. 

In our pilot studies, we tested only the validity of the survey, under the assumption that if it was valid, it would have to have at least moderate reliability. Subsequently, we quantified reliability in two ways. One method utilizes the split-half technique where a person s total response (percent of favorable answers) to one-half of the survey s items (randomly selected) is correlated with his or her total response to the other half If a particular respondent has 67 percent favorable answers on one-half of the questions, we would expect a similar percent favorable from that person on the other half of the questions. Application of this method yielded reliability coefficients in the range of 0.9, indicating a high degree of reliability. 

The reliability coefficients of accidents are comparable only to those in the bus driver studies of Hakkinen and Shaw Sichel but then they are to some... 

As accident retest reliabilities between two periods of time turned out to be low, high correlation coefficients between predictor and accidents could not be expected. Newbold and Cobb (cited in Thorndike 1949) proposed a mathematical model which represents the maximum correlation of reliability that can be obtained between two sets of accident scores and an infallible set of predictive scores. As McBride et al. (1965) pointed out, application of this formula to the accident reliabilities of the California Driver Record Study, which yielded a correlation coefficient of 0.06 over a three year period, produced a maximum reliability coefficient of 0.29 for accidents. In other words, it is... 

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