Emde, M., Fuchs, M.: Need animated faces in web polls: drawbacks and prospects. Surv. Mr. Pract. 5 (2013). www.surveypractice.org/index.php/SurveyPractice/article/view/60 With respect to empirical data, it is often difficult to draw general conclusions, as studies differ on the nature of the issues to be examined, on the characteristics of the sample, on the mode of administration and, in particular, on the nature of the quality indicators used. In addition, there are clear dependencies between characteristics. In this paper, however, my goal is to determine whether there is empirical evidence in the literature, so I will not distinguish the characteristics of the study or the sign of the found effect or the type of indicators. Indeed, the literature takes into account a large number of indicators of measurement quality or their measurement errors. I have considered several types of response style biases, such as extreme and medium reactions and tolerance, non-response to posts and bias as indicators of measurement errors. In addition, I have considered different measures of reliability and validity as indicators of measurement quality.
To directly model Likert binary responses, they can be represented in a binomial form by synthesizing separately consistent and incompreostable responses. The chi-square, Cochran Q or McNemar test are common statistical methods that are used after this transformation. Non-parametric tests such as chi-square, man-whitney test, wilcoxon-character-rank or Kruskal-Wallis test.  are often used in the analysis of Likert scale data. The current distinction in Saris and Gallhofer (2014) is whether or not the labels are separated in different boxes. However, as I have found more choices in the literature, I propose to distinguish between the visual separation of the non-substantial option, the neutral option, the endings, all points or none of the points of the scale. We process the definition, describe important features and provide examples of interval scales that could be particularly useful for your survey strategy. A Likert scale is an evaluation scale that is often found on survey forms and measures how people feel about something.
Technically, this is an ordinal scale with an interval response option. The probability of a threat scenario becoming a threat level and a level of vulnerability to security and indicates the likelihood of a threat scenario appearing within a counterparty. The probability scale can be developed as follows in Table 4.6. Further research is needed for 8 characteristics: whether the polarity of the scales, the agreement between the concept and the polarity of the scale, the information provided by verbal transcripts, the quantifying labels, the symmetry of the scales, the use of a „don`t know“ option, the position of the cursor and the encoding between verbal and numerical labels have or do not influence the quality of the data. Cox III, E.P.: The optimal number of reaction alternatives for a scale. J. Mark. Res. 17, 407-422 (1980). doi:10.2307/3150495 Black, N., Hippler, H.-J.: the numerical values of the evaluation scale: a comparison of their effects in email surveys and telephone interviews. Int. J.
Public Opin. Res. 7, 72-74 (1995). doi:10.1093/ijpor/7.1.72 You can use z.B. a Likert scale to measure how people think about products, services or experiences. Revilla, M.: effect of using different labels for scales in a web survey. Int. J. Mark.
Res. 57, 225-238 (2015). doi:10.2501/IJMR-2014-028 The type of visual representation requires the interviewee to make a more or less significant effort for the response. Below, the different types of visual reaction requirements can be distinguished in the literature: (1) The choice of points is the standard method for representing scales, either a continuous line or categorical options are provided, from which the respondent must show and choose the desired selection; (2) The cursor is a kind of linear implementation in which the respondent should move a marker to give an assessment; (3) Entering the text field is a zon